Vahid Jahangiri | Machin Learning | Best Researcher Award

Posted on by ScienceFather

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

Posted on by ScienceFather

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

Posted on by ScienceFather

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

Posted on by ScienceFather

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

Posted on by ScienceFather

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.

Stefano Cagnin | Life Science | Best Researcher Award

Posted on by ScienceFather

Prof. Stefano Cagnin | Life Science | Best Researcher Award

Professor at University of Padova, Italy

Prof. Stefano Cagnin is a distinguished researcher and educator in the field of molecular biology and genetics, currently affiliated with the University of Padova. With a robust academic background, including a Ph.D. in Molecular Biology, he specializes in transcriptional analysis across various model organisms such as Homo sapiens, Mus musculus, Drosophila melanogaster, and Sus scrofa. His research focuses on dissecting transcriptional regulation in different pathologies, utilizing innovative bioinformatics and genomics techniques. Prof. Cagnin serves as the Editor-in-Chief of “Biochemical Genetics” and holds editorial positions in several prominent scientific journals. He is actively involved in multiple scientific societies, including the Association for Gene and Cell Therapy and the RNA Society. A prolific contributor to the scientific literature, he has authored numerous publications and has presented his work at international conferences. Through his dedication to advancing knowledge in his field, Prof. Cagnin continues to make significant contributions to the understanding of molecular mechanisms underlying various diseases.

Profile:

Education:

Prof. Stefano Cagnin obtained his educational qualifications in the field of biological sciences, laying a strong foundation for his research career. He earned his Bachelor’s degree in Biological Sciences from the University of Padova, where he developed a keen interest in genetics and molecular biology. Following this, he pursued a Master’s degree in Molecular Biology at the same institution, focusing on the complexities of gene expression and regulation. His academic journey culminated in a Ph.D. in Molecular Biology from the University of Padova, where he conducted extensive research on transcriptional regulation in various model organisms. This comprehensive educational background has equipped him with the necessary skills and knowledge to excel in his research endeavors and contribute significantly to the scientific community.

Professional Experience:

Prof. Stefano Cagnin boasts an extensive professional experience in molecular biology and genetics, with a particular focus on transcriptional analysis and regulatory mechanisms in various model organisms. He is currently a faculty member at the University of Padova, where he has made significant contributions to both research and education. In addition to his teaching responsibilities, he has taken on leadership roles in academic publishing, serving as the Editor-in-Chief of “Biochemical Genetics” and as an Associate Editor for “Molecular Diagnostics and Therapeutics.” His editorial contributions extend to being a member of the editorial boards of several esteemed journals, including “Academia Biology” and “Molecular Therapy – Nucleic Acids.” Prof. Cagnin is also a sought-after reviewer for numerous scientific journals, reflecting his expertise and respect within the academic community. His collaborative work includes leadership in special issues on heart failure and multicellular organism analysis, showcasing his commitment to advancing scientific understanding and innovation in his field.

Research Interests:

Prof. Stefano Cagnin’s research interests are centered on transcriptional analysis and the regulatory mechanisms underlying gene expression in various biological contexts. He employs innovative bioinformatic approaches and advanced molecular biology techniques to dissect transcriptional regulation in Homo sapiens as well as in model organisms such as Mus musculus, Drosophila melanogaster, and Sus scrofa. His work focuses on understanding the implications of these regulatory processes in the context of different pathologies, including muscle atrophy and cancer metastasis. Prof. Cagnin is particularly interested in the role of non-coding RNAs and microRNAs in maintaining cellular functions and interactions, which has significant implications for therapeutic strategies in muscle diseases and cancer. Through his interdisciplinary approach, he aims to advance knowledge in genomics and molecular genetics, contributing to the development of novel therapeutic interventions.

Skills:

Prof. Stefano Cagnin possesses a diverse skill set that encompasses advanced methodologies in molecular biology, bioinformatics, and genomics. He is adept at employing various techniques for transcriptional analysis, allowing for in-depth exploration of gene regulation across different biological systems. His expertise includes the design and implementation of innovative experimental approaches, including engineering biology techniques that integrate molecular and cellular methods. Prof. Cagnin has a strong background in data analysis and interpretation, utilizing computational tools to extract meaningful insights from complex biological datasets. Additionally, he is skilled in scientific communication, having led editorial roles in reputable journals and participated in numerous national and international conferences, where he effectively presents his research findings and collaborates with peers in the field.

Conclusion:

Prof. Stefano Cagnin exemplifies the qualities of a strong candidate for the Best Researcher Award through his extensive editorial contributions, active membership in scientific societies, innovative research in transcriptional analysis, impactful publications, and participation in international conferences. His dedication to advancing scientific knowledge and fostering collaboration in the research community positions him as a deserving nominee for this prestigious award.

Publication Top Noted:

  • SPP1 genotype is a determinant of disease severity in Duchenne muscular dystrophy
    • Authors: E. Pegoraro, E.P. Hoffman, L. Piva, B.F. Gavassini, S. Cagnin, M. Ermani, et al.
    • Journal: Neurology
    • Volume: 76
    • Issue: 3
    • Pages: 219-226
    • Year: 2011
    • Citations: 251
  • The mitochondrial calcium uniporter controls skeletal muscle trophism in vivo
    • Authors: C. Mammucari, G. Gherardi, I. Zamparo, A. Raffaello, S. Boncompagni, et al.
    • Journal: Cell Reports
    • Volume: 10
    • Issue: 8
    • Pages: 1269-1279
    • Year: 2015
    • Citations: 201
  • Overview of electrochemical DNA biosensors: new approaches to detect the expression of life
    • Authors: S. Cagnin, M. Caraballo, C. Guiducci, P. Martini, M. Ross, M. SantaAna, et al.
    • Journal: Sensors
    • Volume: 9
    • Issue: 4
    • Pages: 3122-3148
    • Year: 2009
    • Citations: 179
  • Involvement of microRNAs in the regulation of muscle wasting during catabolic conditions
    • Authors: R.J. Soares, S. Cagnin, F. Chemello, M. Silvestrin, A. Musaro, C. De Pitta, et al.
    • Journal: Journal of Biological Chemistry
    • Volume: 289
    • Issue: 32
    • Pages: 21909-21925
    • Year: 2014
    • Citations: 166
  • Parallel protein and transcript profiles of FSHD patient muscles correlate to the D4Z4 arrangement and reveal a common impairment of slow to fast fiber differentiation
    • Authors: B. Celegato, D. Capitanio, M. Pescatori, C. Romualdi, B. Pacchioni, et al.
    • Journal: Proteomics
    • Volume: 6
    • Issue: 19
    • Pages: 5303-5321
    • Year: 2006
    • Citations: 141
  • A fully electronic sensor for the measurement of cDNA hybridization kinetics
    • Authors: L. Bandiera, G. Cellere, S. Cagnin, A. De Toni, E. Zanoni, G. Lanfranchi, et al.
    • Journal: Biosensors and Bioelectronics
    • Volume: 22
    • Issues: 9-10
    • Pages: 2108-2114
    • Year: 2007
    • Citations: 140
  • Reconstruction and functional analysis of altered molecular pathways in human atherosclerotic arteries
    • Authors: S. Cagnin, M. Biscuola, C. Patuzzo, E. Trabetti, A. Pasquali, P. Laveder, et al.
    • Journal: BMC Genomics
    • Volume: 10
    • Pages: 1-15
    • Year: 2009
    • Citations: 118
  • Decellularized allogeneic heart valves demonstrate self-regeneration potential after a long-term preclinical evaluation
    • Authors: L. Iop, A. Bonetti, F. Naso, S. Rizzo, S. Cagnin, R. Bianco, C.D. Lin, P. Martini, et al.
    • Journal: PloS One
    • Volume: 9
    • Issue: 6
    • Article ID: e99593
    • Year: 2014
    • Citations: 99
  • Meta-analysis of expression signatures of muscle atrophy: gene interaction networks in early and late stages
    • Authors: E. Calura, S. Cagnin, A. Raffaello, P. Laveder, G. Lanfranchi, C. Romualdi
    • Journal: BMC Genomics
    • Volume: 9
    • Pages: 1-20
    • Year: 2008
    • Citations: 82
  • A single cell but many different transcripts: a journey into the world of long non-coding RNAs
    • Authors: E. Alessio, R.S. Bonadio, L. Buson, F. Chemello, S. Cagnin
    • Journal: International Journal of Molecular Sciences
    • Volume: 21
    • Issue: 1
    • Article ID: 302
    • Year: 2020
    • Citations: 68

Yonghong Wang | Access Control | Best Researcher Award

Posted on by ScienceFather

Dr. Yonghong Wang | Access Control | Best Researcher Award

Lecturer at Xinzhou Normal University, China

Dr. Yonghong Wang is a Lecturer in Computer Science at Xinzhou Normal University, where he has taught since 2007. He holds a B.S. in Computer Science and Technology from Xinzhou Normal University, an M.S. in Civil and Commercial Law from Shanxi University of Finance and Economics, and an M.S. in Software Engineering from North University of China. Currently pursuing a Ph.D. in Information Systems at INTI International University, Dr. Wang specializes in computer vision, network security, and the Internet of Things. He has published extensively in SCI and Scopus-indexed journals and is actively engaged in both academic and industry research projects.

Profile:

Education:

Dr. Yonghong Wang holds a Bachelor of Science degree in Computer Science and Technology from Xinzhou Normal University, awarded in 2007. He pursued further studies and earned a Master of Science in Civil and Commercial Law from Shanxi University of Finance and Economics in 2015. Additionally, Dr. Wang completed a second Master’s degree in Software Engineering at North University of China in 2016. Currently, he is pursuing a Ph.D. in Information Systems at INTI International University, a program he began in 2020. His educational background is multidisciplinary, integrating expertise in computer science, law, and software engineering.

Professional Experience:

Dr. Yonghong Wang has extensive professional experience as a Lecturer in Computer Science at Xinzhou Normal University, a position he has held since 2007. In this role, he has been responsible for teaching various computer science courses, mentoring students, and contributing to curriculum development. Over the years, he has actively participated in research projects, leading four completed projects and currently overseeing two ongoing projects. Dr. Wang has also engaged in consultancy and industry projects, collaborating with various organizations to apply his expertise in computer vision, network security, and the Internet of Things. His involvement in both academia and industry showcases his commitment to bridging theoretical knowledge with practical applications.

Research Interests:

Dr. Yonghong Wang’s research interests encompass a diverse range of fields, primarily focusing on computer vision, network security, and the Internet of Things (IoT). His work in computer vision explores innovative methods for image processing and analysis, aiming to enhance machine perception capabilities. In the realm of network security, Dr. Wang investigates strategies to protect data integrity and confidentiality in increasingly complex digital environments. Additionally, his research on the Internet of Things emphasizes the integration of smart devices and systems, addressing challenges related to security and interoperability. Through his multifaceted research, Dr. Wang aims to contribute to advancements in technology and improve practical applications in these critical areas.

Skills:

Dr. Yonghong Wang possesses a robust skill set that reflects his expertise in multiple domains. He has strong technical proficiency in computer programming and software development, which underpins his work in computer science and software engineering. His skills in computer vision enable him to implement advanced algorithms for image analysis and processing, while his knowledge of network security equips him to devise effective strategies for safeguarding digital information. Dr. Wang is also adept at data analysis, which is essential for his research in the Internet of Things, where he addresses challenges related to data management and device integration. Additionally, his effective communication and collaboration skills enhance his ability to work on interdisciplinary projects and contribute to both academic and industry partnerships.

Conclusion:

Based on his academic and professional achievements, Dr. Wang Yonghong is a suitable candidate for the Best Researcher Award. His work reflects a blend of technical proficiency and practical impact, especially in the fields of computer vision, network security, and IoT. His academic publications, industry engagements, and commitment to ongoing research affirm his qualifications for this award.

Publication Top Noted:

Federated deep learning for anomaly detection in the internet of things

  • Authors: X. Wang, Y. Wang, Z. Javaheri, L. Almutairi, N. Moghadamnejad, O.S. Younes
  • Journal: Computers and Electrical Engineering
  • Volume: 108
  • Article ID: 108651
  • Year: 2023
  • Citations: 51

Attack detection analysis in software-defined networks using various machine learning methods

  • Authors: Y. Wang, X. Wang, M.M. Ariffin, M. Abolfathi, A. Alqhatani, L. Almutairi
  • Journal: Computers and Electrical Engineering
  • Volume: 108
  • Article ID: 108655
  • Year: 2023
  • Citations: 11

WSLC: Weighted semi-local centrality to identify influential nodes in complex networks

  • Authors: X. Wang, M. Othman, D.A. Dewi, Y. Wang
  • Journal: Journal of King Saud University – Computer and Information Sciences
  • Volume: 36
  • Issue: 1
  • Article ID: 101906
  • Year: 2024
  • Citations: 4

Enhancing Enterprise Value Creation Through Intelligent Digital Transformation of the Value Chain: A Deep Learning and Edge Computing Approach

  • Authors: R. Liu, Y. Wang
  • Journal: Journal of the Knowledge Economy
  • Pages: 1-19
  • Year: 2024
  • Citations: 1

Face Recognition Technology Based on Deep Learning Algorithm for Smart Classroom Usage

  • Authors: Y.H. Wang, W.O. Choo, X.F. Wang
  • Journal: Journal of Engineering Science and Technology
  • Volume: 18
  • Pages: 39-47
  • Year: 2023
  • Citations: 1

DFRDRL: A dynamic fuzzy routing algorithm based on deep reinforcement learning with guaranteed latency and bandwidth for software-defined networks

  • Authors: Y. Wang, M. Othman, W.O. Choo, R. Liu, X. Wang
  • Journal: Journal of Big Data
  • Volume: 11
  • Issue: 1
  • Article ID: 150
  • Year: 2024

Ali Raza | Network Attacks | Best Researcher Award

Posted on by ScienceFather

Mr. Ali Raza | Network Attacks | Best Researcher Award

Lecturer at The University Of Lahore, Pakistan

Mr. Ali Raza is an accomplished computer science professional and researcher with a strong academic foundation and expertise in machine learning, cybersecurity, and software development. He completed his MS in Computer Science with a high CGPA of 3.93 from Khwaja Fareed University of Engineering and Information Technology (KFUEIT), where he also earned his bachelor’s degree. Mr. Raza has experience as a Lecturer at the University of Lahore, teaching software engineering courses, and as a Visiting Lecturer at KFUEIT, covering subjects like machine learning and data structures. His industry experience as a Full Stack Python Developer at BuiltinSoft involved developing web applications using Python Django and machine learning frameworks. Mr. Raza has published several impactful research articles in high-ranking journals, focusing on network attack detection, health risk prediction, and cyber-attack prevention. His work combines deep technical skills and a commitment to advancing applied research in computer science.

Profile:

Education:

Mr. Ali Raza holds an impressive academic background, having completed his Master of Science (MS) in Computer Science at Khwaja Fareed University of Engineering and Information Technology (KFUEIT) with a remarkable CGPA of 3.93 in 2023. During his studies, KFUEIT achieved a ranking of #258 in the Asian University Rankings for Southern Asia, underscoring the institution’s reputation for academic excellence. Prior to this, he earned his Bachelor of Science (BS) in Computer Science from the same university, graduating with a CGPA of 3.47 in 2021. This solid educational foundation has equipped Mr. Raza with the necessary knowledge and skills to excel in the fields of computer science and machine learning, fostering his commitment to furthering research and innovation in technology.

Professional Experience:

Mr. Ali Raza has built a solid professional background in academia and industry, contributing to both teaching and software development. Currently, he serves as a Lecturer in the Department of Software Engineering at the University of Lahore, ranked #40 in the Asian University Rankings for Southern Asia, where he specializes in Object-Oriented Programming. Prior to this role, he was a Visiting Lecturer at Khwaja Fareed University of Engineering and Information Technology (KFUEIT) from 2021 to 2023, where he taught a wide range of courses, including Introduction to ICT, Programming Fundamentals, Database Systems, Machine Learning, Data Structures, and Algorithms. Complementing his academic roles, Mr. Raza gained valuable industry experience as a Full Stack Python Developer at BuiltinSoft from 2020 to 2022. In this role, he developed business web applications using Python Django and integrated machine learning frameworks, further enhancing his practical expertise in application development. This blend of academic and industry experience has equipped Mr. Raza with both a deep theoretical foundation and hands-on technical skills.

Research Interests:

Mr. Ali Raza’s research interests center on advancing methodologies in machine learning, cybersecurity, computer vision, and signal processing. He is particularly focused on leveraging machine learning algorithms to enhance network security, developing predictive models to detect cyber threats, and optimizing feature engineering for data-driven health risk analysis. Additionally, his work in computer vision, particularly using deep learning techniques, explores novel approaches for identifying genetic disorders from facial images, providing valuable tools in the field of medical diagnostics. His research contributions demonstrate a commitment to developing innovative, practical solutions that address complex challenges in technology and healthcare.

Conclusion:

Ali Raza’s strong academic background, extensive teaching and industry experience, and impactful research contributions make him a highly suitable candidate for the Best Researcher Award. His interdisciplinary approach, particularly in applying machine learning to pressing challenges in cybersecurity and healthcare, demonstrates a commitment to both innovation and societal impact. His work aligns well with the goals of the award, making him a deserving candidate for recognition.

Publication Top Noted:

A novel deep learning approach for deepfake image detection

  • Authors: A. Raza, K. Munir, M. Almutairi
  • Journal: Applied Sciences
  • Volume: 12
  • Issue: 19
  • Article: 9820
  • Year: 2022
  • Citations: 80

Predicting employee attrition using machine learning approaches

  • Authors: A. Raza, K. Munir, M. Almutairi, F. Younas, MMS Fareed
  • Journal: Applied Sciences
  • Volume: 12
  • Issue: 13
  • Article: 6424
  • Year: 2022
  • Citations: 77

Ensemble learning-based feature engineering to analyze maternal health during pregnancy and health risk prediction

  • Authors: A. Raza, H.U.R. Siddiqui, K. Munir, M. Almutairi, F. Rustam, I. Ashraf
  • Journal: Plos One
  • Volume: 17
  • Issue: 11
  • Article: e0276525
  • Year: 2022
  • Citations: 63

A novel approach for polycystic ovary syndrome prediction using machine learning in bioinformatics

  • Authors: S. Nasim, M.S. Almutairi, K. Munir, A. Raza, F. Younas
  • Journal: IEEE Access
  • Volume: 10
  • Pages: 97610-97624
  • Year: 2022
  • Citations: 39

A performance overview of machine learning-based defense strategies for advanced persistent threats in industrial control systems

  • Authors: M. Imran, H.U.R. Siddiqui, A. Raza, M.A. Raza, F. Rustam, I. Ashraf
  • Journal: Computers & Security
  • Volume: 134
  • Article: 103445
  • Year: 2023
  • Citations: 29

Novel class probability features for optimizing network attack detection with machine learning

  • Authors: A. Raza, K. Munir, M.S. Almutairi, R. Sehar
  • Journal: IEEE Access
  • Year: 2023
  • Citations: 28

Effective feature engineering technique for heart disease prediction with machine learning

  • Authors: A.M. Qadri, A. Raza, K. Munir, M.S. Almutairi
  • Journal: IEEE Access
  • Volume: 11
  • Pages: 56214-56224
  • Year: 2023
  • Citations: 27

A novel methodology for human kinematics motion detection based on smartphones sensor data using artificial intelligence

  • Authors: A. Raza, M.R. Al Nasar, E.S. Hanandeh, R.A. Zitar, A.Y. Nasereddin, et al.
  • Journal: Technologies
  • Volume: 11
  • Issue: 2
  • Article: 55
  • Year: 2023
  • Citations: 24

LogRF: An approach to human pose estimation using skeleton landmarks for physiotherapy fitness exercise correction

  • Authors: A. Raza, A.M. Qadri, I. Akhtar, N.A. Samee, M. Alabdulhafith
  • Journal: IEEE Access
  • Year: 2023
  • Citations: 22

A novel ensemble method for enhancing Internet of Things device security against botnet attacks

  • Authors: A. Arshad, M. Jabeen, S. Ubaid, A. Raza, L. Abualigah, K. Aldiabat, H. Jia
  • Journal: Decision Analytics Journal
  • Volume: 8
  • Article: 100307
  • Year: 2023
  • Citations: 21

Mamoona Khalid | Electrical and Information | Best Researcher Award

Posted on by ScienceFather

Dr. Mamoona Khalid | Electrical and Information | Best Researcher Award

Lecturer at University of Engineering and Technology, Taxila, Pakistan

Dr. Mamoona Khalid is a dedicated lecturer and researcher in the Electrical Engineering Department at the University of Engineering and Technology (UET), Taxila, Pakistan, with over 15 years of teaching and research experience. She holds a Ph.D. in Electrical and Information Engineering from the University of South Australia, where her research focused on germanate waveguide lasers for infrared applications, resulting in multiple publications. An expert in photonics, optical waveguide fabrication, and laser material characterization, Dr. Khalid also serves as Director of the Photonics and Communications Lab at UET. She has been awarded prestigious scholarships, including the University President Scholarship, and has received significant research funding for lab development initiatives. Additionally, Dr. Khalid is an invited speaker and mentor, actively contributing to the academic and professional growth of her students and peers.

Profile:

Education:

Dr. Mamoona Khalid completed her Ph.D. in Electrical and Information Engineering from the University of South Australia, Adelaide, focusing on germanate waveguide lasers for shortwave to mid-infrared applications. Her Ph.D. research, guided by Prof. David G. Lancaster, culminated in the “Thesis by Publications” pathway, with four journal articles and two conference papers published during her studies. She earned her Master’s degree (MSc) in Electrical Engineering from the University of Engineering and Technology (UET), Taxila, where she was awarded a “Distinction” for her thesis on the mathematical modeling and simulation of light propagation through photonic crystal fibers, publishing four papers in HEC-recognized journals. Dr. Khalid graduated with a Bachelor’s degree (BSc) in Electrical Engineering from UET, Taxila, receiving a Gold Medal for her outstanding performance and earning a “High Distinction” with an overall grade of 83.47%.

Professional Experience:

Dr. Mamoona Khalid is a seasoned educator and researcher with over 15 years of experience in electrical engineering. Since 2008, she has served as a Lecturer in the Electrical Engineering Department at the University of Engineering and Technology (UET), Taxila, Pakistan. Her responsibilities include teaching undergraduate and postgraduate courses aligned with the Washington Accord’s Outcome-Based Education (OBE) accreditation standards. Dr. Khalid also supervises research projects for BSc, MSc, and Ph.D. students and is an HEC and Pakistan Engineering Council-approved Ph.D. supervisor. In her administrative role, she has been the Director of the Photonics and Communications Lab since 2022, and she actively mentors students while advising the UET Taxila branches of IEEE and SIEP. She also served as an AI Trainer for OpenAI in 2024, enhancing AI systems through training on large language models. Previously, she was a researcher and tutor at the University of South Australia, where she gained expertise in optical waveguide fabrication, femtosecond laser-based micromachining, and photonics labs.

Research Interests:

Dr. Mamoona Khalid’s research interests focus on advanced areas within electrical engineering, including photonics, optical communication, and laser material fabrication. Her expertise spans the fabrication and characterization of optical waveguides, femtosecond laser micromachining, and the development of fiber lasers and microchip lasers for infrared applications. She is skilled in designing optical communication links and utilizes cutting-edge techniques such as Ytterbium and Holmium doping in laser systems, absorption and fluorescence spectroscopy, and Optical Time Domain Reflectometry (OTDR) for fault detection. Dr. Khalid is also proficient in software and simulation tools including OptiSystem for optical link design, COMSOL Multiphysics, and photonic crystal fiber design using OptiFDTD, making significant contributions to laser material sciences and photonics engineering.

Skills:

Dr. Mamoona Khalid possesses a diverse set of technical skills that complement her expertise in electrical engineering and photonics. She has hands-on proficiency with lab equipment and techniques, including Ytterbium and Holmium doping in laser systems, fiber cleaving and splicing, brightfield microscopy, and optical-grade polishing of transparent materials. Her skills extend to using the Optical Time Domain Reflectometer (OTDR) for detecting faults in optical communication links, as well as designing advanced optical systems. Dr. Khalid is also adept in several specialized software tools, including OptiSystem for optical link design, RP fiber power for laser simulations, COMSOL Multiphysics, SCAPS for solar cell design, and Zemax for ray tracing. In programming, she is skilled in C++, Python, and MATLAB, enabling her to contribute robustly to both practical and computational aspects of research and development in her field.

Conclusion:

Dr. Mamoona Khalid’s extensive teaching and research experience, academic accomplishments, technical expertise, and contributions to photonics and AI make her a suitable candidate for the Best Researcher Award. Her dedication to research, education, and professional development demonstrates a commitment to advancing the field of Electrical Engineering and supporting the next generation of engineers.

Publication Top Noted:

  • Spectroscopic analysis and laser simulations of Yb³⁺/Ho³⁺ co-doped lead-germanate glass
    Authors: M Khalid, DG Lancaster, H Ebendorff-Heidepriem
    Journal: Optical Materials Express, Vol. 10, Issue 11, Pages 2819-2833
    Year: 2020
    Cited by: 17
  • Femtosecond laser induced low propagation loss waveguides in a lead-germanate glass for efficient lasing in near to mid-IR
    Authors: M Khalid, GY Chen, H Ebendorff-Heidepreim, DG Lancaster
    Journal: Scientific Reports, Vol. 11, Article 10742
    Year: 2021
    Cited by: 13
  • Microchip and ultra-fast laser inscribed waveguide lasers in Yb³⁺ germanate glass
    Authors: M Khalid, GY Chen, J Bei, H Ebendorff-Heidepriem, DG Lancaster
    Journal: Optical Materials Express, Vol. 9, Issue 8, Pages 3557-3564
    Year: 2019
    Cited by: 12
  • Germanate glass for laser applications in ∼ 2.1 μm spectral region: A review
    Authors: M Khalid, M Usman, I Arshad
    Journal: Heliyon, Vol. 9, Issue 1
    Year: 2023
    Cited by: 6
  • Long-range distributed vibration sensing using phase-sensitive forward optical transmission
    Authors: GY Chen, K Liu, X Rao, Y Wang, M Khalid, J He, Y Wang
    Journal: Optics Letters, Vol. 48, Issue 18, Pages 4825-4828
    Year: 2023
    Cited by: 4
  • Design and simulation of photonic crystal fibers to evaluate dispersion and confinement loss for wavelength division multiplexing systems
    Authors: M Khalid, I Arshad, M Zafarullah
    Journal: The Nucleus, Vol. 51, Issue 2, Pages 249-258
    Year: 2014
    Cited by: 3
  • Long-range distributed vibration sensing using phase-sensitive forward optical transmission: publisher’s note
    Authors: GY Chen, K Liu, X Rao, Y Wang, M Khalid, J He, Y Wang
    Journal: Optics Letters, Vol. 48, Issue 22, Page 5967
    Year: 2023
    Cited by: 2
  • Recent advancements in femtosecond laser inscribed waveguides in germanate glass for ∼ 2.1 µm laser applications
    Authors: M Khalid, M Usman, MA Nasir, I Arshad
    Journal: Optik, Vol. 273, Article 170462
    Year: 2023
    Cited by: 2
  • Estimation of low loss and dispersion of hollow core photonic crystal fiber designs for WDM systems
    Authors: M Khalid, I Arshad
    Journal: Electrical Engineering, Vol. 1, Issue 2, Page 1
    Year: 2014
    Cited by: 2

Fulong Chen | Water Resources | Best Researcher Award

Posted on by ScienceFather

Mr. Fulong Chen | Water Resources | Best Researcher Award

Professor at Shihezi University, China.

Mr. Fulong Chen, Ph.D., is a Professor and Doctoral Supervisor with a distinguished career in water resource management and hydropower engineering. He currently serves as a member of the Water Resources Management and Conservation Committee of the International Water Resources Association in China and as Vice Chairman of the Shihezi Hydropower Society. Dr. Chen has led over 10 research projects, published more than 70 academic papers (30 indexed by SCI, EI, and CSSCI), and holds 6 patents. His contributions have been recognized through multiple awards, including 4 provincial and ministerial-level honors and a university-level Graduate Education and Teaching Achievement Award. With a Ph.D. in Engineering, Dr. Chen’s expertise and leadership continue to influence sustainable practices in water management.

Profile:

Education:

Mr. Fulong Chen holds a Ph.D. in Engineering, showcasing a strong foundation in advanced research methodologies and technical expertise. His academic journey laid the groundwork for his extensive contributions to water resource management and hydropower research. Through his doctoral studies, Mr. Chen developed a deep understanding of environmental engineering principles, which has been instrumental in his innovative research projects and his role as a Professor and Doctoral Supervisor. His educational background aligns with his professional achievements, emphasizing his dedication to scientific advancement in his field.

Professional Experience:

Mr. Fulong Chen has extensive professional experience in the field of water resource management and hydropower engineering. He has served as a Professor and Doctoral Supervisor, where he has been instrumental in mentoring the next generation of engineers and researchers. In his role, he has led over 10 research projects at various levels, demonstrating his capacity to oversee complex studies that address critical challenges in water management. Additionally, he has been actively involved in professional organizations, holding positions such as Vice Chairman of the Shihezi Hydropower Society and a member of the Water Resources Management and Conservation Committee of the International Water Resources Association in China. His commitment to research and education is further exemplified by his significant contributions to academic publishing, with more than 70 papers authored or co-authored, along with multiple patents, underscoring his role as a leader in innovative practices within the field.

Research Interests:

Mr. Fulong Chen’s research interests encompass a wide range of topics within water resource management and hydropower engineering. He is particularly focused on sustainable water conservation practices, innovative hydropower technologies, and the integration of environmental considerations into engineering solutions. His work often explores the complexities of water resource allocation and management, aiming to develop strategies that promote efficiency and sustainability in water use. Additionally, Dr. Chen has a keen interest in the application of advanced modeling techniques and data analysis in hydrological studies, enabling him to address pressing challenges in water resource management. His commitment to advancing research in these areas is reflected in his extensive publication record and involvement in various research projects that aim to enhance the resilience and sustainability of water systems.

Skills:

Mr. Fulong Chen possesses a diverse skill set that enhances his expertise in water resource management and hydropower engineering. His strong analytical skills enable him to conduct comprehensive research, utilizing advanced modeling techniques and data analysis to address complex hydrological issues. Dr. Chen is adept at leading multidisciplinary research teams, fostering collaboration among researchers, engineers, and industry stakeholders to drive innovative solutions. His technical skills are complemented by a robust understanding of environmental regulations and sustainable practices, allowing him to integrate ecological considerations into engineering designs. Additionally, his experience in academic publishing and patent development reflects his ability to translate research findings into practical applications, further showcasing his commitment to advancing the field of water resource management.

Conclusion:

With a strong foundation in leadership, extensive research output, and numerous accolades, Mr. Fulong Chen’s contributions make him a highly suitable candidate for the Best Researcher Award. His work not only advances knowledge in water resources and hydropower but also sets a standard in academic and pedagogical excellence.

Publication Top Noted:

Glacier Area Change and its Impact on Runoff in the Manas River Basin, Northwest China from 2000 to 2020

  • Authors: Wang, T., Chen, F., Long, A., Liu, B., Huang, Y.
  • Journal: Journal of Arid Land
  • Volume: 16 (7), Pages 877–894
  • Year: 2024
  • Citations: 0

Evaluating the Potential Benefits of Float Solar Photovoltaics through the Water Footprint Recovery Period

  • Authors: Du, S., Liang, C., Sun, H., Disse, M., Zhang, W.
  • Journal: Journal of Cleaner Production
  • Volume: 446, Article 141399
  • Year: 2024
  • Citations: 2

Predicting Runoff from the Weigan River under Climate Change

  • Authors: Su, J., Zhang, P., Deng, X., Chen, F., Long, A.
  • Journal: Applied Sciences (Switzerland)
  • Volume: 14 (2), Article 541
  • Year: 2024
  • Citations: 0

Different Types of Meteorological Drought and their Impact on Agriculture in Central China

  • Authors: Sun, H., Sun, X., Chen, J., Chen, F., Zhang, W.
  • Journal: Journal of Hydrology
  • Volume: 627, Article 130423
  • Year: 2023
  • Citations: 10

Response and Prediction of Runoff to Climate Change in the Headwaters of the Bortala River

  • Authors: Tian, H., Chen, F., Long, A., Liu, J., Hai, Y.
  • Journal: Arid Land Geography
  • Volume: 46 (9), Pages 1432–1442
  • Year: 2023
  • Citations: 4

Impact of the Construction of Water Conservation Projects on Runoff from the Weigan River

  • Authors: Su, J., Long, A., Chen, F., Gu, X., Deng, X.
  • Journal: Water (Switzerland)
  • Volume: 15 (13), Article 2431
  • Year: 2023
  • Citations: 3

Change and Driving Factor Analysis of Eco-Environment of Typical Lakes in Arid Areas

  • Authors: Guo, W., Jiao, A., Wang, W., Yan, J., Chen, F.
  • Journal: Water (Switzerland)
  • Volume: 15 (11), Article 2107
  • Year: 2023
  • Citations: 2