Syed Aziz Shah | Privacy-Preserving | Top Researcher Award

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Dr. Syed Aziz Shah | Privacy-Preserving | Top Researcher Award

Associate Professor at Coventry University UK, United Kingdom

Dr. Syed Aziz Shah is a Reader (Associate Professor) at the Research Centre for Intelligent Healthcare at Coventry University, UK, where he specializes in AI-based RF sensing technologies. He also serves as the Post Graduate Research Lead at the same institution. Dr. Shah earned his PhD in Electrical and Electronics Engineering from Xidian University, China, in 2018. His research focuses on advanced sensing techniques, remote patient monitoring, and machine learning applications in healthcare. He has received several prestigious awards, including the UK’s ESPRC New Investigator Award and the Royal Academy of Engineering’s Emerging Leader endorsement for his pioneering work in RF sensing. Dr. Shah has published extensively in high-impact journals and is actively involved in various academic and professional affiliations, including IEEE and the Pakistan Engineering Council.

 

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Education

Dr. Syed Aziz Shah completed his PhD in Electrical and Electronics Engineering at Xidian University, China, from 2015 to 2018. His doctoral research focused on advanced RF sensing technologies, and he gained recognition for his significant contributions to the field. Dr. Shah’s academic journey also includes extensive research and publications in esteemed journals such as IEEE, IET, and MDPI, which earned him several awards, including the Research Excellence Award from Xidian University for achieving the highest number of publications during his PhD studies. His strong educational foundation has been instrumental in his current work at the Research Centre for Intelligent Healthcare at Coventry University, UK, where he leads cutting-edge research in AI-based RF sensing technologies.

Experience

Dr. Syed Aziz Shah currently holds the position of Reader (Associate Professor) in AI-based RF Sensing Technologies at the Research Centre for Intelligent Healthcare, Coventry University, UK, where he has been serving since 2020. In addition, he is the Post Graduate Research Lead at the same institution, overseeing research initiatives and guiding postgraduate research projects. Dr. Shah leads the Healthcare Sensing Technology Group, managing a team of researchers including one Assistant Professor, two Research Fellows, and eight PhD students. He has made significant contributions to the field of intelligent healthcare through his research on AI-based RF sensing technologies, particularly in applications such as remote patient monitoring and fall detection. His leadership extends beyond research, as he also serves as the Outreach Programme Manager at the Institute of Health and Wellbeing at Coventry University, where he works to enhance the institute’s visibility through strategic initiatives. Throughout his career, Dr. Shah has been invited to deliver keynote talks and courses at prestigious institutions such as Imperial College London, University of Bristol, University of Manchester, and University of Leeds, further cementing his position as an expert in the field. He has also supervised several PhD students and served as an external examiner for doctoral theses at various international institutions.

Research Interests

Dr. Syed Aziz Shah’s research interests lie at the intersection of AI-based technologies and RF (Radio Frequency) sensing, with a particular focus on their applications in healthcare. His work explores innovative solutions for remote patient monitoring, human activity recognition, and disease detection through advanced RF sensing techniques. Dr. Shah has contributed extensively to the development of intelligent healthcare systems, using machine learning algorithms to enhance the accuracy and efficiency of RF sensing technologies. His research also delves into the use of intelligent reflecting surfaces in communication systems, aiming to improve the quality and reliability of wireless communications for healthcare applications. Additionally, he is involved in developing AI-driven methodologies to support medical diagnostics, such as contactless respiratory waveform extraction for COVID-19 patients. Dr. Shah is particularly interested in the integration of RF sensing and AI to create cutting-edge solutions for healthcare monitoring and intervention, advancing the field of intelligent healthcare technology.

Skills

Dr. Syed Aziz Shah possesses a robust set of skills in advanced technologies, particularly in the realms of AI-based RF Sensing, Machine Learning, and Signal Processing. His expertise spans RF System Design and the application of Artificial Intelligence in healthcare sensing technologies. He is adept at developing and managing RF sensing solutions for real-time healthcare monitoring, including fall detection and respiratory waveform extraction for remote patient care. Dr. Shah has substantial skills in project management, exemplified through leading large research projects and managing research teams at Coventry University’s Research Centre for Intelligent Healthcare, where he oversees a team comprising Assistant Professors, Research Fellows, and Ph.D. students. Additionally, Dr. Shah is experienced in outreach and pastoral care, having managed outreach initiatives and welfare programs to enhance institutional visibility and student support. His skills in supervision and mentorship are demonstrated by his involvement in Ph.D. supervision and training programs, alongside his role as an external examiner for doctoral research. His technical and leadership skills are further underscored by his active participation as a keynote speaker, course leader, and organizer of academic conferences and workshops, establishing him as a leader in the field of intelligent healthcare and RF sensing technology.

Awards

Dr. Syed Aziz Shah has received several prestigious awards and honors throughout his academic and research career. Notably, he was honored with the UK’s Most Prestigious ESPRC New Investigator Award, a recognition granted to individuals holding academic lectureship positions, which includes a substantial grant of GBP 410,000. This award highlights his pioneering work in RF sensing for remote patient monitoring. Additionally, Dr. Shah was endorsed as an Exceptional Talent: ‘Emerging Leader’ by the Royal Academy of Engineering, UK, in acknowledgment of his groundbreaking contributions to the field of RF sensing technology. This prestigious recognition is given to early-career innovators and scientists who demonstrate exceptional potential and leadership in their field. Furthermore, he received the Research Excellence Award from Xidian University, China, for achieving the highest number of publications in esteemed journals such as IEEE, IET, and MDPI during his Ph.D. studies. As part of this honor, he was also awarded a USD 5,000 reward for his academic achievements. These awards reflect Dr. Shah’s significant impact on the research community, particularly in the area of intelligent healthcare technology and RF sensing.

Publication Top Noted

Title: RF sensing technologies for assisted daily living in healthcare: A comprehensive review

  • Authors: SA Shah, F Fioranelli
  • Journal: IEEE Aerospace and Electronic Systems Magazine
  • Volume: 34
  • Issue: 11
  • Pages: 26-44
  • Cited by: 170
  • Year: 2019

Title: An intelligent non-invasive real-time human activity recognition system for next-generation healthcare

  • Authors: W Taylor, SA Shah, K Dashtipour, A Zahid, QH Abbasi, MA Imran
  • Journal: Sensors
  • Volume: 20
  • Issue: 9
  • Article Number: 2653
  • Cited by: 162
  • Year: 2020

Title: A novel hybrid secure image encryption based on julia set of fractals and 3D Lorenz chaotic map

  • Authors: F Masood, J Ahmad, SA Shah, SS Jamal, I Hussain
  • Journal: Entropy
  • Volume: 22
  • Issue: 3
  • Article Number: 274
  • Cited by: 130
  • Year: 2020

Title: A Review of the State of the Art in Non-Contact Sensing for COVID-19

  • Authors: W Taylor, QH Abbasi, K Dashtipour, S Ansari, SA Shah, A Khalid, et al.
  • Journal: Sensors
  • Volume: 20
  • Issue: 19
  • Article Number: 5665
  • Cited by: 108
  • Year: 2020

Title: Radar sensing for healthcare: The applications of radar in monitoring vital signs and recognizing human activity patterns

  • Authors: DF Fioranelli, DSA Shah, H Li, A Shrestha, DS Yang, DJL Kernec
  • Journal: Electronics Letters
  • Volume: 55
  • Issue: 19
  • Pages: 1022-1024
  • Cited by: 108*
  • Year: 2019

Title: Radar for health care: Recognizing human activities and monitoring vital signs

  • Authors: F Fioranelli, J Le Kernec, SA Shah
  • Journal: IEEE Potentials
  • Volume: 38
  • Issue: 4
  • Pages: 16-23
  • Cited by: 94
  • Year: 2019

Title: Machine learning driven approach towards the quality assessment of fresh fruits using non-invasive sensing

  • Authors: A Ren, A Zahid, A Zoha, SA Shah, MA Imran, A Alomainy, QH Abbasi
  • Journal: IEEE Sensors Journal
  • Volume: 20
  • Issue: 4
  • Pages: 2075-2083
  • Cited by: 89
  • Year: 2019

Title: Human activity recognition: Preliminary results for dataset portability using FMCW radar

  • Authors: SA Shah, F Fioranelli
  • Conference: 2019 International Radar Conference (RADAR)
  • Pages: 1-4
  • Cited by: 73
  • Year: 2019

Title: Freezing of gait detection considering leaky wave cable

  • Authors: X Yang, SA Shah, A Ren, N Zhao, Z Zhang, D Fan, J Zhao, W Wang, et al.
  • Journal: IEEE Transactions on Antennas and Propagation
  • Volume: 67
  • Issue: 1
  • Pages: 554-561
  • Cited by: 64
  • Year: 2018

Conclusion

Dr. Syed Aziz Shah’s exceptional contributions to AI, RF sensing, and intelligent healthcare systems make him a fitting nominee for the Top Researcher Award. His leadership in research, innovative projects, and outstanding academic achievements reflect his dedication to advancing technology for the betterment of society. His accolades, teaching roles, and continued research excellence position him as a trailblazer in his field, deserving of this prestigious recognition.

Liliana Aguilar-Marcelino | Cybersecurity | Best Innovation Award

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Dr. Liliana Aguilar-Marcelino | Cybersecurity | Best Innovation Award

Senior researcher at Instituto Nacional de Investigaciones Forestales Agricolas y Pecuarias, Mexico

Dr. Liliana Aguilar-Marcelino is a senior researcher at the Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad (CENID-SAI) at INIFAP, Mexico. With a focus on microbial consortia, biocontrol, biotechnology, and natural product pharmacology, she investigates the bioactivity of fungi, bacteria, insects, mites, and nematodes. Her work includes exploring sustainable pest control strategies through biocontrol agents and metabolomic studies. Dr. Aguilar-Marcelino has contributed extensively to research on the insecticidal properties of metabolites from edible mushrooms and the development of nematocidal compounds. Her innovative research aims to advance agricultural sustainability and environmental health.

 

Profile

Scopus Profile

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ORCID Profile

Education

Dr. Liliana Aguilar-Marcelino holds a distinguished academic background in the field of biological sciences. She completed her undergraduate studies in biology and later pursued advanced education, specializing in microbiology and biotechnology. Dr. Aguilar-Marcelino obtained her graduate degree (Master’s and/or Ph.D.) from a renowned institution, where she honed her expertise in microbial consortia, biocontrol, biotechnology, and the bioactivity of natural products. Her education has been instrumental in shaping her research focus, which spans a wide array of topics including natural product pharmacology, metabolomics, and the development of sustainable pest management solutions. With her strong academic foundation, Dr. Aguilar-Marcelino has become a leading researcher in her field, contributing significantly to the advancement of agricultural science and sustainable biocontrol technologies.

Experience

Dr. Liliana Aguilar-Marcelino has been a senior researcher at the Centro Nacional de Investigación Disciplinaria en Salud Animal e Inocuidad (CENID-SAI) at INIFAP, Mexico, since 2008. During her tenure, she has focused on pioneering research in microbial consortia, biocontrol, biotechnology, and metabolomics. She has led multiple studies exploring the bioactivity of fungi, bacteria, insects, mites, and nematodes, contributing to the development of sustainable solutions for pest control and agricultural health. Dr. Aguilar-Marcelino has published numerous research papers on topics such as the insecticidal effects of metabolites from edible mushrooms and the nematocidal properties of natural extracts, further establishing her expertise in the field of biocontrol and natural product pharmacology.

Research Interests

Dr. Liliana Aguilar-Marcelino’s research interests are centered on microbial consortia, biocontrol, and biotechnology, with a particular focus on the bioactivity of natural products. She specializes in metabolomics and the pharmacological potential of fungi, bacteria, insects, mites, and nematodes. Her work explores the development of natural pest control methods and sustainable agricultural practices through the study of bioactive compounds derived from edible mushrooms, fungi, and other microorganisms. Additionally, Dr. Aguilar-Marcelino investigates the potential of natural products for managing plant-parasitic nematodes and other agricultural pests, aiming to provide eco-friendly alternatives to traditional chemical controls.

 

Publication Top Noted

Title: New and future developments in microbial biotechnology and bioengineering: Trends of microbial biotechnology for sustainable agriculture and biomedicine systems: Diversity and applications

  • Authors: AA Rastegari, AN Yadav, N Yadav
  • Publisher: Elsevier
  • Cited by: 136
  • Year: 2020

Title: Micro (nano) plastics in wastewater: A critical review on toxicity risk assessment, behaviour, environmental impact, and challenges

  • Authors: S Singh, TSSK Naik, AG Anil, J Dhiman, V Kumar, DS Dhanjal, et al.
  • Journal: Chemosphere
  • Volume: 290
  • Article Number: 133169
  • Cited by: 71
  • Year: 2022

Title: Plasmodium berghei ookinetes induce nitric oxide production in Anopheles pseudopunctipennis midguts cultured in vitro

  • Authors: A Herrera-Ortíz, H Lanz-Mendoza, J Martínez-Barnetche, et al.
  • Journal: Insect Biochemistry and Molecular Biology
  • Volume: 34
  • Issue: 9
  • Pages: 893-901
  • Cited by: 65
  • Year: 2004

Title: The nematophagous fungus Duddingtonia flagrans reduces the gastrointestinal parasitic nematode larvae population in faeces of orally treated calves maintained under tropical conditions

  • Authors: P Mendoza-de-Gives, ME López-Arellano, L Aguilar-Marcelino, et al.
  • Journal: Veterinary Parasitology
  • Volume: 263
  • Pages: 66-72
  • Cited by: 52
  • Year: 2018

Title: Recent Trends in Mycological Research: Volume 1: Agricultural and Medical Perspective

  • Author: AN Yadav
  • Publisher: Springer International Publishing
  • Cited by: 49
  • Year: 2021

Title: Using molecular techniques applied to beneficial microorganisms as biotechnological tools for controlling agricultural plant pathogens and pests

  • Authors: L Aguilar-Marcelino, P Mendoza-de-Gives, LKT Al-Ani, et al.
  • Book: Molecular Aspects of Plant Beneficial Microbes in Agriculture
  • Pages: 333-349
  • Cited by: 47
  • Year: 2020

Title: Jesús Antonio Pineda-Alegría, José Ernesto Sánchez-Vázquez, Manases González-Cortazar, Alejandro Zamilpa, María Eugenia López-Arellano, Edgar Josué Cuevas-Padilla

  • Authors: P Mendoza-de-Gives, L Aguilar-Marcelino
  • Cited by: 69
  • Year: 2018

Conclusion

Dr. Liliana Aguilar-Marcelino’s innovative research in the areas of biocontrol, biotechnology, and natural product pharmacology has led to the development of several novel approaches for sustainable agricultural pest management. By focusing on natural alternatives to chemical pesticides, her work not only advances scientific understanding but also promotes environmentally friendly practices. Through her groundbreaking studies, Dr. Aguilar-Marcelino has significantly contributed to the field of sustainable agriculture, making her an outstanding candidate for the Research for Best Innovation Award.

Zhijiao Chen | Cryptographic Hardware | Best Researcher Award

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Prof. Zhijiao Chen | Cryptographic Hardware | Best Researcher Award

Associate Professor at Beijing University of Post and Telecommunications, China

Prof. Zhijiao Chen is an Associate Professor at Beijing University of Posts and Telecommunications, specializing in millimeter-wave antenna design and wireless communication technologies. He holds a Ph.D. in Antennas from Queen Mary University of London and has a strong background in dielectric resonator antennas, 3D printed antennas, and shaped beam synthesis. Prof. Chen has collaborated with leading institutions worldwide, including the National Physical Laboratory and City University of Hong Kong. His research focuses on high-efficiency antenna arrays for 5G and beyond, as well as innovative materials for antenna design. He is an active member of IEEE and has received multiple awards for his contributions to research and teaching.

 

Profile

Scopus Profile

ORCID Profile

Education

Prof. Zhijiao Chen obtained his PhD from the Antennas Research Group at Queen Mary University of London (2010–2014), under the supervision of Prof. Clive G. Parini, a Fellow of the Royal Academy of Engineering. His doctoral research, awarded in November 2014, laid a strong foundation in advanced antenna design. Prior to his PhD, he completed a BSc in a joint program between Beijing University of Posts and Telecommunications and Queen Mary University of London, graduating with First Class Honors in 2010.

Experience

Currently, Prof. Chen serves as an Associate Professor at the Beijing University of Posts and Telecommunications (2020-present). He previously held a lecturer position there from 2014 to 2020. He has extensive international exposure, having been a Visiting Scholar at institutions like the National Physical Laboratory in the UK (2019), City University of Hong Kong (2018–2019), and Northeastern University in the USA (2013). His collaborations with leading researchers in the field, such as Professors Tian Hong Loh, Chi Hou Chan, and Nian-Xiang Sun, underscore his expertise and contribution to global antenna research.

Research Interests

Prof. Chen’s research interests span critical areas in antenna technology, including millimeter-wave and dielectric resonator antennas, base station antennas, 3D printed antennas, shaped beam synthesis, and bandpass filters. His innovative work in these areas has significant implications for advancing 5G, satellite communication, and vehicular connectivity.

Awards 

Prof. Chen has received multiple accolades throughout his career, reflecting his scholarly impact. Notable awards include the Young Scientists Award at the ACES-China 2021 symposium and the Best Oral Presentation Award at IEEE ICET 2021. His contributions to antenna technology have also earned him first place in the 2020 Ceyear Electronic Measurement Competition and Best Paper Award at IEEE iWAT2013, underscoring his role as a leader in antenna research.

Skills

Prof. Zhijiao Chen specializes in millimeter-wave antennas, dielectric resonator antennas, 3D printed antennas, and beam synthesis for advanced communication systems. His expertise includes high-efficiency antenna arrays, satellite communications, and IoT applications. He is skilled in materials science, particularly in the use of ceramics and dielectric structures for antenna design. Prof. Chen has extensive experience in collaborative research with leading institutions and plays an active role in the academic community as a reviewer, editor, and conference session chair. His work bridges theory and practice, contributing to advancements in wireless communication technologies like 5G and beyond.

Publication Top Noted

  • Great Adventures and Experiences: The IEEE Antennas and Propagation Society Young Professional Ambassador Program [Young Professionals]
    • Author(s): Chen, Z.
    • Journal: IEEE Antennas and Propagation Magazine
    • Year: 2024
    • Volume: 66
    • Issue: 2
    • Pages: 80–83
    • Type: Article, Open Access
    • Abstract & Related Documents: Not available
  • Compact Multibeam Antenna Using Miniaturized Slow-Wave Substrate-Integrated Waveguide Rotman Lens for Satellite-Assisted Internet of Vehicles
    • Author(s): Deng, J.-Y., Liu, Y.-B., Chen, Z., Lin, W.
    • Journal: IEEE Internet of Things Journal
    • Year: 2024
    • Volume: 11
    • Issue: 4
    • Pages: 6848–6856
    • Type: Article
    • Citations: 3
  • FDM 3D-Printed DRA Array for 5G Millimeter Wave and 6G Applications
    • Author(s): Li, S., Izquierdo, B.S., Gao, S., Chen, Z.
    • Conference: IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)
    • Year: 2024
    • Pages: 417–418
    • Type: Conference Paper
    • Citations: 0
  • A Dental Dielectric Resonator Antenna
    • Author(s): Chen, Z., Zhang, J., Jing, Y., Jiang, X., Sanz-Izquierdo, B.
    • Conference: IEEE Antennas and Propagation Society, AP-S International Symposium (Digest)
    • Year: 2024
    • Pages: 1391–1392
    • Type: Conference Paper
    • Citations: 0
  • IWS 2024 Women in Microwaves: Challenge Yourself and Be Proud [Women in Microwaves]
    • Author(s): Li, Z., Chen, Z., Han, Y., Yang, W., Che, W.
    • Journal: IEEE Microwave Magazine
    • Year: 2024
    • Volume: 25
    • Issue: 10
    • Pages: 87–90
    • Type: Conference Paper
    • Citations: 0
  • A W-Band High-Gain Low-Sidelobe Circular-Shaped Monopulse Antenna Array Based on Dielectric Loaded Waveguide
    • Author(s): Zhang, X., Chen, Z., Ye, X.
    • Journal: IEEE Access
    • Year: 2024
    • Volume: 12
    • Pages: 64997–65006
    • Type: Article, Open Access
    • Citations: 2
  • A Wearable Open-Ring Dielectric Resonator Antenna with Frequency Reconfiguration
    • Author(s): Jiang, X., Chen, Z., Sanz-Izquierdo, B.
    • Conference: 18th European Conference on Antennas and Propagation, EuCAP 2024
    • Year: 2024
    • Type: Conference Paper
    • Citations: 0
  • Dielectric Resonator Antennas: Materials, Designs and Applications
    • Author(s): Chen, Z., Deng, J., Liu, H.
    • Book Title: Dielectric Resonator Antennas: Materials, Designs and Applications
    • Year: 2024
    • Pages: 1–301
    • Type: Book
    • Citations: 1
  • Wideband Millimeter-Wave MIMO Antenna with a Loaded Dielectric Cover for High-Gain Broadside Radiation
    • Author(s): Chen, Z., Song, W., Wang, W.
    • Journal: Electronics (Switzerland)
    • Year: 2023
    • Volume: 12
    • Issue: 21
    • Article ID: 4384
    • Type: Article, Open Access
    • Citations: 2
  • Novel B-site Scheelite Structure Ceramic Bi(Ge0.5Mo0.5)O4 and its Dielectric Properties
    • Author(s): Xu, D., Zhang, H., Pang, L., Chen, Z., Zhou, D.
    • Journal: Journal of the American Ceramic Society
    • Year: 2023
    • Volume: 106
    • Issue: 11
    • Pages: 6675–6683
    • Type: Article
    • Citations: 7

Conclusion

Prof. Zhijiao Chen’s extensive academic and research experience, along with his significant contributions to the field of antenna technology and communication systems, make him an outstanding candidate for the Research for Best Researcher Award. His expertise, leadership in research projects, collaboration with international institutions, and recognition within the scientific community underscore his qualifications for this honor.

Adla Padma | Blockchain | Women Researcher Award

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Ms. Adla Padma | Blockchain | Women Researcher Award

Research Scholar at Vellore Institute of Technology, India

Ms. Adla Padma is an Assistant Professor (On Contract) at the School of Computer Science Engineering and Information Systems (SCORE) at Vellore Institute of Technology (VIT), Vellore, Tamil Nadu. With over six years of academic experience, her research focuses on blockchain technology and privacy preservation in IoT environments. Currently pursuing a Ph.D. in Computer Science and Engineering at VIT, Ms. Padma’s thesis explores efficient blockchain frameworks for IoT smart environments. She has published several journal articles and conference papers, including works on scalable blockchain solutions and secure information sharing in smart cities. Ms. Padma has received multiple recognitions, including the Raman Research Award for her significant contributions to blockchain research. She has also actively participated in technical workshops and courses related to blockchain, IoT, and cybersecurity.

Profile:

Education:

Ms. Adla Padma is currently pursuing a Ph.D. in Computer Science and Engineering at Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, with her thesis focusing on “An Efficient Blockchain Enabled Privacy Preservation Framework for IoT Smart Environment.” She holds a Master’s degree in Computer Science and Engineering (M.Tech) from Sri Indu Institute of Engineering and Technology, Rangareddy, Telangana, where she graduated in 2016 with a commendable 82.75%. Prior to that, Ms. Padma completed her Bachelor of Technology (B.Tech) in Computer Science and Engineering from KBR Engineering College, Yadadri Bhuvanagiri, Telangana, in 2012, with a notable percentage of 79.94%. Her educational background also includes an Intermediate from Nalanda Junior College, Nalgonda, Telangana, where she scored an impressive 90%. Ms. Padma’s strong academic foundation has laid the groundwork for her successful career in research and teaching.

Professional Experience:

Ms. Adla Padma has over six years of professional experience in the field of academia, specializing in computer science and engineering. She is currently serving as an Assistant Professor (On Contract) at the School of Computer Science Engineering and Information Systems (SCORE) at Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, where she has been involved in teaching and research since 2022. Prior to this, Ms. Padma worked as an Assistant Professor at Sri Indu Institute of Engineering and Technology, Rangareddy, Telangana, from 2016 to 2020. Throughout her career, she has been dedicated to advancing research in blockchain technology, privacy preservation in IoT environments, and related fields. Ms. Padma has also contributed significantly to academic projects, technical talks, and workshops, further enhancing her expertise in areas like machine learning, web technologies, and programming languages. Her academic journey has been marked by a strong focus on both teaching and research, with an emphasis on integrating cutting-edge technologies into real-world applications.

Research Interests:

Ms. Adla Padma’s research interests primarily revolve around the intersection of blockchain technology, privacy preservation, and the Internet of Things (IoT). She is particularly focused on developing efficient frameworks for privacy protection in smart environments using blockchain, aiming to enhance the security and scalability of IoT applications. Her research also explores the design and analysis of algorithms, machine learning, and programming languages such as C, C++, Python, and Java. Additionally, Ms. Padma is interested in web technologies and their application in secure information sharing, as well as the integration of blockchain for smart city solutions. Through her work, she seeks to contribute to the development of innovative solutions that address pressing challenges in digital security and privacy across various industries.

Awards and Honors:

Ms. Adla Padma has been recognized with several prestigious awards and honors throughout her academic and research career. She received the Raman Research Award at VIT, Vellore, Tamil Nadu, for her impactful publications, including “GLSBIoT: GWO-based enhancement for lightweight scalable blockchain for IoT with trust-based consensus” and “Blockchain Based an Efficient and Secure Privacy Preserved Framework for Smart Cities”. These awards reflect her significant contributions to blockchain technology and privacy preservation. Additionally, Ms. Padma has been appointed as a reviewer for the American Journal of Information Science and Technology for the period of 2024–2027, further solidifying her standing in the research community.

Skills:

Ms. Adla Padma possesses a diverse skill set that spans various domains within computer science and engineering. She is highly proficient in blockchain technology, with a focus on privacy preservation and security frameworks for IoT environments. Her expertise extends to the design and analysis of algorithms, programming languages including C, C++, Python, and Java, as well as web technologies and machine learning. Additionally, Ms. Padma is skilled in conducting research, academic writing, and publishing in high-impact journals. She is also experienced in guiding and mentoring students on technical projects, particularly in the fields of deep learning and IoT. Her technical proficiency is complemented by her ability to design and implement innovative solutions to complex problems in the computing and technology landscape.

Publication Top Noted:

Title: Blockchain based an efficient and secure privacy preserved framework for smart cities

  • Authors: A. Padma, M. Ramaiah
  • Journal: IEEE Access
  • Citations: 19
  • Year: 2024

Title: A review of security vulnerabilities in industry 4.0 applications and the possible solutions using blockchain

  • Authors: M. Ramaiah, V. Chithanuru, A. Padma, V. Ravi
  • Book: Cyber Security Applications for Industry 4.0
  • Pages: 63-95
  • Citations: 17
  • Year: 2022

Title: Detecting security breaches on smart contracts through techniques and tools: A brief review – Applications and challenges

  • Authors: A. Padma, R. Mangayarkarasi
  • Conference: International Conference on Information and Management Engineering
  • Pages: 361-369
  • Citations: 12
  • Year: 2022

Title: GLSBIoT: GWO-based enhancement for lightweight scalable blockchain for IoT with trust-based consensus

  • Authors: A. Padma, M. Ramaiah
  • Journal: Future Generation Computer Systems
  • Volume: 159
  • Pages: 64-76
  • Citations: 8
  • Year: 2024

Title: 4 A Technologies Study on Trending for IoT Use Cases Aspires to Build Sustainable Smart Cities

  • Authors: M. Ramaiah, R. M. Yousuf, R. Vishnukumar, A. Padma
  • Book: Intelligent Systems and Sustainable Computational Models: Concepts
  • Citations: 1
  • Year: 2024

Title: Exploring Explainable AI in Healthcare: Challenges and Future Directions

  • Authors: A. Padma, V. Chithanuru, P. Uppamma, R. Vishnukumar
  • Book: Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry
  • Pages: 199-233
  • Citations: 1
  • Year: 2024

Title: A Survey on importance of English skills for Academics and future growth of scholars

  • Author: A. Padma
  • Source: Retrieved March 3, 2022
  • Citations: 1
  • Year: 2021

Title: Blockchain for Agriculture Technology Supply Chain Management

  • Authors: A. Padma, M. Ramaiah, V. Ravi
  • Book: Intelligent Computing and Optimization for Sustainable Development
  • Year: 2024

Title: Intelligent Connected Vehicle Intrusion Detection and Mitigation: An Analysis of Explainable AI

  • Authors: R. Vishnukumar, A. Padma, M. Ramaiah
  • Conference: 2024 International Conference on Emerging Techniques in Computational …
  • Year: 2024

Title: A hybrid wrapper technique enabled Network Intrusion Detection System for Software-defined networking based IoT networks

  • Authors: M. Ramaiah, A. Padma, R. Vishnukumar, M. Y. Rahamathulla, V. Chithanuru
  • Conference: 2024 3rd International Conference on Artificial Intelligence for Internet of …
  • Year: 2024

Conclusion:

Given her extensive research output, contributions to academia, active involvement in the scientific community, and notable awards, Ms. Adla Padma is a deserving candidate for the Women Researcher Award. Her research not only furthers the understanding of complex technologies but also strives to make them more secure and applicable to real-world challenges, particularly in IoT and smart cities.

Arif Ali | Detection and Prevention | Excellence in Innovation

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Mr. Arif Ali | Detection and Prevention | Excellence in Innovation

Lecuturer at Cadet College Karak, Pakistan, Pakistan

Mr. Arif Ali is a plant scientist with a strong background in molecular genetics, agronomy, and stress physiology. He is currently engaged in research at Hainan University, China, collaborating on projects related to safflower germplasm and lentil genetic markers. Mr. Ali holds a Master’s degree in Plant Sciences from Quaid-i-Azam University, Islamabad, Pakistan, and a Bachelor’s degree in Botany from Islamia College University, Peshawar, Pakistan. With expertise in genome-wide association studies, high-throughput genomic sequencing, and plant stress responses, he has contributed to several publications and research projects aimed at improving crop resilience and agricultural sustainability. Additionally, he has held teaching positions as Head of the Biology Departments at various educational institutions in Pakistan.

Profile:

Education:

Mr. Arif Ali holds a Master’s degree in Plant Sciences from Quaid-i-Azam University, Islamabad, Pakistan, where he completed his thesis on the molecular characterization of the TIN-1 gene locus in winter bread wheat, with a CGPA of 3.77/5. Prior to this, he earned a Bachelor of Science degree in Botany from Islamia College University, Peshawar, Pakistan, graduating with a CGPA of 3.56/4. His academic journey has been marked by a strong focus on plant genetics, molecular biology, and stress physiology, equipping him with a solid foundation to contribute significantly to the field of plant science through research and innovation.

Professional Experience:

Mr. Arif Ali has extensive professional experience in both research and academia. Currently, he is involved in a research collaboration at Hainan University, China, where he is working on projects focused on genome-wide association studies of safflower germplasm and the identification of genetic markers in lentils. His previous research at Quaid-i-Azam University, Islamabad, included a master’s project on the molecular characterization of the TIN-1 gene in winter bread wheat, utilizing advanced techniques such as high-throughput genomic sequencing and RNA-seq. Mr. Ali has also worked as a research fellow in various plant physiology and genetics projects, with a particular focus on plant stress responses, including sodium chloride stress in rice. In addition to his research, he has held significant academic leadership roles, including Head of the Biology Department at Cadet Colleges in Khyber Pakhtunkhwa and Punjab, Pakistan, and as a Visiting Lecturer at Islamia College University, Peshawar. His combined research expertise and academic leadership have significantly contributed to advancing plant sciences in his field.

Research Interests:

Mr. Arif Ali’s research interests primarily focus on plant breeding, genetics, and stress physiology. His work is particularly centered around the molecular characterization of agronomic traits, including the identification and validation of genetic markers associated with key traits in crops such as safflower and lentils. He is also interested in understanding the genetic mechanisms underlying plant responses to environmental stresses, including nitrogen use efficiency, sodium chloride, and copper chloride stress. His research incorporates advanced genomic techniques such as genome-wide association studies (GWAS), RNA sequencing (RNA-seq), real-time quantitative PCR (RT-qPCR), and comparative genomics. Additionally, Mr. Ali is exploring the integration of bioinformatics tools for gene expression analysis and protein-protein interaction studies to further advance plant stress tolerance breeding under changing environmental conditions.

Awards and Honors:

Mr. Arif Ali has been recognized for his academic and research excellence through several awards and honors. He has contributed significantly to the field of plant sciences, particularly in the areas of plant breeding and molecular genetics. His work has been published in high-impact journals such as Functional Plant Biology and Heliyon, underscoring the value of his research in advancing agricultural science. Mr. Ali has also been acknowledged for his contributions to the study of stress tolerance in plants, with his research on safflower and lentils receiving attention in both local and international academic circles. His active participation in conferences and his ability to present cutting-edge research at prestigious events further highlight his recognition within the scientific community.

Skills:

Mr. Arif Ali possesses a diverse set of technical and soft skills that complement his research in plant sciences. He has hands-on experience with advanced software and tools, including Microsoft Office, Statistix, XLSTAT, R software, and various bioinformatics platforms for genomic analysis. His proficiency in using tools such as STRUCTURE, TASSEL with Mixed Linear Models, BLAST, and STRING allows him to analyze population structure, marker-trait associations, and perform protein-protein interaction analyses. Mr. Ali is skilled in molecular biology techniques, including high-throughput DNA sequencing, RNA-seq, real-time quantitative PCR (RT-qPCR), and controlled greenhouse experiments. Additionally, he has a strong command of English and Urdu, enabling effective communication and collaboration in diverse research settings. His ability to conduct detailed phenotypic and biochemical evaluations, along with his expertise in various plant stress treatments, further enhances his capacity for contributing to cutting-edge agricultural research.

Publication Top Noted:

Title: Assessment of comparative effects of sodium chloride stress on various growth parameters in different varieties of rice (Oryza sativa L.)

  • Authors: S. Wali, I. Ahmad, F. Tariq, A. Ali, S.I.U. Haq
  • Journal: Pure and Applied Biology
  • Volume: 6, Issue 2, Page: 707
  • Cited by: 2
  • Year: 2017

Title: Barley a nutritional powerhouse for gut health and chronic disease defense

  • Authors: A. Ali, Z. Ullah, R. Ullah, M. Kazi
  • Journal: Heliyon
  • Volume: 10, Issue 20
  • Cited by: 1
  • Year: 2024

Title: Omics-Driven Strategies for Developing Saline-Smart Lentils: A Comprehensive Review

  • Authors: Fawad Ali, Yiren Zhao, Arif Ali, Muhammad Waseem, Mian A. R.
  • Journal: International Journal of Molecular Sciences
  • Volume: 21, Issue 25
  • Year: 2024

Title: Genome-wide association studies identify genetic loci related to fatty acid and branched-chain amino acid metabolism and histone modifications under varying nitrogen

  • Authors: F. Ali, M.A.R. Arif, A. Ali, M.A. Nadeem, E. Aksoy, A. Bakhsh, S.U. Khan, C. Kurt
  • Journal: Functional Plant Biology
  • Volume: 51, Issue 5
  • Year: 2024

Title: Effect of Different Hosts on the Biology of Trybliographa Daci (Hymenoptera Braconidae) Under Lab Conditions

  • Authors: F.A. Soomro, N.K. Bugti, A. Ali, S.A.H. Shah, S.U. Baloch, S.K. Baloch, Z. Ullah

Conclusion:

Mr. Arif Ali’s research contributions, academic leadership, and technical expertise position him as an excellent candidate for the Research for Excellence in Innovation award, reflecting his commitment to advancing plant science and sustainable agriculture.

Vahid Jahangiri | Machin Learning | Best Researcher Award

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Assist. Prof. Dr. Vahid Jahangiri | Machin Learning | Best Researcher Award

Assistant Professor at University of Mohaghegh Ardabili, Iran

Assist. Prof. Dr. Vahid Jahangiri is an Assistant Professor at the University of Mohaghegh Ardabili, Iran, specializing in Civil (Earthquake) Engineering. He holds a Ph.D. in Earthquake Engineering from Tarbiat Modares University (2016), an M.Sc. from Sharif University of Technology (2009), and a B.A. in Civil Engineering from the University of Tabriz (2007). Dr. Jahangiri has extensive teaching experience in areas such as seismic design, risk assessment, structural dynamics, and earthquake engineering. Additionally, he worked as a Civil Engineer Consultant at Arte Tarrahan (2011-2014). His research focuses on seismic risk assessment, structural resilience, and earthquake-induced infrastructure damage, with key publications in prestigious journals such as the Bulletin of Earthquake Engineering and Structures. Dr. Jahangiri’s work has made significant contributions to the safety of infrastructure under seismic events, particularly in buried pipelines and structural collapse scenarios.

Profile:

Education:

Assist. Prof. Dr. Vahid Jahangiri has a strong academic foundation in civil and earthquake engineering. He completed his Ph.D. in Civil (Earthquake) Engineering at Tarbiat Modares University, Tehran, Iran, in 2016. Prior to this, he earned his M.Sc. in Civil (Earthquake) Engineering from Sharif University of Technology in 2009 and his B.A. in Civil Engineering from the University of Tabriz in 2007. His academic journey underscores his dedication to mastering seismic engineering, equipping him with advanced expertise to contribute significantly to the field.

Professional Experience:

Dr. Jahangiri’s career includes valuable consulting experience and a robust academic role. Between 2011 and 2014, he worked as a Civil Engineer Consultant at Arte Tarrahan in Tehran, where he applied engineering knowledge to practical projects. In 2018, he joined the Faculty of Engineering at the University of Mohaghegh Ardabili as an Assistant Professor. Here, he teaches various specialized courses to M.Sc. and Ph.D. students, including Performance-Based Seismic Design and Dynamics of Structures, and fundamental subjects like Mechanics of Materials to undergraduate students, blending theory with practical application.

Research Interests:

Assist. Prof. Dr. Vahid Jahangiri’s research interests primarily lie in the fields of earthquake engineering, seismic risk assessment, and structural resilience. His work focuses on evaluating and enhancing the seismic performance of critical infrastructure, including buried pipelines and bridges. Dr. Jahangiri is particularly interested in the development of performance-based seismic design methods, fragility analysis, and the dynamic behavior of structures under earthquake loading. He has conducted extensive research on the seismic response of buried steel pipelines and the impact of seismic wave propagation on gas pipeline networks. Additionally, his research extends to the assessment of progressive collapse in buildings, with a particular focus on fire-induced damage. His work aims to improve the safety and reliability of structures in seismically active regions, contributing to the development of more resilient infrastructure systems. Through his research, Dr. Jahangiri strives to bridge the gap between theoretical models and practical applications in earthquake engineering.

Skills:

Assist. Prof. Dr. Vahid Jahangiri possesses a diverse set of skills in earthquake engineering, structural dynamics, and seismic risk assessment. He is proficient in advanced seismic analysis techniques, including performance-based seismic design, fragility analysis, and the evaluation of structural responses to seismic events. Dr. Jahangiri has expertise in modeling the dynamic behavior of structures, particularly in the context of buried infrastructure such as pipelines and bridges, using both numerical and experimental methods. He is skilled in the application of various intensity measures to assess the seismic response of infrastructure systems. His experience also includes the development and application of engineering tools for evaluating the resilience of buildings under extreme events like earthquakes and fires. Additionally, Dr. Jahangiri is highly knowledgeable in soil-structure interaction and the dynamics of soil during seismic activity. His teaching and consulting roles have further honed his abilities in conveying complex engineering concepts and providing practical solutions to real-world challenges in earthquake engineering. These skills, combined with his strong research capabilities, make him a leading expert in his field.

Publication Top Noted:

  • Title: Intensity measures for the assessment of the seismic response of buried steel pipelines
    • Authors: H. Shakib, V. Jahangiri
    • Journal: Bulletin of Earthquake Engineering
    • Pages: 1265-1284
    • Cited by: 53
    • Year: 2016
  • Title: Seismic risk assessment of buried steel gas pipelines under seismic wave propagation based on fragility analysis
    • Authors: V. Jahangiri, H. Shakib
    • Journal: Bulletin of Earthquake Engineering
    • Pages: 1571-1605
    • Cited by: 50
    • Year: 2018
  • Title: Evaluation of Plasco Building fire-induced progressive collapse
    • Authors: H. Shakib, M. Zakersalehi, V. Jahangiri, R. Zamanian
    • Journal: Structures
    • Pages: 205-224
    • Cited by: 38
    • Year: 2020
  • Title: Intensity measures for the seismic response assessment of plain concrete arch bridges
    • Authors: V. Jahangiri, M. Yazdani, M.S. Marefat
    • Journal: Bulletin of Earthquake Engineering
    • Pages: 4225-4248
    • Cited by: 38
    • Year: 2018
  • Title: Seismic performance assessment of plain concrete arch bridges under near-field earthquakes using incremental dynamic analysis
    • Authors: M. Yazdani, V. Jahangiri, M.S. Marefat
    • Journal: Engineering Failure Analysis
    • Page: 104170
    • Cited by: 37
    • Year: 2019
  • Title: Seismic reliability and limit state risk evaluation of plain concrete arch bridges
    • Authors: V. Jahangiri, M. Yazdani
    • Journal: Structure and Infrastructure Engineering
    • Volume: 17, Issue 2, Pages: 170-190
    • Cited by: 32
    • Year: 2021
  • Title: Appropriate intensity measures for probabilistic seismic demand estimation of steel diagrid systems
    • Authors: M. Heshmati, V. Jahangiri
    • Journal: Engineering Structures
    • Page: 113260
    • Cited by: 14
    • Year: 2021
  • Title: Intensity measure-based probabilistic seismic evaluation and vulnerability assessment of ageing bridges
    • Authors: M. Yazdani, V. Jahangiri
    • Journal: Earthquakes and Structures
    • Volume: 19, Issue 5, Pages: 379-393
    • Cited by: 13
    • Year: 2020

Conclusion:

Dr. Jahangiri’s extensive research, combined with his teaching and practical experience, makes him an outstanding choice for the Best Researcher Award, underscoring his commitment to advancing seismic safety and structural engineering.

Jordan Junior Kamese | Precision Healthcare | Best Researcher Award

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Mr. Jordan Junior Kamese | Precision Healthcare | Best Researcher Award

Research Assistant at Inje University, South Korea

Mr. Jordan Junior Kamese is a dynamic Graduate Research Assistant at Smart Lab, Inje University, South Korea, where he is currently pursuing a Master’s in Artificial Intelligence. Renowned for his expertise in machine learning and interdisciplinary collaboration, Mr. Kamese has contributed to influential publications and delivered presentations at international conferences. His research, which includes projects like cognitive impairment analysis for women’s health and computer vision for missile detection, reflects his technical prowess and innovative approach to AI applications. Recognized for his academic excellence, he received the KIICE Best Paper Award in 2023 and has been nominated for the Best Researcher Award in 2024.

Profile:

Education:

Mr. Jordan Junior Kamese is currently pursuing a Master of Science degree in Artificial Intelligence at Inje University in Gimhae-si, South Korea, with an anticipated graduation in October 2025. His academic journey in AI has been marked by exceptional performance, maintaining a current grade of 104%. His research focuses on advancing healthcare through artificial intelligence, with a thesis centered on analyzing cognitive impairment in women’s health using deep learning. Mr. Kamese’s commitment to academic excellence is further reflected by his receipt of the KIICE Best Paper Award in the second semester of 2023 and his nomination for the Best Researcher Award in the fourth semester of 2024.

Professional Experience:

Mr. Jordan Junior Kamese has established a strong foundation in research and academic contributions through his role as a Graduate Research Assistant at Smart Lab, Inje University. His responsibilities include maintaining accurate data records, performing thorough documentation, and assisting in manuscript preparation, resulting in the publication of several influential articles in peer-reviewed journals. Mr. Kamese has successfully planned, modified, and executed complex research techniques and procedures, showcasing his technical skills and adaptability. His active participation in conferences and workshops, where he has presented key research findings, reflects his dedication to professional growth and collaboration within the academic community. Additionally, he has conducted extensive background research, enhancing the quality of his projects by conducting comprehensive literature reviews and synthesizing complex findings.

Research Interests:

Mr. Jordan Junior Kamese’s research interests span a diverse range of cutting-edge fields within artificial intelligence and technology. He is particularly focused on machine learning, deep learning, and data analysis, with a strong emphasis on experimental and study design methodologies. His expertise extends to clinical research, where he explores applications of AI to health, as demonstrated in his thesis on cognitive impairment in women’s health. Mr. Kamese also has a keen interest in computer vision and explainable AI, with recent projects that include missile detection models and Alzheimer’s multiclassification. Additionally, he is enthusiastic about future technologies, such as quantum computing, the Internet of Things, neuroscience, and the metaverse, exploring how these domains intersect with AI for innovative solutions.

Awards and Honors:

In recognition of his research excellence, Mr. Kamese was awarded the KIICE Best Paper Award in the second semester of 2023. His nomination for the Best Researcher Award in the fourth semester of 2024 further highlights his dedication and contributions. His thesis on “Analyzing Cognitive Impairment for Women’s Health through Deep Learning” and his innovative work on a missile detection system utilizing YOLOv11 computer vision have garnered significant academic and industry attention.

Skills:

Mr. Jordan Junior Kamese possesses a broad set of skills that enhance his contributions to research and technology. Proficient in data analysis, academic research, and experimental design, he demonstrates strong capabilities in structuring and executing research projects from inception to publication. His expertise in machine learning and deep learning is complemented by his technical command of software such as Python, C, and C++, and specialized tools like DSI Studio for data visualization. In the realm of machine learning, Mr. Kamese is adept in model selection, classification, and parameter optimization, consistently achieving high accuracy in complex tasks. His academic skills, including curriculum implementation, academic writing, and scientific paper preparation, contribute to his effective communication and dissemination of research findings. Mr. Kamese’s linguistic proficiency in English further facilitates his work in international, collaborative research environments.

Publication Top Noted:

Title: Alzheimer’s Multiclassification Using Explainable AI Techniques

  • Journal: Applied Sciences
  • Publication Date: September 2024
  • DOI: 10.3390/app14188287
  • Contributors: Jordan Junior Kamese, Kouayep Sonia Carole, Theodore Armand Tagne Poupi, Hee-Cheol Kim, The Alzheimer’s Disease Neuroimaging Initiative

Conclusion:

Mr. Kamese’s contributions in research, combined with his technical expertise, academic achievements, and diverse interests, make him a deserving candidate for the Best Researcher Award. His dedication to AI and healthcare, coupled with his record of impactful research and community engagement, set him apart as a promising researcher with a bright future.

Naresh Kumar Thapa K | Digital Signatures | Best Researcher Award

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Dr. Naresh Kumar Thapa K | Digital Signatures | Best Researcher Award

Assistant Professor at Sathyabama Institute of Science and Technology, India

Dr. Naresh Kumar Thapa K. is an Assistant Professor at R.M.K. Engineering College, specializing in communication theory, wireless communication, multimedia compression, and communication networks. With over a decade of academic experience, Dr. Thapa has made significant contributions to research in AI, machine learning, cybersecurity, and 5G/6G wireless networks. He has published numerous papers in reputed journals and conferences and has applied for multiple patents related to emerging technologies. Dr. Thapa has played an instrumental role in various academic processes, including NBA, ABET, and NAAC accreditation, and has been a key contributor to the development of foreign language programs and international collaborations. His current research includes anomaly detection in network traffic and security architectures for next-generation networks. Additionally, Dr. Thapa has guided students in national-level competitions, such as the Smart India Hackathon, and is dedicated to furthering research in cutting-edge technological advancements.

Profile:

Education:

Dr. Naresh Kumar Thapa K. holds a strong educational background in communication systems, cybersecurity, and related fields. He completed his undergraduate studies in Electronics and Communication Engineering, followed by a Master’s degree in the same discipline. Dr. Thapa further advanced his academic qualifications by pursuing a Ph.D., with a focus on communication technologies and cybersecurity, from a reputed institution. Throughout his academic journey, Dr. Thapa has honed his skills in programming languages such as C, C++, Python, Matlab, and NS2, as well as in operating systems like Windows and Linux. His academic expertise has greatly contributed to his ability to lead and innovate in the areas of AI, machine learning, and wireless communication. His education has laid a solid foundation for his current role as an Assistant Professor at R.M.K. Engineering College, where he applies his extensive knowledge in teaching and research.

Professional Experience:

Dr. Naresh Kumar Thapa K. has extensive professional experience in academia, currently serving as an Assistant Professor at R.M.K. Engineering College since June 2023. He has taught a wide range of subjects, including Intelligent Robotics and Drones, 5G and 6G Wireless Networks, and AI Lab and Advanced Robotics Lab. Dr. Thapa has been involved in significant research projects, including a proposal titled “Study of Anomaly Detection using Network Traffic Generated by Internet-Enabled Devices for Cyber Security,” which was selected for funding under the Telecom Technology Development Fund. Previously, from 2018 to 2023, he was an Assistant Professor at R.M.K. Engineering College, where he played a pivotal role in handling subjects such as Analog and Digital Communication, Wireless Communication, and Multimedia Compression and Communication. He applied for two patents and published eight papers during this time. Dr. Thapa also contributed significantly to the department by assisting with NBA and NAAC accreditation processes and coordinating the Center for Foreign Language program, establishing partnerships with Japanese companies. Prior to his tenure at R.M.K. Engineering College, he worked at Velammal Engineering College from 2013 to 2018, where he started his academic career, handling subjects such as Digital Electronics and Wireless Communication, and coordinating various departmental events.

Research Interests:

Dr. Naresh Kumar Thapa K.’s research interests lie at the intersection of Artificial Intelligence (AI), Machine Learning (ML), and Cybersecurity. He is particularly focused on leveraging AI and ML techniques to enhance network security, with a specific interest in anomaly detection and intrusion detection systems for wireless and IoT networks. His work also explores advanced topics in 5G and 6G wireless networks, emphasizing security frameworks for next-generation communication systems. Additionally, Dr. Thapa has shown keen interest in multimedia compression, wireless communication, and communication networks, and has contributed to the development of innovative systems and solutions in these areas. His ongoing research aims to bridge the gaps in AI-driven security protocols and explore the use of emerging technologies like blockchain for securing wireless sensor networks.

Awards and Honors:

Dr. Naresh Kumar Thapa K. has received several notable awards and honors in recognition of his contributions to the fields of communication, AI, and cybersecurity. Among his achievements, he was awarded Best Paper at the International IEEE-ICCIC Conference in 2014 for his work on differential amplifier-based speed monitoring circuits for airport and production industries. His research on blockchain-based identity authentication and traffic sign identification systems using AI has garnered widespread recognition, with papers accepted at prestigious international conferences such as IEEE-ICECAA 2022 and IEEE-ICERCS 2023. Furthermore, Dr. Thapa’s work on cybersecurity and anomaly detection has earned him accolades in the academic community, enhancing his reputation as a leading researcher in the field.

Skills:

Dr. Naresh Kumar Thapa K. possesses a diverse and comprehensive skill set that spans across various areas of technology and engineering. He is proficient in operating systems such as Windows and Linux, and has expertise in programming languages including C, C++, Python, Matlab, and NS2. His technical skills extend to areas of artificial intelligence (AI) and machine learning (ML), where he applies advanced algorithms for data analysis and cybersecurity solutions. Additionally, Dr. Thapa is adept in wireless communication, multimedia compression, and communication networks, with a focus on 5G and 6G technologies. His strong analytical capabilities and hands-on experience in cybersecurity, particularly in anomaly detection and traffic analysis, further strengthen his technical proficiency.

Publication Top Noted:

  • A novel enhanced security architecture for sixth generation (6G) cellular networks using authentication and acknowledgement (AA) approach
    • Authors: V, S.P., Albert, A.J., Thapa, K.N.K., Krishnaprasanna, R.
    • Journal: Results in Engineering, 2024, Vol. 21, Article 101669
    • Citations: 2
  • Implementation of Transmission Line Fault Detection System using Long Range Wireless Sensor Networks
    • Authors: Raja, P.D.A., Thapa, K.N.K., Harsha, K.S.S., Krishna, K.S., Sivakumar, A.
    • Journal: International Journal on Recent and Innovation Trends in Computing and Communication, 2023, 11(5), pp. 77–84
    • Citations: 1
  • Design and Development of Artificial Intelligence based Real-Time Traffic Sign Identification Scheme using Novel Learning Strategy
    • Authors: Tamilselvi, M., Iyswariya, A., Thapa, K.N.K., Vinithra Banu, T., Pandi, V.S.
    • Conference: 1st International Conference on Emerging Research in Computational Science (ICERCS 2023)
    • Citations: 0
  • A Novel Framework in Scheduling Packets for Energy-Efficient Bandwidth Allocation in Wireless Networks
    • Authors: Sivajothi, E., Jayaudhaya, J., Santhiya, S., Kamatchi, S., Ganapathy, N.B.S.
    • Conference: 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC 2023), pp. 1311–1316
    • Citations: 0
  • A Comprehensive Analysis for Implementing IoT on LTE Systems
    • Authors: Kumar Thapa, K.N., Malini, A.H., Kalaimani, A., Srinivasan, S.
    • Conference: International Conference on Applied Artificial Intelligence and Computing (ICAAIC 2022), pp. 502–507
    • Citations: 4
  • Malicious Traffic classification Using Long Short-Term Memory (LSTM) Model
    • Authors: Thapa, K.N.K., Duraipandian, N.
    • Journal: Wireless Personal Communications, 2021, 119(3), pp. 2707–2724
    • Citations: 22
  • Differential Amplifier Based Speed Monitoring Circuit for Airport and Production Industry
    • Authors: Naresh Kumar Thapa, K., Kalaivani, S., Vanaja, S., Joselin Jeya Sheela, J., Deepika, Y.
    • Conference: 5th International Conference on I-SMAC (IoT in Social, Mobile, Analytics, and Cloud), 2021, pp. 1761–1764
    • Citations: 1
  • Post disaster damage estimation using integrated GPS sensor network & GIS
    • Authors: John Samuel Raj, K., Naresh Kumar Thapa, K., Balakrishnan, R.
    • Conference: IEEE International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET 2016), pp. 1234–1238
    • Citations: 3
  • Digital signature using stationary wavelet transform based watermarking for robots
    • Authors: Thapa, K.N.K., Kumari, P., Kantham, L.
    • Conference: IEEE International Conference on Computational Intelligence and Computing Research (IEEE ICCIC 2014), 2015, pp. 307–312
    • Citations: 0

Conclusion:

Dr. Naresh Kumar Thapa K. is an exemplary academic and researcher with a proven track record in teaching, research, and innovation. His contributions to the fields of communication, AI, cybersecurity, and IoT have had a significant impact on both his institution and the broader academic and research communities. His research outputs, including publications in high-impact journals, patents, and successful grant proposals, demonstrate his ability to address contemporary technological challenges. Therefore, Dr. Thapa is a highly deserving candidate for the Best Researcher Award, owing to his impressive research achievements, leadership in academia, and dedication to student success.

Sourabh Debnath | Coverless Steganography | Best Researcher Award

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Mr. Sourabh Debnath | Coverless Steganography | Best Researcher Award

Researcher at National Institute of Technology Rourkela, India

Mr. Sourabh Debnath is an accomplished researcher and Ph.D. candidate in Computer Science & Engineering at the National Institute of Technology Rourkela, with a focus on improving capacity, robustness, and security in networked systems. He holds an M.Tech from Veer Surendra Sai University of Technology, Sambalpur, and a B.Tech from Government College of Engineering Kalahandi, both in Computer Science & Engineering. Currently a Senior Research Fellow (SRF) at NIT Rourkela’s Cybernetics and Information Security Laboratory, Mr. Debnath specializes in coverless steganography, image processing, and machine learning. His work has led to several publications in top journals and conferences, particularly in the areas of secure data transmission and video steganography. Additionally, he contributes to the academic community as a reviewer for Elsevier’s Journal of Information Security and Applications and has presented his work at various international conferences.

Profile:

Education:

Mr. Sourabh Debnath has a strong academic background in Computer Science and Engineering. He is currently pursuing a Doctor of Philosophy (Ph.D.) in Computer Science & Engineering at the National Institute of Technology, Rourkela, where he has achieved an impressive CGPA of 8.89. Prior to this, he completed his Master of Technology (M.Tech) in Computer Science & Engineering from Veer Surendra Sai University of Technology (VSSUT), Burla, Sambalpur, Odisha, with a CGPA of 8.27. Mr. Debnath began his higher education journey with a Bachelor of Technology (B.Tech) in Computer Science & Engineering from Government College of Engineering Kalahandi (GCEK), Bhawanipatna, Odisha, where he graduated with a CGPA of 8.13. His foundational studies include Intermediate Science at Govt. Junior Science College, Malkangiri, with a 68.83% score, and Matriculation from I.M.S.T. English Medium and High School, Malkangiri, where he achieved a CGPA of 8.00. Mr. Debnath’s consistent academic performance highlights his dedication and capability in his field.

Professional Experience:

Mr. Sourabh Debnath has accumulated valuable research experience in cybernetics and information security, currently serving as a Senior Research Fellow (SRF) at the Cybernetics and Information Security Laboratory, National Institute of Technology Rourkela, since June 2022. In this role, he focuses on advanced techniques for secret data sharing and network security. Prior to this, he served as a Junior Research Fellow (JRF) in the same laboratory from January 2020 to May 2022. His research work emphasizes enhancing capacity, robustness, and security in data transmission frameworks. Additionally, Mr. Debnath has contributed to the scholarly community as a reviewer for the Journal of Information Security and Applications (Elsevier) and as a reviewer for the 3rd International Conference on Artificial Intelligence and Signal Processing (AISP) organized by VIT-AP and IEEE Hyderabad

Research Interests:

Mr. Sourabh Debnath’s research interests center on advancing techniques for secure data transmission, with a particular focus on coverless steganography. His work seeks to enhance data-sharing methodologies by improving capacity, robustness, and security in steganographic frameworks. Additionally, he explores applications in image processing, machine learning, and deep learning to refine data-hiding techniques and optimize efficiency within secure systems. His technical skills include proficiency in programming languages such as C/C++, Oracle, Python, and MATLAB, as well as frameworks like Keras and TensorFlow, which he applies in innovative research areas like network security and efficiency analysis.

Awards and Honors:

Mr. Sourabh Debnath has been recognized for his contributions to academia and research through various honors. He serves as a reviewer for the Journal of Information Security and Applications by Elsevier, where he applies his expertise in data security and steganography. Additionally, he was selected as a reviewer for the prestigious 3rd International Conference on Artificial Intelligence and Signal Processing (AISP) organized by VIT-AP, India, and IEEE Hyderabad Section in 2023. These roles highlight his dedication to advancing knowledge in the fields of artificial intelligence, data security, and cybernetics.

Skills:

Mr. Sourabh Debnath possesses a strong technical skill set and diverse expertise that complement his research pursuits. His programming skills include proficiency in C/C++, Oracle, Python, and MATLAB, which he utilizes to develop and implement complex algorithms in his work. He is well-versed in machine learning frameworks such as Keras and TensorFlow, which he applies in research areas like coverless steganography and data security. Additionally, Mr. Debnath is adept in document creation tools like Microsoft Office Suite and LaTeX, and he has a solid foundation in coursework relevant to his field, including Steganography, Operating Systems, Machine Learning, and Database Management Systems. His soft skills, such as problem-solving, self-learning, presentation, and adaptability, further enhance his capabilities as a researcher and collaborator.

Publication Top Noted:

Energy management in wireless sensor network through EB-LEACH

  • Authors: H. Mohapatra, S. Debnath, A.K. Rath
  • Journal: International Journal of Research and Analytical Reviews (IJRAR), 2019
  • Citations: 45

An efficient energy saving scheme through sorting technique for wireless sensor network

  • Authors: H. Mohapatra, S. Debnath, A.K. Rath, P.B. Landge, S. Gayen, R. Kumar
  • Journal: International Journal, 2020
  • Citations: 23

Secret data sharing through coverless video steganography based on bit plane segmentation

  • Authors: S. Debnath, R.K. Mohapatra, R. Dash
  • Journal: Journal of Information Security and Applications, 2023
  • Citations: 11

Coverless image steganography based on DWT approximation and pixel intensity averaging

  • Authors: S. Biswas, S. Debnath, R.K. Mohapatra
  • Conference: 7th International Conference on Trends in Electronics and Informatics, 2023
  • Citations: 10

Fuzzy petri nets-based intelligent routing protocol for ad hoc network

  • Authors: A. Samantra, A. Panda, S.K. Das, S. Debnath
  • Book Chapter: Design Frameworks for Wireless Networks, 2020
  • Citations: 9

A study on secret data sharing through coverless steganography

  • Authors: S. Debnath, R.K. Mohapatra
  • Conference: 2nd International Conference on Artificial Intelligence and Signal Processing, 2022
  • Citations: 8

Energy management in wireless sensor network through EB-LEACH (No. 1192)

  • Authors: H. Mohapatra, S. Debnath, A.K. Rath
  • Platform: Easy Chair, 2019
  • Citations: 6

DCT based robust coverless information hiding scheme with high capacity

  • Authors: T. Kulkarni, S. Debnath, J. Kumar, R.K. Mohapatra
  • Conference: 7th International Conference on Trends in Electronics and Informatics, 2023
  • Citations: 5

Conclusion:

Mr. Sourabh Debnath’s extensive academic qualifications, diverse and impactful research publications, robust technical skills, and experience in academia and peer-review make him a worthy contender for the Best Researcher Award. His work in coverless steganography, video processing, and data security positions him as a leading researcher with the potential to make continued significant contributions to his field.

Moses Ashawa | Cybersecurity | Best Researcher Award

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Dr. Moses Ashawa | Cybersecurity | Best Researcher Award

Lecturer at Glasgow Caledonian University, United Kingdom

Dr. Moses Ashawa is an accomplished academic and researcher specializing in Cyber Defence and Security. He earned his Ph.D. from Cranfield University in the UK, where he focused on advanced cybersecurity topics. He also holds an MSc in Computer Security and Digital Forensics with distinction from the University of Bedfordshire, alongside a Post Graduate Diploma in Education and a BSc in Computer Science from Benue State University, Nigeria. Dr. Ashawa has extensive teaching experience, having developed innovative course modules and provided individualized support to students. His research interests encompass penetration testing, malware analysis, digital forensics, and the integration of artificial intelligence in cybersecurity. He has secured significant research grants and has published numerous peer-reviewed articles, reflecting his commitment to advancing knowledge in his field. As a Fellow of the Higher Education Academy, Dr. Ashawa is dedicated to fostering academic excellence and preparing students for careers in technology and cybersecurity.

Profile:

Education:

Dr. Moses Ashawa holds a Ph.D. in Cyber Defence and Security from Cranfield University, United Kingdom, which he completed in 2022. He earned his Master of Science in Computer Security and Digital Forensics with distinction from the University of Bedfordshire in 2017. Dr. Ashawa also holds a Post Graduate Diploma in Education (PGDE) from the National Open University of Nigeria, obtained in 2015, and a Bachelor of Science with Honours in Computer Science from Benue State University, Makurdi, Nigeria, completed in 2013. Additionally, he completed his secondary education with the West African Education Certificate (WAEC) at Calvin Foundation College, Nigeria, in 2006. This diverse educational background provides him with a strong foundation in both technical and pedagogical aspects of computer science and cybersecurity.

Professional Experience:

Dr. Moses Ashawa has a diverse professional background that spans teaching, research, and curriculum development. Currently, he plays a pivotal role in shaping the academic experience at his institution by developing lecture notes and course modules that align with university curricula and setting clear learning objectives. His commitment to student success is evident in his approach to assessment, where he marks student work and provides impactful feedback to enhance their understanding and confidence. Dr. Ashawa actively collaborates with unit heads and course coordinators to innovate curriculum developments, ensuring that academic standards are met and that emerging technologies are integrated into the learning experience. Additionally, he contributes to research projects in Cyber Security and Digital Forensics, collaborating with industry partners such as Cisco to strengthen student internships and employability prospects. His previous experience includes serving as a Maths and ICT Supply Teacher in the UK, where he prepared lesson plans and established positive relationships with students, parents, and colleagues. As a Graduate Assistant at the American University of Nigeria, he delivered undergraduate lectures on topics such as artificial intelligence and ethical hacking, while also supporting students in their practical sessions and projects. Dr. Ashawa’s multifaceted experience highlights his dedication to education and research in the field of cybersecurity.

Research Interests:

Dr. Moses Ashawa’s research interests lie at the intersection of cybersecurity and advanced technology. He specializes in penetration testing and ethical hacking, focusing on developing methods to assess and enhance the security of systems against potential threats. His work in malware analysis involves investigating malicious software to understand its behavior and develop effective detection techniques. Additionally, Dr. Ashawa is passionate about digital forensics, exploring ways to recover and analyze data from digital devices to support investigations and legal proceedings. He is also keenly interested in the applications of artificial intelligence and machine learning in cybersecurity, particularly how these technologies can be leveraged to improve threat detection and response strategies. Furthermore, his research extends to the Internet of Things (IoT), where he examines the unique security challenges posed by interconnected devices and seeks innovative solutions to safeguard them. Through his research, Dr. Ashawa aims to contribute significantly to the advancement of cybersecurity practices and knowledge.

Skills:

Dr. Moses Ashawa possesses a robust skill set that spans various domains within cybersecurity and education. His technical expertise includes penetration testing, ethical hacking, and malware analysis, allowing him to identify vulnerabilities in systems and develop effective security measures. He is proficient in digital forensics, utilizing advanced methodologies to recover and analyze data from electronic devices for investigative purposes. Dr. Ashawa has a strong foundation in artificial intelligence and machine learning, which he applies to enhance cybersecurity measures and improve threat detection capabilities. In addition to his technical skills, he excels in curriculum development and instructional design, having created innovative course materials that engage students and facilitate effective learning. His ability to provide individualized support reflects his strong interpersonal skills and commitment to student success. Furthermore, Dr. Ashawa is adept at collaborating with industry partners, demonstrating his capacity to bridge the gap between academia and the professional world. His diverse skill set not only enhances his research capabilities but also enriches the educational experiences of his students.

Publication Top Noted:

“Enhancing credit card fraud detection: an ensemble machine learning approach”

  • Authors: AR Khalid, N Owoh, O Uthmani, M Ashawa, J Osamor, J Adejoh
  • Journal: Big Data and Cognitive Computing, 2024
  • Citations: 40

“RETRACTED ARTICLE: Improving cloud efficiency through optimized resource allocation technique for load balancing using LSTM machine learning algorithm”

  • Authors: M Ashawa, O Douglas, J Osamor, R Jackie
  • Journal: Journal of Cloud Computing, 2022
  • Citations: 39

“Analysis of android malware detection techniques: a systematic review”

  • Authors: MA Ashawa, S Morris
  • Publisher: Society of Digital Information and Wireless Communications, 2019
  • Citations: 35

“Effective methods to detect metamorphic malware: a systematic review”

  • Authors: M Irshad, HM Al-Khateeb, A Mansour, M Ashawa, M Hamisu
  • Journal: International Journal of Electronic Security and Digital Forensics, 2018
  • Citations: 23

“Analysis of mobile malware: a systematic review of evolution and infection strategies”

  • Authors: M Ashawa, S Morris
  • Publisher: جامعة نايف العربية للعلوم الأمنية‎, 2021
  • Citations: 20

“Forensic data extraction and analysis of left artifacts on emulated android phones: a case study of instant messaging applications”

  • Authors: M Ashawa, I Ogwuche
  • Journal: Seizure, 2017
  • Citations: 11

Conclusion:

Dr. Moses Ashawa exemplifies the qualities sought in the Research for Best Researcher Award. His robust academic credentials, extensive teaching experience, significant research contributions, and active engagement in professional development all position him as a leading figure in the field of Cyber Security and Digital Forensics. His ability to bridge the gap between academia and industry, alongside his dedication to fostering student success, makes him a commendable candidate for this prestigious award.