Xiangyun Tang | Artificial Intelligence Security | Best Researcher Award

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Prof. Xiangyun Tang | Artificial Intelligence Security | Best Researcher Award

Associate Professor at Minzu University of China, China

Prof. Xiangyun Tang is a distinguished researcher specializing in machine learning security, data privacy preservation, and applied cryptography. He earned his Ph.D. in Cyberspace Security from the Beijing Institute of Technology, where his research focused on secure and trustworthy distributed machine learning. He also holds a Bachelor of Engineering in Computer Science from Minzu University of China. Prof. Tang has contributed significantly to privacy-preserving systems, including federated learning and blockchain-based secure systems, with numerous publications in prestigious journals and conferences. His work experience includes roles in industry, such as a Machine Learning Engineer at Tencent, and he has been recognized with multiple awards and honors for his academic and professional achievements.

 

Profile

Google Scholar

ORCID

Education

Prof. Xiangyun Tang holds a Ph.D. in Cyberspace Security from the Beijing Institute of Technology, Beijing, China, where he studied from September 2016 to June 2022. His doctoral research focused on “Secure and Trustworthy Distributed Machine Learning,” supervised by Prof. Liehuang Zhu and Prof. Meng Shen, and he achieved an impressive GPA of 3.83/4.00. He also holds a Bachelor of Engineering in Computer Science from Minzu University of China, completed in June 2016, with a GPA of 3.68/4.00. His strong academic foundation underscores his expertise in cybersecurity and distributed systems.

 Experience

Prof. Xiangyun Tang has accumulated extensive experience in academia, research, and industry. As a Ph.D. candidate at the Beijing Institute of Technology, he conducted groundbreaking research in secure and trustworthy distributed machine learning under the guidance of Profs. Liehuang Zhu and Meng Shen. During his tenure as a Machine Learning Engineer at Tencent Technology Inc., he developed real-time forwarding prediction models for cascade graphs and sentiment quantification solutions using Graph Neural Networks. Additionally, he has participated in various funded projects, including privacy-preserving federated learning systems and blockchain-based collaborative learning mechanisms, where he contributed to system design and implementation. Prof. Tang has also provided professional services as a reviewer for top-tier journals like the IEEE Internet of Things J

Research Interests

Prof. Xiangyun Tang’s research interests lie at the intersection of machine learning security, data privacy preservation, and applied cryptography. He focuses on designing robust privacy-preserving verifiability systems to enhance the security of federated learning, effectively defending against malicious participants. His work leverages advanced cryptographic techniques, including zero-knowledge proofs, homomorphic encryption, and secret sharing, to ensure data privacy and system integrity. Prof. Tang’s research aims to address critical challenges in secure collaborative learning and develop innovative solutions that integrate privacy and performance in distributed machine learning environments.

Skills

Prof. Xiangyun Tang possesses a diverse skill set that bridges advanced cryptographic techniques and practical applications in machine learning security. His expertise includes designing privacy-preserving systems utilizing zero-knowledge proofs, homomorphic encryption, and secret sharing to ensure secure and trustworthy distributed machine learning. He is proficient in developing robust algorithms for federated learning, enabling secure data sharing and collaborative training across decentralized environments. Additionally, Prof. Tang has extensive experience in sentiment quantification, real-time data analysis on cascade graphs, and implementing secure systems for software-defined networks and blockchain-based applications. His technical acumen is complemented by strong problem-solving skills and a commitment to advancing data privacy and cybersecurity.

 

Publications

Privacy-Preserving Support Vector Machine Training over Blockchain-Based Encrypted IoT Data in Smart Cities

  • Authors: M. Shen, X. Tang, L. Zhu, X. Du, M. Guizani
  • Journal: IEEE Internet of Things Journal
  • Volume: 6 (5), Pages: 7702-7712
  • Cited By: 465
  • Year: 2019

Privacy-Preserving DDoS Attack Detection Using Cross-Domain Traffic in Software Defined Networks

  • Authors: L. Zhu, X. Tang, M. Shen, X. Du, M. Guizani
  • Journal: IEEE Journal on Selected Areas in Communications
  • Volume: 36 (3), Pages: 628-643
  • Cited By: 121
  • Year: 2018

Secure SVM Training over Vertically-Partitioned Datasets Using Consortium Blockchain for Vehicular Social Networks

  • Authors: M. Shen, J. Zhang, L. Zhu, K. Xu, X. Tang
  • Journal: IEEE Transactions on Vehicular Technology
  • Volume: 69 (6), Pages: 5773-5783
  • Cited By: 87
  • Year: 2019

Privacy-Preserving Machine Learning Training in IoT Aggregation Scenarios

  • Authors: L. Zhu, X. Tang, M. Shen, F. Gao, J. Zhang, X. Du
  • Journal: IEEE Internet of Things Journal
  • Volume: 8 (15), Pages: 12106-12118
  • Cited By: 33
  • Year: 2021

Pile: Robust Privacy-Preserving Federated Learning via Verifiable Perturbations

  • Authors: X. Tang, M. Shen, Q. Li, L. Zhu, T. Xue, Q. Qu
  • Journal: IEEE Transactions on Dependable and Secure Computing
  • Volume: 20 (6), Pages: 5005-5023
  • Cited By: 28
  • Year: 2023

Blockchains for Artificial Intelligence of Things: A Comprehensive Survey

  • Authors: M. Shen, A. Gu, J. Kang, X. Tang, X. Lin, L. Zhu, D. Niyato
  • Journal: IEEE Internet of Things Journal
  • Volume: 10 (16), Pages: 14483-14506
  • Cited By: 27
  • Year: 2023

Secure and Trusted Collaborative Learning Based on Blockchain for Artificial Intelligence of Things

  • Authors: X. Tang, L. Zhu, M. Shen, J. Peng, J. Kang, D. Niyato, A. A. Abd El-Latif
  • Journal: IEEE Wireless Communications
  • Volume: 29 (3), Pages: 14-22
  • Cited By: 24
  • Year: 2022

Secure Semantic Communications: Challenges, Approaches, and Opportunities

  • Authors: M. Shen, J. Wang, H. Du, D. Niyato, X. Tang, J. Kang, Y. Ding, L. Zhu
  • Journal: IEEE Network
  • Cited By: 15
  • Year: 2023

Fully Exploiting Cascade Graphs for Real-Time Forwarding Prediction

  • Authors: X. Tang, D. Liao, W. Huang, L. Zhu, M. Shen, J. Xu
  • Conference: AAAI 2021 Conference
  • Cited By: 36
  • Year: 2021

When Homomorphic Cryptosystem Meets Differential Privacy: Training Machine Learning Classifier with Privacy Protection

  • Authors: X. Tang, L. Zhu, M. Shen, X. Du
  • Platform: arXiv preprint
  • arXiv ID: arXiv:1812.02292
  • Cited By: 11
  • Year: 2018

Conclusion

Prof. Xiangyun Tang’s extensive contributions to privacy-preserving machine learning, applied cryptography, and data security establish him as an exceptional candidate for the Research for Best Researcher Award. His innovative research, industry experience, academic service, and numerous accolades collectively make him highly deserving of this recognition.

A S M Ahsanul Sarkar Akib | Cyber Threat | Best Researcher Award

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Mr. A S M Ahsanul Sarkar Akib | Cyber Threat | Best Researcher Award

Managing Director at Robo Tech Valley, Bangladesh

Mr. A.S.M. Ahsanul Sarkar Akib is a highly accomplished robotics and technology expert based in Bangladesh. He holds a Bachelor of Science in Engineering from the Bangladesh University of Business and Technology, specializing in Computer Science and Engineering. With a strong passion for robotics, IoT, and drone development, he has gained extensive experience in the field through roles such as Technical Director at the Japan-Bangladesh Robotics and Advanced Technology Research Centre, and Robotics Trainer at various universities. Additionally, he is the Founder & CEO of Dhopa Elo Online Laundry Service and Robo Tech Valley & Shop. Mr. Akib has also earned several accolades, including multiple championships in robotics competitions such as Ureckon 19 in India and Technocracy 2019 in Bangladesh. His innovative projects include humanoid robots, self-learning AI educational robots, and IoT-based solutions for water turbines and smart door systems.

 

Profile

Google Scholar

ORCID

Education

Mr. A.S.M. Ahsanul Sarkar Akib has a robust academic foundation, highlighted by his Bachelor of Science (B.Sc.) in Engineering from the Department of Computer Science and Engineering at Bangladesh University of Business and Technology. His academic journey is marked by exceptional achievements, including a GPA of 4.94 in his Higher Secondary Certificate (HSC) examinations from Cantonment Public School and College (BUSMS) under the Dinajpur Board, specializing in science. He also excelled in his Secondary School Certificate (SSC) examinations, attaining a GPA of 4.75 from the same institution. These accomplishments reflect his strong analytical abilities and dedication to academic excellence.

 Experience

Mr. A.S.M. Ahsanul Sarkar Akib has a diverse and extensive professional background in robotics, technology, and entrepreneurship. He has been serving as the Technical Director at the Japan-Bangladesh Robotics and Advanced Technology Research Centre since May 2018, where he plays a key role in advancing research and development in robotics. Additionally, he worked as a Robotics Trainer at BGC Trust University (Chattogram) and the National Academy for Computer Training and Research (NACTAR) in 2020. Mr. Akib also served as a Project Coordinator and Researcher at the Bangladesh Advance Robotics Research Center in 2018 and worked as a Robotics Engineer at Rafusoft Software and Robotics Firm between 2017 and 2018. Throughout his career, he has contributed to various robotics workshops across leading universities in Bangladesh, including Dhaka University, NSU, and Brac University. As an entrepreneur, Mr. Akib is the Founder & CEO of Dhopa Elo Online Laundry Service and the Founder & Managing Director of Robo Tech Valley & Shop, where he continues to drive innovation in both technology and business.

Research Interests

Mr. A.S.M. Ahsanul Sarkar Akib’s research interests lie in the fields of robotics, Internet of Things (IoT), and drone development. He focuses on developing cutting-edge technologies such as self-learning AI systems, humanoid robots, and IoT-based automation solutions. His work includes designing innovative projects like the Humanoid Bangla AI Robot “Bongo,” a self-learning educational robot, and various robotics systems for renewable energy applications, including hydro power water turbines and automated fish farming solutions. Mr. Akib is also passionate about developing IoT-based systems for smart home automation, water monitoring, and waste management. Through his research, he aims to push the boundaries of robotics and IoT technologies to improve daily life and contribute to sustainable development.

Skills

Mr. A.S.M. Ahsanul Sarkar Akib possesses a diverse set of technical skills, with expertise in robotics, IoT, and drone development. He is proficient in programming languages such as C, C++, Java, and Python, and has hands-on experience with Robotics Operating Systems (ROS). His technical skills also include working with Latex for documentation, and he is adept at designing and developing complex robotics systems. Additionally, Mr. Akib has specialized knowledge in the creation of self-learning AI models and the development of IoT-based solutions for smart homes, water monitoring systems, and renewable energy projects. His skills in project coordination and leadership, coupled with his deep understanding of cutting-edge technology, have made him a valuable asset in various robotics and technology-driven initiatives.

 

Publications

Artificial Intelligence Humanoid Bongo Robot in Bangladesh

  • Conference: 2019 1st International Conference on Advances in Science, Engineering, and Technology
  • Cited By: 22
  • Year: 2019

Future Micro Hydro Power: Generation of Hydroelectricity and IoT-Based Monitoring System

  • Conference: 2021 International Conference on Innovation and Intelligence for Informatics
  • Cited By: 4
  • Year: 2021

Precision Fish Farming to Mitigate Pond Water Quality Through IoT

  • Conference: 2024 IEEE 3rd International Conference on Computing and Machine Intelligence
  • Cited By: 1
  • Year: 2024

Computer Vision-Based IoT Architecture for Post-COVID-19 Preventive Measures

  • Journal: Journal of Advances in Information Technology
  • Volume: 14 (1), Pages: 7-19
  • Cited By: 5
  • Year: 2023

IoT-Based Smart Remote Door Lock and Monitoring System Using an Android Application

  • Journal: Engineering Proceedings
  • Volume: 76 (1), Pages: 85
  • Year: 2024

Conclusion

Mr. A.S.M. Ahsanul Sarkar Akib’s academic excellence, innovative research, and diverse professional achievements make him a strong candidate for the Best Researcher Award. His groundbreaking projects, technical expertise, and dedication to advancing robotics and IoT position him as a leader in his field, deserving of recognition for his contributions to science and technology.

Yanpeng Song | Museum Studies | Best Researcher Award

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Dr. Yanpeng Song | Museum Studies | Best Researcher Award

Director at Information Center of Dunhuang Research Academy, China

Dr. Yanpeng Song is a distinguished researcher and academic in the field of museum studies and grotto arts. He earned his Ph.D. in Museum Studies from the University of Leicester, UK, in 2023, with a focus on the role of museums in promoting moral education for middle school children in China. Dr. Song has been a key staff member at the Dunhuang Research Academy since 2012, where he currently serves as the Director of the Information Center for Dunhuang Studies. He has published over ten academic papers on topics related to Dunhuang grottoes and museum education. Additionally, he has led significant research projects, including a literature review on the Silk Road and Dunhuang, supported by the Dunhuang Research Academy. Dr. Song has also been involved in several national research projects funded by China’s National Social Science Foundation and Ministry of Education. As a respected expert, he has given numerous lectures in museums and universities and actively participates in international academic exchanges, earning recognition in the global academic community.

 

Profile

ORCID

Education

Dr. Yanpeng Song holds a Ph.D. in Museum Studies from the University of Leicester, UK, where he completed his studies from January 2019 to January 2023. His doctoral dissertation, titled “From Moral Indoctrination to Moral Experience: An Experiential Model for Promoting Middle School Children’s Moral Education in China’s Museums,” reflects his innovative approach to museum education. Prior to his Ph.D., Dr. Song earned a Master of Business Administration (MBA) from Lanzhou Jiaotong University between September 2010 and December 2012. He also holds a Bachelor of Arts in English Language and Literature from Anhui Normal University, which he completed from September 2003 to July 2007, and passed the Test for English Majors (TEM-8), further demonstrating his proficiency in the English language. Dr. Song’s diverse educational background has equipped him with a strong foundation in both humanities and business, enabling him to contribute significantly to the fields of museum studies and Dunhuang research.

 Experience

Dr. Yanpeng Song has an extensive professional background in museum studies and cultural heritage research. Since 2012, he has been a key staff member at the Dunhuang Research Academy, where his career has advanced significantly. He served as the Deputy Director of the Information Center for Dunhuang Studies from 2021 to 2024, and in 2024, he was promoted to Director of the Information Center. In addition to his leadership role, Dr. Song has contributed to various research projects, including those supported by the National Social Science Foundation of China and the Ministry of Education of China. He has also worked as a Master’s supervisor at Lanzhou University, mentoring the next generation of scholars. Throughout his career, Dr. Song has been involved in numerous academic seminars, conferences, and international exchange activities, enhancing his reputation in the field of museum studies and grotto art research. His professional work focuses on the intersection of cultural heritage, museum education, and the preservation of Dunhuang’s artistic legacy.

Research Interests

Dr. Yanpeng Song’s research interests lie at the intersection of cultural heritage, museum studies, and grotto art, with a particular focus on the rich legacy of the Dunhuang region. He explores innovative approaches to moral education in museums, as exemplified by his doctoral research on experiential models for middle school children’s moral development. His work delves into the artistic and historical significance of Dunhuang Grottoes, examining topics such as iconography, mural analysis, and thematic representations. Additionally, Dr. Song is dedicated to advancing the understanding of the relationship between the Silk Road and Dunhuang’s cultural history. His academic pursuits extend to enhancing museum learning experiences and fostering global discussions on cultural preservation and education. Through his research, Dr. Song contributes to the preservation and promotion of invaluable cultural assets, bridging historical insights with contemporary educational practices.

Skills

Dr. Yanpeng Song possesses strong analytical and research skills, particularly in cultural heritage and museum studies, with expertise in iconography and historical interpretation. He is proficient in project management, academic writing, and publishing, demonstrated through successful research projects and numerous scholarly articles. As a skilled educator and public speaker, he supervises master’s students and delivers lectures at universities and museums. His technological proficiency and multilingual abilities enhance his leadership in managing digital tools and facilitating international collaborations, solidifying his global academic reputation.

 

Publications

Moral Feeling in a Museum Learning Through an Exemplar-Based Thematic Exhibition

  • Journal: Curator: The Museum Journal
  • Date: 2024-11-28
  • Type: Journal Article

A Preliminary Study on the Relationship between the Paintings on the South Wall and the Votive Text on the North Wall in Mogao Cave 285

  • Journal: Dunhuang Studies
  • Date: 2024-11-26
  • Type: Journal Article (Writing – Original Draft)

Research on the Cock Images in Mogao Cave 285

  • Publication: Proceedings of Research Seminar on Mogao Cave 285
  • Date: 2024-06-11
  • Type: Conference Paper

Research on the Images of Dragon-Shaped Pendant in Dunhuang and Yungang Grottoes

  • Journal: Journal of Hongde
  • Date: 2024-06-01
  • Type: Journal Article (Writing – Original Draft)

Research on the Images and Source of the Three-Pronged Crown Seen in Dunhuang Grottoes

  • Journal: Image Historical Studies
  • Date: 2023-06-01
  • Type: Journal Article

From Moral Indoctrination to Moral Experience: An Experiential Model for Promoting Middle School Children’s Moral Education in China’s Museums

  • Type: Dissertation/Thesis
  • Date: 2023-01-16

Summary of the 2021 Academic Seminar on Dunhuang Studies from the Perspective of the ‘One Belt and One Road’ Initiative & the Council Meeting of the Chinese Association of Dunhuang and Turfan Studies

  • Journal: Dunhuang Studies
  • Date: 2022-01-02
  • Type: Journal Article

Conclusion

Dr. Yanpeng Song’s exceptional research output, leadership in Dunhuang studies, and his influential role in advancing museum education make him a remarkable candidate for the Best Researcher Award. His multidisciplinary expertise, combined with a commitment to academic excellence and international collaboration, positions him as a highly deserving recipient of this recognition.

Swati Tyagi | Mathematical Modelling | Women Researcher Award

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Assist. Prof. Dr. Swati Tyagi | Mathematical Modelling | Women Researcher Award

Assistant Professor at Amity University Punjab, India

Assist. Prof. Dr. Swati Tyagi is an accomplished mathematician and educator, currently serving as an Assistant Professor at Amity University, Mohali. She holds a Ph.D. in Mathematics from IIT Mandi, where she specialized in neural network models and differential equations. With a strong academic background, including an M.Sc. in Mathematics (H) from Panjab University and a B.Sc. in Computer Science, she has held teaching and research positions at prestigious institutions such as Punjab Engineering College, Chandigarh University, and Shoolini University. Her research focuses on mathematical modeling, epidemiology, delay differential equations, fractional differential equations, and stability analysis. Dr. Tyagi has received several accolades, including the SERB National Postdoctoral Fellowship and recognition for her highly cited research. A prolific scholar, she has published extensively in reputed journals, presented at numerous international conferences, and contributed actively to academic administration and journal reviewing.

 

Profile

Google Scholar

Education

Assist. Prof. Dr. Swati Tyagi has an impressive academic trajectory, reflecting her dedication to the field of mathematics. She completed her Ph.D. in Mathematics at IIT Mandi in 2016, earning a remarkable CGPA of 8. Prior to this, she pursued her M.Sc. in Mathematics (Hons.) from Panjab University, graduating in 2011 with a commendable score of 69.55%. Her foundational studies include a B.Sc. in Computer Science from Panjab University, where she excelled with a score of 78.75% in 2009. Dr. Tyagi’s secondary education also highlights her academic excellence, with 81% in her Senior Secondary (Non-Medical) from CBSE in 2006 and an outstanding 86.8% in her High School from PSEB in 2004. Her consistent academic performance was recognized through various scholarships and merit certificates, underscoring her strong academic foundation.

Experience

Assist. Prof. Dr. Swati Tyagi has extensive academic and research experience, having contributed to various prestigious institutions. Currently an Assistant Professor at Amity University, Mohali, she previously served as an Assistant Professor in Mathematics at Chandigarh University and Punjab Engineering College (Deemed to be University), Chandigarh. She gained valuable postdoctoral research experience as a SERB National Postdoctoral Fellow at IIT Ropar, where she worked on advanced neural network models under the mentorship of Dr. S.C. Martha. Earlier in her career, Dr. Tyagi held teaching positions at Shoolini University, Solan, and Chandigarh Group of Colleges, Landran. Her teaching portfolio includes a wide range of undergraduate and postgraduate courses, and she has also served as a teaching assistant for mathematics courses during her tenure at IIT Mandi and IIT Ropar. Dr. Tyagi has been actively involved in academic administration, event coordination, and mentoring students throughout her career.

Research Interests

Assist. Prof. Dr. Swati Tyagi’s research interests lie at the intersection of applied mathematics and computational sciences, with a focus on mathematical modeling and epidemiology. Her work encompasses the study of delay differential equations, fractional differential equations, and neural networks, delving into their stability analysis and solution approximations. Dr. Tyagi is particularly interested in exploring the dynamics of infectious diseases, developing advanced models for neural networks, and analyzing their implications in real-world applications. Her contributions also extend to numerical methods and theoretical frameworks that enhance the understanding of complex systems in her field.

Skills

Assist. Prof. Dr. Swati Tyagi possesses a diverse set of skills that bridge theoretical mathematics and practical computational applications. She is proficient in advanced mathematical techniques, including stability analysis, approximation methods, and modeling complex systems such as neural networks and infectious disease dynamics. Her expertise in computational tools like MATLAB, Maple, and LaTeX enhances her ability to conduct simulations and present research findings effectively. Additionally, her skills in teaching and mentoring students are demonstrated through her extensive experience in delivering undergraduate and postgraduate courses in mathematics and related subjects. Dr. Tyagi is also skilled in academic writing, peer review, and conference presentations, which complement her research and academic endeavors.

 

Publications

Global analysis of a delayed density dependent predator–prey model with Crowley–Martin functional response

  • Authors: JP Tripathi, S Tyagi, S Abbas
  • Journal: Communications in Nonlinear Science and Numerical Simulation
  • Year: 2016
  • Volume: 30, Issues: 1-3, Pages: 45-69
  • DOI: 10.1016/j.cnsns.2015.06.002

Finite-time stability for a class of fractional-order fuzzy neural networks with proportional delay

  • Authors: S Tyagi, SC Martha
  • Journal: Fuzzy Sets and Systems
  • Year: 2019
  • DOI: 10.1016/j.fss.2018.04.011

Discrete fractional‐order BAM neural networks with leakage delay: existence and stability results

  • Authors: J Alzabut, S Tyagi, S Abbas
  • Journal: Asian Journal of Control
  • Year: 2020
  • Volume: 22, Issue: 1, Pages: 143-155
  • DOI: 10.1002/asjc.1973

Mathematical modeling and analysis for controlling the spread of infectious diseases

  • Authors: S Tyagi, SC Martha, S Abbas, A Debbouche
  • Journal: Chaos, Solitons & Fractals
  • Year: 2021
  • Volume: 144, Article: 110707
  • DOI: 10.1016/j.chaos.2021.110707

Global exponential stability of fractional‐order impulsive neural network with time‐varying and distributed delay

  • Authors: HM Srivastava, S Abbas, S Tyagi, D Lassoued
  • Journal: Mathematical Methods in the Applied Sciences
  • Year: 2018
  • Volume: 41, Issue: 5, Pages: 2095-2104
  • DOI: 10.1002/mma.4734

Global Mittag–Leffler stability of complex valued fractional-order neural network with discrete and distributed delays

  • Authors: S Tyagi, S Abbas, M Hafayed
  • Journal: Rendiconti del Circolo Matematico di Palermo Series 2
  • Year: 2016
  • Volume: 65, Pages: 485-505
  • DOI: 10.1007/s12215-015-0190-1

Stability and bifurcation analysis of a fractional‐order model of cell‐to‐cell spread of HIV‐1 with a discrete time delay

  • Authors: S Abbas, S Tyagi, P Kumar, VS Ertürk, S Momani
  • Journal: Mathematical Methods in the Applied Sciences
  • Year: 2022
  • Volume: 45, Issue: 11, Pages: 7081-7095
  • DOI: 10.1002/mma.8071

Conclusion

Dr. Swati Tyagi’s impressive academic achievements, pioneering research, and contributions to the mathematical community make her a deserving candidate for the Research for Women Researcher Award. Her dedication to advancing knowledge and mentoring future generations further underscores her exceptional profile.

Nagamaniammai Govindarajan | Food Technology | Best Researcher Award

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Assoc. Prof. Dr. Nagamaniammai Govindarajan | Food Technology | Best Researcher Award

Associate Professor at SRM Institute of Science and Technology, India

Assoc. Prof. Dr. Nagamaniammai Govindarajan is a distinguished academic and researcher with over 21 years of experience spanning academia, industry, and quality assurance. She holds a Ph.D. in Nutraceutical and Functional Foods from SRM Institute of Science and Technology, Chennai. Her academic background includes an M.Tech. in Food Technology and Biochemical Engineering from Jadavpur University and a B.E. in Food Processing and Preservation Technology from Avinashilingam Deemed University. Currently serving as an Associate Professor in the Department of Food Process Engineering at SRM Institute of Science and Technology, she is actively involved in teaching, mentoring, and research. Her expertise includes food processing, nutraceutical development, quality systems, and value-added food products. Dr. Govindarajan has also contributed significantly to her field with numerous publications in SCI-indexed journals, focusing on innovative approaches to food technology and nutrition.

 

Profile

SCOPUS

ORCID

Education

Assoc. Prof. Dr. Nagamaniammai Govindarajan holds a Ph.D. in Process Development, Optimization, and Quality Evaluation of Nutraceutical and Functional Foods from SRM Institute of Science and Technology (SRM University), Chennai, completed in June 2014. She earned her Master of Technology in Food Technology and Biochemical Engineering from Jadavpur University, Kolkata, graduating with 71% in 2004. Additionally, she holds a Bachelor of Engineering in Food Processing and Preservation Technology from Avinashilingam Deemed University, Coimbatore, where she graduated with 69% in 2001. Her diverse academic qualifications form a strong foundation for her expertise in food science and technology.

Experience

Assoc. Prof. Dr. Nagamaniammai Govindarajan brings over 21 years of extensive experience in academia, corporate sectors, and research and development. She currently serves as an Associate Professor in the Department of Food Process Engineering at SRM Institute of Science and Technology, where she teaches M.Tech. courses, mentors Ph.D. and M.Tech. students, establishes industry linkages, and spearheads academic research initiatives. Previously, she was Professor and Head of the Department of Food Processing Technology at AMET University, where she successfully implemented activity-based teaching methodologies, established undergraduate program infrastructure, and secured external funding for research. Her industry experience includes serving as Assistant General Manager and Head (QA – R&D) at Sri Varadaraja Food Exports Pvt. Ltd., where she established quality systems adhering to ISO 9001:2015, ISO 22000:2005, HACCP, and organic processing standards. Dr. Govindarajan’s career reflects her commitment to excellence in teaching, research, and the food processing industry.

Research Interests

Assoc. Prof. Dr. Nagamaniammai Govindarajan’s research interests are deeply rooted in the field of food science and technology, with a particular focus on the development of nutraceutical and functional foods. She is dedicated to optimizing processing techniques to enhance the nutritional quality of food products and mitigate anti-nutritional factors. Her work explores the utilization of underutilized legumes, plant-based protein alternatives, and advanced food processing methods to address global nutritional challenges. Additionally, she is keenly interested in food safety, quality assurance systems, and innovative approaches to sustainable food production, contributing to advancements in both academic and industrial food science domains.

Skills

Assoc. Prof. Dr. Nagamaniammai Govindarajan possesses extensive research skills in food science and technology, with expertise in developing innovative processes for nutraceuticals and functional foods. She is adept at process development, optimization, and quality evaluation, focusing on enhancing the nutritional value of food products while mitigating anti-nutritional factors. Her skills include advanced techniques in food processing, such as leveraging legumes and plant-based proteins for sustainable alternatives. She is proficient in quality assurance systems, including ISO and HACCP standards, ensuring safety and compliance in food production. Additionally, her analytical abilities extend to experimental design, data interpretation, and collaborative research, contributing to impactful publications in leading scientific journals.

 

Publications

Traditional weaning foods and processing methods with fortification for sustainable development of infants to combat zero hunger: a review

  • Authors: Kabeer, S., Mary, S.J., Govindarajan, N., Essa, M.M., Qoronfleh, M.W.
  • Journal: Journal of Food Science and Technology
  • Year: 2024
  • Volume: 61(12), Pages: 2263–2274

Unlocking the potential of underutilized legumes: nutritional benefits, anti-nutritional challenges, and mitigation strategies

  • Authors: Navin Venketeish, K.S., Govindarajan, N., Pandiselvam, R., Mousavi Khaneghah, A.
  • Journal: Journal of Food Measurement and Characterization
  • Year: 2024
  • Volume: 18(11), Pages: 9588–9602

Optimization and extraction of annatto pigments obtained from Bixa orellana L. using supercritical fluid extraction

  • Authors: Paramadhas, S., Selvi, P., Shridar, B., Govindarajan, N., Pandiselvam, R.
  • Journal: Microchemical Journal
  • Year: 2024
  • Volume: 206, Article: 111494

Effect of drying methods on the biochemical and functional qualities of ready-to-mix traditional pearl millet porridge (Pennisetum glaucum)

  • Authors: Sivasubramaniyan, V., Govindarajan, N., Kottur Senthilkumar, N.V., Kabeer, S.
  • Journal: International Journal of Nutrition, Pharmacology, Neurological Diseases
  • Year: 2024
  • Volume: 14(3), Pages: 337–342

Effect of partial replacement of whole milk khoa with groundnut (Arachis hypogaea) and sunflower seeds (Helianthus annuus) milk on biochemical and functional properties

  • Authors: Sivaraj, D., Govindarajan, N., Pandiselvam, R.
  • Journal: Journal of Food Science and Technology
  • Year: 2024

Impact of Different Processing Techniques on the Retention of Zinc in Foods

  • Authors: Govindarajan, N., Kabeer, S., Venketeish, N.
  • Book Chapter: Zinc: Early Development, Applications, and Emerging Trends
  • Year: 2024
  • Pages: 223–231

Effect of drying technique on physiochemical and nutritional properties of Eleusine coracana (finger millet) porridge powder

  • Authors: Kabeer, S., Govindarajan, N., Radhakrishnan, P., Essa, M.M., Qoronfleh, M.W.
  • Journal: Journal of Food Science and Technology
  • Year: 2023
  • Volume: 60(12), Pages: 3024–3034

Biosensors as freshness indicators for packed animal and marine products: A review

  • Authors: Milintha, T.P.M., Kumaravel, B., Nagamaniammai, G., Qoronfleh, M.W., Chacko, L.
  • Journal: International Food Research Journal
  • Year: 2023
  • Volume: 30(4), Pages: 848–854

Conclusion

Assoc. Prof. Dr. Nagamaniammai Govindarajan’s robust academic background, diverse professional experience, and impactful research outputs make her an excellent candidate for the “Best Researcher Award.” Her contributions to nutraceuticals, functional foods, and sustainable food processing reflect her commitment to advancing science and addressing global challenges.

Ms. Sana Naz | Blockchain Consensus | Best Researcher Award

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Ms. Sana Naz | Blockchain Consensus | Best Researcher Award

Ph.D. Scholar at Hanyang University, South Korea

Ms. Sana Naz, born in Karachi, Pakistan, in 1990, is a dedicated researcher and academic in the field of Computer Science and Engineering. She holds a B.S. in Computer Engineering from Sir Syed University of Engineering and Technology and an M.S. in Software Engineering from Hamdard University. Currently, she is pursuing her Ph.D. at Hanyang University, South Korea, with a focus on blockchain technology and consensus mechanisms. With prior experience as a faculty member at Dawood University of Engineering and Technology and as a Software Engineer, Ms. Naz has contributed to both academia and industry. Her research interests include blockchain networks, software design patterns, and code quality, complemented by her active participation in professional organizations like the Pakistan Engineering Council.

 

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Education

Ms. Sana Naz was born in Karachi, Pakistan, in 1990. She completed her Bachelor of Science degree in Computer Engineering from Sir Syed University of Engineering and Technology, Pakistan, in 2012. She then pursued her Master of Science degree in Software Engineering at Hamdard University, Pakistan, graduating in 2016. Currently, she is advancing her academic journey by pursuing a Ph.D. in Computer Science and Engineering at Hanyang University, South Korea, where her research focuses on developing innovative consensus mechanisms for blockchain networks.

Experience

Ms. Sana Naz has a diverse professional background, blending academic and industry expertise. Before pursuing her Ph.D. in Computer Science and Engineering at Hanyang University, South Korea, she served as a faculty member in the Computer Engineering Department at Dawood University of Engineering and Technology, Pakistan. During her tenure, she contributed to curriculum development and academic mentorship. In addition to her academic roles, she gained significant industry experience as a Software Engineer, working with various software houses on projects involving software development and design. This combination of teaching and industry experience has equipped her with a strong foundation for conducting impactful research in blockchain technology and software engineering.

Research Interests

Ms. Sana Naz’s research interests lie at the intersection of blockchain technology and software engineering. She is particularly focused on developing advanced consensus mechanisms for blockchain networks to enhance their security and efficiency. Her work also delves into software design patterns, anti-patterns, and code smells, aiming to improve software quality and maintainability. With a keen interest in exploring innovative solutions, she is dedicated to advancing the fields of cybersecurity and cryptography through her research contributions.

Skills

Ms. Sana Naz possesses a versatile skill set that spans both technical and academic domains. She is proficient in blockchain technology, specializing in developing and optimizing consensus mechanisms. Her expertise extends to software engineering, including software design patterns, anti-patterns, and code quality analysis. Additionally, she holds certifications such as Microsoft Technology Associate (MTA) in Database and Software Development (C#) and Microsoft Office Specialist (MOS) in Word, Excel, and PowerPoint. With strong analytical and problem-solving abilities, Ms. Naz combines her technical expertise with a solid foundation in research and teaching, making her a well-rounded professional in her field.

 

Publications

Title: Why the New Consensus Mechanism is Needed in Blockchain Technology?

  • Authors: S. Naz, SUJ Lee
  • Conference: 2020 Second International Conference on Blockchain Computing and Applications
  • Year: 2020
  • Citations: 23

Title: Sea Shield: A Blockchain Technology Consensus to Improve Proof-of-Stake-Based Consensus Blockchain Safety

  • Authors: S. Naz, SUJ Lee
  • Journal: Mathematics
  • Year: 2024
  • Volume: 12
  • Issue: 6
  • Article ID: 833
  • Citations: 0

Title: S&Sem: A Secure and Speed-Up Election Mechanism for PoS-Based Blockchain Network

  • Authors: S. Naz, SUJ Lee
  • Status: Available at SSRN
  • Year: 2024

Conclusion

Ms. Sana Naz is a strong candidate for the Best Researcher Award in the category of Cybersecurity and Cryptography. Her innovative contributions to blockchain technology, combined with her academic and professional accomplishments, make her a deserving nominee. Additionally, she is equally qualified for recognition in categories such as the Women Research Award, Young Scientist Award, and Best Research Scholar Award. Her work is both relevant and forward-looking, contributing to the advancement of secure and efficient blockchain systems.

Sunzida Siddique | Physical Models with AI | Best Researcher Award

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Ms. Sunzida Siddique | Physical Models with AI | Best Researcher Award

Student at Daffodil International University, Bangladesh

Ms. Sunzida Siddique is a skilled software engineer and researcher with a strong academic foundation in Computer Science. She holds a Master of Science in Computer Science from Jahangirnagar University and a Bachelor of Science in Computer Science & Engineering from Daffodil International University. Currently working as a Jr. Software Engineer at Silicon Orchard Ltd., she specializes in AI, machine learning, deep learning, and cybersecurity. Ms. Siddique has contributed to several impactful projects, including Bengali speech-based gender classification and machine learning-based book reading level prediction. Her leadership experience includes roles as an organizer and research instructor in various tech-related clubs. With expertise in programming, web development, and advanced computational techniques, she is committed to advancing research and technology.

 

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Education

Ms. Sunzida Siddique has an impressive academic background, which reflects her dedication and aptitude in the field of Computer Science and Engineering. She holds a Master of Science (M.Sc.) in Computer Science from Jahangirnagar University, where she graduated with a remarkable CGPA of 3.83. Her academic journey also includes a Bachelor of Science (B.Sc.) in Computer Science & Engineering from Daffodil International University, where she achieved a strong CGPA of 3.70. Prior to her university education, Ms. Siddique completed her Higher Secondary Certificate from Narsingdi Model College in 2015, securing a perfect 5.00 in the Science group. She also earned a Secondary School Certificate from Brahmondi Girl’s High School in 2013, where she similarly excelled with a perfect score of 5.00. Ms. Siddique’s consistent academic excellence throughout her educational journey highlights her commitment to mastering her field and her readiness to contribute to cutting-edge research and technological advancements.

Experience

Ms. Sunzida Siddique has gained valuable professional experience in both technical and administrative roles. Since February 2023, she has been working as a Jr. Software Engineer at Silicon Orchard Ltd., where she applies her skills in AI, machine learning, deep learning, cybersecurity, and generative AI to solve complex analytical problems. Her work focuses on leveraging cutting-edge technologies to address challenges in various domains. Prior to this, Ms. Siddique served as an Office Executive at Future Cloud Bangladesh Ltd. from April 2021 to January 2023, where she handled customer service, administrative duties, and maintained effective communication through email and phone. This role honed her multitasking and communication skills while allowing her to gain valuable experience in organizational operations. Her professional journey reflects a strong

Research Interests

Ms. Sunzida Siddique’s research interests lie at the intersection of Artificial Intelligence (AI), Machine Learning, Deep Learning, and Cybersecurity. She is particularly focused on exploring innovative solutions through AI-driven techniques, such as natural language processing and computer vision, to address real-world challenges. Her work includes projects like Bengali Continuous Speech Voice-Based Gender Classification and Machine Learning-based Book Reading Level Prediction, where she applies machine learning algorithms to enhance language processing and educational tools. Additionally, Ms. Siddique is interested in the integration of Physics Guided Neural Networks and Knowledge Graphs to solve complex scientific problems. Her passion for advancing Generative AI and Cybersecurity further drives her research, as she aims to create secure, efficient, and intelligent systems that can transform industries and improve everyday life.

Skills

Ms. Sunzida Siddique possesses a diverse skill set that combines technical proficiency with strong interpersonal capabilities. She is well-versed in programming languages such as C, Java, and Python, with a particular focus on AI and Machine Learning applications. Her expertise extends to utilizing frameworks and libraries to develop solutions in deep learning and cybersecurity. In addition to her programming skills, Ms. Siddique is proficient in web development technologies, including HTML5, CSS3, Bootstrap5, and JavaScript. She is also adept at using tools like Microsoft Word, Excel, and PowerPoint, which support her in documentation, data analysis, and presentation tasks. Her multitasking abilities, coupled with strong communication and leadership skills, enable her to collaborate effectively and manage projects efficiently. These skills, along with her commitment to continuous learning, position Ms. Siddique as a highly capable and adaptable professional.

 

Publication Top Noted

Title: Survey on machine learning biases and mitigation techniques

  • Authors: S Siddique, MA Haque, R George, KD Gupta, D Gupta, MJH Faruk
  • Journal: Digital
  • Volume: 4
  • Issue: 1
  • Pages: 1-68
  • Cited by: 9
  • Year: 2023

Title: Machine learning-based model for predicting stress level in online education due to coronavirus pandemic: a case study of Bangladeshi students

  • Authors: S Siddique, S Baidya, MS Rahman
  • Conference: 2021 5th International Conference on Electrical Information and Communication Technology (EICT)
  • Cited by: 8
  • Year: 2021

Title: Cyber Security issues in the industrial applications of digital twins

  • Authors: S Siddique, MA Haque, RH Rifat, R George, K Shujaee, KD Gupta
  • Conference: 2023 IEEE Symposium Series on Computational Intelligence (SSCI)
  • Pages: 873-878
  • Cited by: 4
  • Year: 2023

Title: Challenges and opportunities of computational intelligence in industrial control system (ICS)

  • Authors: S Siddique, MA Haque, RH Rifat, LR Das, S Talukder, SB Alam, KD Gupta
  • Conference: 2023 IEEE Symposium Series on Computational Intelligence (SSCI)
  • Pages: 1158-1163
  • Cited by: 2
  • Year: 2023

Title: Deep Learning Modeling for Gourd Species Recognition Using VGG-16

  • Authors: MM Hasan, K Alam, S Siddique, TA Topu, MT Habib, MS Uddin
  • Book: Computer Vision and Machine Learning in Agriculture, Volume 3
  • Pages: 19-35
  • Cited by: 2
  • Year: 2023

Title: Computer Vision and Machine Learning in Agriculture, Volume 3

  • Authors: JC Bansal, MS Uddin
  • Publisher: Springer Verlag, Singapore
  • Cited by: 2
  • Year: 2023

Title: People Thoughts Prediction using Machine Learning on Women’s Contribution in ICT in Bangladesh

  • Authors: S Akter, S Siddique, I Jahan, T Rabeya, MR Mim
  • Conference: 2021 IEEE 6th International Conference on Computing, Communication and Networking Technologies (ICCCNT)
  • Cited by: 1
  • Year: 2021

Conclusion

Ms. Sunzida Siddique’s strong academic foundation, her contribution to innovative research projects, and her leadership in organizing and mentoring within technical clubs make her an exceptional candidate for the Research for Best Researcher Award. Her work in AI, machine learning, and other emerging technologies, combined with her enthusiasm for continuous learning, underscores her potential to make significant strides in her field.

Wanchang Zhang | Malware Analysis | Best Researcher Award

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Prof.Dr. Wanchang Zhang | Malware Analysis | Best Researcher Award

Earth System Science at Aerospace Information Research Institute/Chinese Academy of Sciences, China

Prof. Dr. Wanchang Zhang is a distinguished expert in Earth System Science, specializing in remote sensing and GIS applications for ecology, hydrology, water resources, climate change, and disaster mitigation. He is a Professor and Ph.D. Supervisor at the Aerospace Information Research Institute, Chinese Academy of Sciences (CAS), and an awardee of the prestigious “Hundred Talents Program.” With over 400 academic publications, including 270 indexed in SCI/EI, and numerous highly cited works, Dr. Zhang’s research has achieved global recognition. He has developed advanced hydrological and environmental simulation systems and holds 10 national invention patents and 14 software copyrights. Dr. Zhang also serves as Vice Director of the CAS-TWAS Center of Excellence on Space Technology for Disaster Mitigation, showcasing his leadership in addressing critical global challenges.

 

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Education

Prof. Dr. Wanchang Zhang holds a Ph.D. in Earth System Science, reflecting his deep expertise in understanding and addressing complex interactions within natural and human systems. His educational foundation has been instrumental in his significant contributions to fields such as remote sensing, hydrology, and global climate studies. Through rigorous academic training and extensive research, Dr. Zhang has developed innovative approaches and technologies that have propelled advancements in disaster mitigation, environmental monitoring, and water resource management.

Experience

Prof. Dr. Wanchang Zhang is a distinguished Professor and Ph.D. Supervisor at the Aerospace Information Research Institute, Chinese Academy of Sciences (CAS), and Vice Director of the CAS-TWAS Center of Excellence on Space Technology for Disaster Mitigation. With extensive academic positions at Nagoya University, Nanjing University, and the Institute of Atmospheric Physics at CAS, he has pioneered research in hydrology, water resources, climate change, and disaster risk mitigation. Dr. Zhang has developed advanced simulation systems and software for monitoring and managing environmental and geological disasters, solidifying his reputation as a leader in Earth System Science and GIS applications.

Research Interests

Prof. Dr. Wanchang Zhang’s research interests lie at the intersection of Earth System Science and advanced remote sensing technologies. His work spans diverse domains, including the study of hydrological processes, water resource management, and water environment simulation systems. He is deeply involved in understanding global climate change and its impacts, as well as developing methodologies for disaster risk assessment and mitigation. Dr. Zhang’s expertise extends to creating innovative models for monitoring and early warning of geological hazards, droughts, and floods, leveraging GIS and remote sensing tools. His research also addresses pressing global challenges in ecology and environmental sustainability, showcasing a commitment to using science and technology to mitigate disasters and enhance resilience.

Skills

Prof. Dr. Wanchang Zhang possesses a comprehensive skill set in advanced Earth System Science research, with a strong emphasis on remote sensing and GIS applications. He is adept at developing and implementing distributed hydrology and water resource simulation systems, including the ESSI-I, II, and III models. His expertise extends to designing practical tools and software for risk assessment, environmental monitoring, and disaster early warning systems. Dr. Zhang is skilled in conducting interdisciplinary research that integrates hydrology, ecology, and climate change studies. Additionally, his proficiency in academic writing and publishing is reflected in his extensive record of SCI/EI-indexed papers, patents, and highly cited research. His technical and managerial capabilities also include leading collaborative projects, supervising Ph.D. candidates, and contributing to global academic and professional communities.

Awards

Prof. Dr. Wanchang Zhang has received numerous accolades in recognition of his exceptional contributions to Earth System Science and remote sensing applications. He was honored as an awardee of the prestigious “Hundred Talents Program” by the Chinese Academy of Sciences (CAS), highlighting his status as a leading expert in his field. His groundbreaking research has earned him five awards for papers published in esteemed international and domestic journals or presented at conferences. Additionally, several of his publications are acknowledged as highly cited works in the ESI database and domestic journals, underscoring their significant impact on the scientific community. Dr. Zhang’s innovative contributions are further evidenced by 10 national invention patents and 14 software copyrights, showcasing his pivotal role in advancing technology and scientific knowledge.

 

Publication Top Noted

Title: Semantic segmentation of urban buildings from VHR remote sensing imagery using a deep convolutional neural network

  • Authors: Y Yi, Z Zhang, W Zhang, C Zhang, W Li, T Zhao
  • Journal: Remote Sensing
  • Volume: 11
  • Issue: 15
  • Article Number: 1774
  • Cited by: 227
  • Year: 2019

Title: Landslide susceptibility mapping using multiscale sampling strategy and convolutional neural network: A case study in Jiuzhaigou region

  • Authors: Y Yi, Z Zhang, W Zhang, H Jia, J Zhang
  • Journal: Catena
  • Volume: 195
  • Article Number: 104851
  • Cited by: 181
  • Year: 2020

Title: Assessment of water quality and identification of polluted risky regions based on field observations & GIS in the Honghe River Watershed, China

  • Authors: CA Yan, W Zhang, Z Zhang, Y Liu, C Deng, N Nie
  • Journal: PloS One
  • Volume: 10
  • Issue: 3
  • Article Number: e0119130
  • Cited by: 178
  • Year: 2015

Title: Mapping favorable groundwater potential recharge zones using a GIS-based analytical hierarchical process and probability frequency ratio model: A case study from an agro-urban area

  • Authors: A Arshad, Z Zhang, W Zhang, A Dilawar
  • Journal: Geoscience Frontiers
  • Volume: 11
  • Issue: 5
  • Pages: 1805-1819
  • Cited by: 161
  • Year: 2020

Title: 基于 GIS 的空间插值方法研究 (Spatial interpolation method based on GIS)

  • Authors: 朱求安 (Zhu Qiunan), 张万昌 (Zhang Wanchang), 余钧辉 (Yu Junhui)
  • Journal: 江西师范大学学报: 自然科学版 (Journal of Jiangxi Normal University: Natural Science Edition)
  • Volume: 28
  • Issue: 2
  • Pages: 183-188
  • Cited by: 144
  • Year: 2004

Title: A simple empirical topographic correction method for ETM+ imagery

  • Authors: Y Gao, W Zhang
  • Journal: International Journal of Remote Sensing
  • Volume: 30
  • Issue: 9
  • Pages: 2259-2275
  • Cited by: 143
  • Year: 2009

Conclusion

Dr. Wanchang Zhang’s groundbreaking research, prolific publication record, and technological innovations make him a strong contender for the Best Researcher Award. His contributions to Earth System Science and disaster mitigation have not only enriched academic understanding but also provided practical solutions to pressing global challenges.

Jacob Kwaku Nkrumah | Detection and Prevention | Best Researcher Award

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Dr. Jacob Kwaku Nkrumah | Detection and Prevention | Best Researcher Award

Ph.D student at Jiangsu University, Zhenjiang, China

Dr. Jacob Kwaku Nkrumah is a dedicated academic and researcher specializing in automotive and mechanical engineering. He is currently pursuing a Ph.D. in Vehicle Engineering at Jiangsu University, China, with anticipated completion in December 2024. Dr. Nkrumah holds advanced degrees, including an MPhil in Automotive Engineering and Technology and an M-Tech in Mechanical Engineering Education, complemented by a robust background in teaching and curriculum development. His research focuses on automotive safety systems, innovative engineering solutions, and materials science, with multiple publications in esteemed journals. Dr. Nkrumah’s professional experience includes roles as a lecturer at Tamale Technical University and as a teacher in Ghana’s education system, showcasing his passion for knowledge dissemination and academic excellence.

 

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Education

Dr. Jacob Kwaku Nkrumah has an impressive educational background that highlights his dedication to advancing his expertise in mechanical and automotive engineering. He is currently pursuing a Ph.D. in Vehicle Engineering at Jiangsu University, Zhenjiang, China, with completion expected in December 2024. He holds an MPhil in Automotive Engineering and Technology (2021) and an M-Tech in Mechanical Engineering Education (2014), both from the University of Education, Winneba, Ghana. In addition, he earned a Diploma in Education from the same institution in 2016. Dr. Nkrumah further strengthened his technical foundation with a B-Tech in Automobile Engineering (2011) from Kwame Nkrumah University of Science and Technology, Kumasi, Ghana, and an HND in Mechanical Engineering (2003) from Tamale Technical University, Ghana. His academic achievements underscore a strong commitment to research and education in engineering disciplines.

Experience

Dr. Jacob Kwaku Nkrumah has extensive teaching and academic experience that spans nearly two decades, showcasing his dedication to education and engineering. From 2017 to 2021, he served as a lecturer in the Automotive Engineering Department at Tamale Technical University, Ghana, where he taught courses such as Engineering Mathematics, Engineering Science, and Engineering Physics. Prior to this, he worked with the Ghana Education Service, first as a teacher at Krachi Senior High School (2012–2017), where he taught Mathematics and Physics, and earlier at Kogni Junior High School (2004–2016), where he was responsible for teaching Science and Mathematics. Dr. Nkrumah began his professional journey as a National Service Personnel at Debokpa Vocational Institute, Tamale, from 2003 to 2004. His diverse roles have equipped him with strong classroom management, conflict resolution, and curriculum development skills, which reflect his commitment to academic excellence and the advancement of engineering education.

Research Interests

Dr. Jacob Kwaku Nkrumah’s research interests are primarily focused on automotive engineering, vehicle safety systems, and mechanical engineering innovations. His work explores the development and enhancement of automotive technologies, particularly in the areas of intelligent lighting systems, headlight beam intensity control, and sensor-based automatic systems for improved driving safety and efficiency. Dr. Nkrumah is also deeply involved in material science, with research on the modal and thermal analysis of components like the internal combustion engine’s connecting rod. His studies aim to contribute to the advancement of vehicle performance, safety, and energy efficiency, as well as the broader field of mechanical engineering through the application of finite element methods and other engineering simulation techniques.

Skills

Dr. Jacob Kwaku Nkrumah possesses a diverse set of skills that enhance his effectiveness as both an educator and a researcher. He is adept at preparing comprehensive lesson notes and has strong classroom management abilities, ensuring a productive and focused learning environment. His skills in conflict management within the classroom have been key in maintaining harmony and fostering effective student engagement. Additionally, Dr. Nkrumah has significant experience in curriculum development, where he has contributed to shaping educational frameworks to meet modern engineering standards. These skills complement his research expertise and his ability to teach complex engineering concepts effectively, making him a well-rounded academic professional.

Awards

Dr. Jacob Kwaku Nkrumah has earned recognition for his outstanding contributions to the field of automotive and mechanical engineering. His dedication to research and education has led to multiple publications in prestigious journals, highlighting his innovative work in automotive safety systems and mechanical engineering. While specific awards are not listed, Dr. Nkrumah’s academic achievements, including his Ph.D. candidacy and successful research projects, reflect his commitment to advancing knowledge and excellence in engineering. His work continues to garner attention and contributes significantly to the academic community, particularly in the realm of vehicle engineering and safety technologies.

 

Publication Top Noted

Title: Assessing the Skills of Roadside Mechanics in Diagnosing and Fixing Problems of Modern Electronic Managed Vehicles in Ghana (Tamale Metropolis)

  • Authors: B Ziblim, J Nkrumah, I Imoro
  • Journal: American Scientific Research Journal for Engineering, Technology, and …
  • Cited by: 7
  • Year: 2018

Title: The evolution of vehicle pneumatic vibration isolation: A systematic review

  • Authors: VA Atindana, X Xu, AN Nyedeb, JK Quaisie, JK Nkrumah, SP Assam
  • Journal: Shock and Vibration
  • Volume: 2023(1)
  • Article Number: 1716615
  • Cited by: 6
  • Year: 2023

Title: A novel semi-active control of an integrated chassis and seat quasi-zero stiffness suspension system for off-road vehicles

  • Authors: VA Atindana, X Xu, NJ Kwaku, A Akayeti, X Jiang
  • Journal: Journal of Vibration and Control
  • Article Number: 10775463231224835
  • Cited by: 5
  • Year: 2024

Title: Analysis of the material properties of vehicle suspension coil spring

  • Authors: I Imoro, JK Nkrumah, B Ziblim, AH Mohammed
  • Journal: World Journal of Engineering and Technology
  • Volume: 11
  • Issue: 4
  • Pages: 827-858
  • Cited by: 4
  • Year: 2023

Title: Experimental design and optimization of pneumatic low-frequency driver seat for off-road vehicles: quasi-zero negative stiffness and gray wolf optimization algorithm

  • Authors: VA Atindana, X Xu, L Huan, A Nirere, AN Nyedeb, JK Quaisie, NJ Kwaku, …
  • Journal: Journal of the Brazilian Society of Mechanical Sciences and Engineering
  • Volume: 45
  • Cited by: 4
  • Year: 2023

Title: Review of Suspension Control and Simulation of Passive, Semi-Active and Active Suspension Systems Using Quarter Vehicle Model

  • Authors: DIO Jacob Kwaku Nkrumah, Kwabla Sherry Amedorme, Baba Ziblim
  • Journal: American Academic Scientific Research Journal for Engineering, Technology …
  • Cited by: 2
  • Year: 2022

Title: A review of automotive intelligent and adaptive headlight beams intensity control approaches

  • Authors: JK Nkrumah, Y Cai, A Jafaripournimchahi
  • Journal: Advances in Mechanical Engineering
  • Volume: 16
  • Issue: 4
  • Article Number: 16878132231220355
  • Cited by: 1
  • Year: 2024

Conclusion

Dr. Jacob Kwaku Nkrumah exemplifies the qualities of an outstanding researcher. His dedication to advancing automotive safety and efficiency, combined with his academic contributions and educational impact, make him a strong contender for the Best Researcher Award. His work addresses critical challenges in engineering, offering innovative solutions with practical applications, which aligns with the award’s mission to recognize excellence in research.

Jinshuo Liu | Data Mining | Top Researcher Award

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Prof. Jinshuo Liu | Data Mining | Top Researcher Award

Professor at Wuhan University, China

Prof. Jinshuo Liu is a distinguished researcher and educator with over 27 years of experience at Wuhan University, one of China’s top universities. He currently serves as a Professor in the School of Cyber Science and Engineering, where he leads a research group specializing in web mining and data mining. Prof. Liu has supervised numerous students, guiding six Ph.D. and 101 Master’s students in their research. His leadership extends to being the head of the collaboration lab between Wuhan University and the University of Edinburgh, UK. Prof. Liu’s extensive research contributions include over 50 published papers and more than 30 Chinese invention patents. He has led 41 projects, including major initiatives funded by the National Natural Science Foundation of China and the National Key Research and Development Program of China. His research interests are rooted in data mining, high-performance computing, and advancing technological solutions in cybersecurity.

 

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Education

Prof. Jinshuo Liu holds an impressive academic background in computer science, which has been instrumental in shaping his research career. He earned his Ph.D. in Computer Software and Theory from Wuhan University, China, in 2006, building on his foundational knowledge and research skills. Prior to that, he completed a Master’s degree in Computer Science from Leiden University, Netherlands, in 2003, where he further honed his expertise in computing theories and applications. Prof. Liu began his academic journey at Wuhan University, where he obtained his Bachelor’s degree in Computer Science in 1997. His academic pursuits also include international experience as a Visiting Associate Professor at the University of Virginia, USA, in 2017, and as a Visiting Scholar at Konkuk University, Korea, in 2012. These experiences have enriched his global perspective and contributed to his leadership in data mining and high-performance computing.

Experience

Prof. Jinshuo Liu has an extensive professional background, with over 27 years at Wuhan University, one of China’s top universities. Currently, he is a Professor in the School of Cyber Science and Engineering, where he leads a specialized research group in web mining. His leadership extends to an international collaboration lab between Wuhan University and the University of Edinburgh, UK, highlighting his role in fostering global research initiatives. Throughout his career, Prof. Liu has led 41 major projects, including three funded by the National Natural Science Foundation of China and three from the National Key Research and Development Program of China. He has also supervised the academic progress of six Ph.D. students and 101 master’s students. His contributions to the field are further underscored by his impressive record of over 50 publications and more than 30 invention patents, which reflect his commitment to advancing research in data mining and high-performance computing.

Research Interests

Prof. Jinshuo Liu’s research interests are centered on data mining and high-performance computing, with a focus on cutting-edge challenges in web mining and information processing. His work involves developing advanced techniques to address complex issues in identity disambiguation, network security, and critical information dissemination within cyberspace. Leading research at the intersection of computing theory and practical application, Prof. Liu also collaborates internationally to explore topics such as entity identification, public opinion monitoring, and efficient parallel computation for large-scale Earth system models. His research aims to innovate solutions for high-impact applications in both cybersecurity and the analysis of large data sets.

Skills

Prof. Jinshuo Liu possesses a robust skill set in advanced data mining, high-performance computing, and cybersecurity. His expertise includes web mining, identity disambiguation, and malicious information tracing, utilizing cutting-edge algorithms and frameworks for efficient data processing. He is highly skilled in developing and applying high-efficiency identification and recovery methods, particularly in areas involving network supervision and public opinion analysis. With significant experience leading national projects, Prof. Liu is adept at managing complex research collaborations, including his leadership role in a collaborative lab between Wuhan University and the University of Edinburgh. His skills extend to fostering innovation in computational methods for large-scale Earth system models, making significant contributions to both national and international projects.

Awards

Prof. Jinshuo Liu has received several prestigious awards in recognition of his contributions to research and technology. Notably, he was honored with the China Earthquake Administration Scientific and Technological Achievement Award for Earthquake Prevention and Disaster Reduction, receiving the 2nd Class Award in 2017. In the same year, he was awarded the China State Grid Science and Technology Progress Award, earning the 3rd Prize. These accolades highlight his significant contributions to both the advancement of scientific knowledge and practical applications in critical fields, including cybersecurity and disaster management. Prof. Liu’s recognition underscores his leadership and innovative contributions to technology and research.

 

Publication Top Noted

Title: Collaborate SLM and LLM with latent answers for event detection

  • Authors: Yan, Y., Liu, J., Ji, D., Wang, X., Pan, J.Z.
  • Journal: Knowledge-Based Systems
  • Volume: 305
  • Article Number: 112684
  • Year: 2024
  • Citations: 0

Title: Construction of Disaster Event Evolutionary Graph Based on Spatiotemporal Relationship

  • Authors: Ning, H., Sui, H., Wang, J., Liu, J.
  • Journal: Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University
  • Volume: 49
  • Issue: 5
  • Pages: 831–843
  • Year: 2024
  • Citations: 1

Title: Knowledge-Enhanced Prompt Learning for Few-Shot Text Classification

  • Authors: Liu, J., Yang, L.
  • Journal: Big Data and Cognitive Computing
  • Volume: 8
  • Issue: 4
  • Article Number: 43
  • Year: 2024
  • Citations: 0

Title: Intelligent load balancing in data center software-defined networks

  • Authors: Gilliard, E., Liu, J., Aliyu, A.A., Jing, H., Wang, M.
  • Journal: Transactions on Emerging Telecommunications Technologies
  • Volume: 35
  • Issue: 4
  • Article Number: e4967
  • Year: 2024
  • Citations: 0

Title: Knowledge graph reasoning for cyber attack detection

  • Authors: Gilliard, E., Liu, J., Aliyu, A.A.
  • Journal: IET Communications
  • Volume: 18
  • Issue: 4
  • Pages: 297–308
  • Year: 2024
  • Citations: 2

Title: Inhomogeneous Interest Modeling via Hypergraph Convolutional Networks for Social Recommendation

  • Authors: Luo, L., Wang, M., Liu, J., Huang, J.
  • Conference: Proceedings of the International Joint Conference on Neural Networks
  • Year: 2024
  • Citations: 0
  • Title: Content-Biased and Style-Assisted Transfer Network for Cross-Scene Hyperspectral Image Classification
  • Authors: Shi, Z., Lai, X., Deng, J., Liu, J.

Title: An efficient blockchain-based approach to improve the accuracy of intrusion detection systems

  • Authors: Abubakar, A.A., Liu, J., Gilliard, E.
  • Journal: Electronics Letters
  • Volume: 59
  • Issue: 18
  • Article Number: e12888
  • Year: 2023
  • Citations: 2

Conclusion

Prof. Jinshuo Liu’s career reflects a commitment to pioneering research, impactful mentorship, and substantial contributions to technology and society. His leadership in national and collaborative projects, international research ties, numerous publications, and innovation patents underscore his status as a top researcher. Prof. Liu is well-suited for the Top Researcher Award, given his groundbreaking achievements in data mining, high-performance computing, and digital security advancements.