Takeshi Nikawa | Biochemistry | Research Excellence Award

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Prof. Dr. Takeshi Nikawa | Biochemistry | Research Excellence Award

Tokushima University Graduate School | Japan

Prof. Dr. Takeshi Nikawa is a distinguished researcher at Tokushima University, Japan, with expertise in skeletal muscle physiology, molecular biology, and nutritional interventions. His research explores the mechanisms underlying muscle atrophy, mitochondrial function, and gene regulation during myogenesis, aiming to understand how these processes impact aging, metabolism, and overall health. Nikawa’s work integrates experimental studies with translational approaches to develop strategies for maintaining muscle mass and function, particularly in aging populations or individuals at risk of muscle degeneration. He actively collaborates with international scientists across multiple disciplines, fostering knowledge exchange and advancing global research initiatives. Through his publications and applied studies, Nikawa contributes to both fundamental scientific understanding and practical interventions, supporting the development of therapeutic, nutritional, and lifestyle strategies that enhance quality of life and address key societal challenges related to health and aging.

Citation Metrics (Scopus)

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Featured Publications

CHENGZU DONG | Computer Science | Best Researcher Award

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Prof . CHENGZU DONG | Computer Science | Best Researcher Award

Assistant Professor at Lingnan University , Hong Kong

Dr. Chengzu Dong is a highly accomplished early-career researcher specializing in cybersecurity, AI, blockchain, IoT, UAVs, and edge computing. Currently an Assistant Professor at Lingnan University, he has published over 30 peer-reviewed papers in prestigious Q1 journals and Core A/A* conferences, showcasing his strong research productivity and interdisciplinary expertise. His collaborations with CSIRO and industry partners reflect a robust blend of academic rigor and applied impact. Dr. Dong has received multiple accolades, including best paper awards, hackathon honors, and scholarships, highlighting his innovation and leadership potential. In addition to research, he has made significant contributions to teaching, mentoring, and curriculum development across several international institutions. While he could further enhance his profile through principal investigator roles and broader international visibility, his achievements and contributions make him a strong candidate for the Best Researcher Award, particularly in emerging areas of intelligent systems, secure computing, and next-generation network technologies.

Professional Profile 

Education🎓

Dr. Chengzu Dong has a strong and diverse educational background in computer science and information technology. He earned his Ph.D. from Deakin University, Australia, specializing in blockchain, AI, UAVs, edge computing, IoT, Web3, and the Metaverse. During his Ph.D. studies (2021–2024), he conducted extensive research in next-generation technologies, contributing significantly to academic and applied fields. Prior to that, he completed a Bachelor of Computer Science (Honours) at Swinburne University of Technology in 2020, where he deepened his expertise in software development and systems engineering. He also holds a Bachelor of Information Technology from Deakin University (2016–2019), which laid the foundation for his interests in cybersecurity and emerging technologies. His education reflects a consistent focus on interdisciplinary innovation and a strong grounding in both theoretical knowledge and practical applications. Dr. Dong’s academic journey across top Australian universities has prepared him well for a career in high-impact, technology-driven research and teaching.

Professional Experience📝

Dr. Chengzu Dong brings a rich and diverse professional background in academia, research, and industry. He is currently serving as an Assistant Professor at Lingnan University, Hong Kong, where he teaches and develops courses in blockchain, data mining, machine learning, and cybersecurity. Prior to this, he held multiple academic roles at Deakin University, including seminar lecturer, academic tutor, course developer, and capstone mentor, contributing significantly to curriculum innovation and student mentorship. His research experience includes collaborations with CSIRO, Australia’s leading scientific agency, where he worked on blockchain and AI projects. He also held positions as a research assistant at Swinburne University and Deakin University, and worked in software development roles at Artchain Global, Creative Geelong, and FPT Software. These roles highlight his strong technical skills and ability to bridge academia and industry. Dr. Dong’s professional journey reflects a well-rounded portfolio of teaching, research, and applied innovation in emerging technologies.

Research Interest🔎

Dr. Chengzu Dong’s research interests lie at the intersection of emerging technologies and intelligent systems, with a strong focus on cybersecurity, blockchain, artificial intelligence (AI), Internet of Things (IoT), unmanned aerial vehicles (UAVs), edge computing, Web3, and the Metaverse. His work aims to address critical challenges in data privacy, secure communication, and decentralized systems through the integration of blockchain and federated learning frameworks. He is particularly passionate about developing secure and efficient architectures for UAV delivery systems and smart edge networks, making his research highly relevant to real-world applications. Dr. Dong’s interdisciplinary approach combines theoretical advancements with practical implementations, as demonstrated by his collaborations with CSIRO and numerous industry partners. His contributions not only advance academic knowledge but also provide innovative solutions to pressing technological issues in digital security and autonomous systems. This diverse and forward-looking research portfolio positions him as a thought leader in next-generation computing and intelligent infrastructure.

Award and Honor🏆

Dr. Chengzu Dong has received numerous awards and honors in recognition of his academic excellence, research impact, and innovative contributions to emerging technologies. He was the recipient of the prestigious Deakin University Postgraduate Research Scholarship and a CSIRO Top-up Scholarship, supporting his advanced research in blockchain and AI. His work has earned best paper awards at international conferences such as IEEE IAS GLOBCONHT 2023, and he has achieved first runner-up prizes in blockchain hackathons in both Thailand and Australia. Dr. Dong is a certified member of the Australian Computer Society and holds various professional certifications, including Cisco CCNET and Certificate IV in Training and Assessment. His academic excellence was further recognized with the Golden Key Top 15% Student Award. He has also received recognition as a journal and conference reviewer, including a free ACM membership. These accolades collectively highlight his leadership, innovation, and dedication to research excellence and professional development.

Research Skill🔬

Dr. Chengzu Dong possesses a comprehensive set of research skills that span theoretical development, applied experimentation, and interdisciplinary collaboration. He is highly proficient in blockchain technology, artificial intelligence, federated learning, and cybersecurity frameworks, with a particular focus on secure systems for UAVs and edge computing environments. Dr. Dong demonstrates strong technical expertise in programming languages such as Python, Node.js, and React, along with experience in data analytics, machine learning model development, and system architecture design. His ability to design privacy-preserving frameworks and implement decentralized solutions reflects his strength in combining research theory with practical outcomes. Additionally, his experience working with organizations like CSIRO showcases his capability to collaborate on large-scale, real-world projects. Dr. Dong is also skilled in academic writing and publishing, with over 30 high-quality publications in top-tier journals and conferences. His strong analytical mindset, problem-solving ability, and innovation make him a highly capable and impactful researcher in advanced computing domains.

Conclusion💡

Dr. Chengzu Dong exemplifies the qualities of an outstanding researcher and academic, making him a highly suitable candidate for the Best Researcher Award. His extensive contributions to cutting-edge areas such as blockchain, AI, cybersecurity, and UAV systems reflect both depth and breadth in research expertise. With over 30 high-impact publications, multiple international awards, and active collaborations with renowned institutions like CSIRO, Dr. Dong has demonstrated consistent research excellence and innovation. His ability to translate theoretical knowledge into practical solutions for real-world challenges, especially in emerging technologies, underscores his relevance and leadership in the field. Additionally, his dedication to teaching and mentoring at multiple universities enhances his influence in shaping future researchers and professionals. Dr. Dong’s interdisciplinary skills, academic achievements, and forward-thinking research agenda not only position him as a leader in his domain but also affirm his deserving candidacy for this prestigious recognition.

Publications Top Noted✍

  • Title: BBM: A Blockchain-Based Model for Open Banking via Self-Sovereign Identity
    Authors: C. Dong, Z. Wang, S. Chen, Y. Xiang
    Year: 2020
    Citations: 32

  • Title: A Novel Security Framework for Edge Computing Based UAV Delivery System
    Authors: A. Yao, F. Jiang, X. Li, C. Dong, Y.X. Jia, X.L. Gang Li
    Year: 2021
    Citations: 28

  • Title: Enhancing Quality of Service Through Federated Learning in Edge-Cloud Architecture
    Authors: J. Zhou, S. Pal, C. Dong, K. Wang
    Year: 2024
    Citations: 22

  • Title: A Blockchain-Aided Self-Sovereign Identity Framework for Edge-Based UAV Delivery System
    Authors: C. Dong, F. Jiang, X. Li, A. Yao, G. Li, X. Liu
    Year: 2021
    Citations: 20

  • Title: Optimizing Performance in Federated Person Re-Identification Through Benchmark Evaluation for Blockchain-Integrated Smart UAV Delivery Systems
    Authors: C. Dong, J. Zhou, Q. An, F. Jiang, S. Chen, L. Pan, X. Liu
    Year: 2023
    Citations: 15

  • Title: Continuous Authentication for UAV Delivery Systems Under Zero-Trust Security Framework
    Authors: C. Dong, F. Jiang, S. Chen, X. Liu
    Year: 2022
    Citations: 15

  • Title: A Privacy-Preserving Location Data Collection Framework for Intelligent Systems in Edge Computing
    Authors: A. Yao, S. Pal, X. Li, Z. Zhang, C. Dong, F. Jiang, X. Liu
    Year: 2024
    Citations: 11

  • Title: A Framework for User Biometric Privacy Protection in UAV Delivery Systems with Edge Computing
    Authors: A. Yao, S. Pal, C. Dong, X. Li, X. Liu
    Year: 2024
    Citations: 11

Hossein Nematzadeh | Computer Science | Best Researcher Award

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Dr. Hossein Nematzadeh | Computer Science | Best Researcher Award

Assist Prof at Universidad de Malaga, Spain

Dr. Hossein Nematzadeh is an accomplished researcher and academic with a Ph.D. in Computer Science from the University of Technology, Malaysia. He is currently an Assistant Professor at the Modern College of Business and Science in Oman, with prior experience as a researcher at Universidad de Málaga, Spain, and an assistant professor at Islamic Azad University, Iran. His research interests span Data Science, Artificial Intelligence, Cryptography, and Software Engineering, with a particular focus on explainable AI, feature selection, evolutionary algorithms, and image encryption. Dr. Nematzadeh has published extensively in high-impact journals, contributing to advancements in AI and machine learning. He is also an experienced educator, having taught a wide array of computer science courses at various academic levels. With expertise in technologies like Python, MATLAB, and AWS, he is committed to both advancing research and mentoring the next generation of computer scientists.

Professional Profile 

Education

Dr. Hossein Nematzadeh has a strong academic foundation in Computer Science, having completed his Ph.D. at the University of Technology, Malaysia in 2014. Prior to his doctoral studies, he earned his Master’s degree from the same institution in 2009, further solidifying his expertise in the field. Dr. Nematzadeh also holds a Bachelor’s degree from Mazandaran University of Science and Technology, obtained in 2007. His educational journey reflects a deep commitment to the study of computer science, particularly in areas such as Artificial Intelligence, Data Science, and Cryptography. Throughout his academic career, he has gained a robust understanding of both theoretical and practical aspects of the field, which has informed his subsequent research and teaching. This solid educational background, combined with his ongoing research contributions, enables him to be a leader in his academic and professional endeavors.

Professional Experience

Dr. Hossein Nematzadeh has extensive professional experience in academia and research. He is currently serving as an Assistant Professor at the Modern College of Business and Science in Oman, where he teaches and supervises students in the field of Computer Science. Prior to this role, he was a researcher at Universidad de Málaga in Spain from 2021 to 2024, contributing to several high-impact research projects in Artificial Intelligence and Data Science. From 2012 to 2021, he served as an Assistant Professor at Islamic Azad University in Iran, where he taught various computer science courses and engaged in research activities. Throughout his career, Dr. Nematzadeh has built a reputation as both an educator and a researcher, publishing extensively in leading journals and presenting his work in international forums. His expertise spans across Data Science, Artificial Intelligence, and Cryptography, making him a prominent figure in these fields.

Research Interest

Dr. Hossein Nematzadeh’s research interests lie at the intersection of Data Science, Artificial Intelligence, Cryptography, and Software Engineering. He is particularly focused on developing advanced techniques in explainable AI, feature selection, and noise detection, with an emphasis on making AI models more interpretable and reliable. His work in evolutionary algorithms and fuzzy logic explores ways to optimize decision-making processes and improve system performance. Dr. Nematzadeh is also passionate about cryptography, specifically in areas such as image encryption, which contributes to enhancing data security in digital environments. Additionally, he has a strong interest in software engineering, with research dedicated to verification and validation processes, as well as the application of Petri nets to model and analyze complex systems. His research aims to push the boundaries of AI and machine learning, providing solutions to both theoretical and practical challenges in these rapidly evolving fields.

Award and Honor

Dr. Hossein Nematzadeh has earned recognition for his contributions to research and academia throughout his career. He has received several honors for his work in the fields of Data Science, Artificial Intelligence, and Cryptography, particularly for his research on explainable AI and feature selection methods. Dr. Nematzadeh’s scholarly impact is reflected in his publications in prestigious journals such as Engineering Applications of Artificial Intelligence and Knowledge-Based Systems. His work has been widely cited, demonstrating the influence of his research on the scientific community. In addition to his academic accomplishments, Dr. Nematzadeh has been actively involved in mentoring students and contributing to the advancement of his field through teaching and supervision. His dedication to fostering new talent in Computer Science and his continuous pursuit of research excellence have earned him respect within academic circles, making him a highly regarded figure in the global academic and research community.

Publications Top Noted

  • Title: Medical image encryption using a hybrid model of modified genetic algorithm and coupled map lattices
    Authors: H Nematzadeh, R Enayatifar, H Motameni, FG Guimarães, VN Coelho
    Year: 2018
    Cited by: 157
  • Title: A hybrid feature selection method based on information theory and binary butterfly optimization algorithm
    Authors: Z Sadeghian, E Akbari, H Nematzadeh
    Year: 2021
    Cited by: 116
  • Title: Heuristic filter feature selection methods for medical datasets
    Authors: M Alirezanejad, R Enayatifar, H Motameni, H Nematzadeh
    Year: 2020
    Cited by: 78
  • Title: Binary search tree image encryption with DNA
    Authors: H Nematzadeh, R Enayatifar, M Yadollahi, M Lee, G Jeong
    Year: 2020
    Cited by: 72
  • Title: Frequency based feature selection method using whale algorithm
    Authors: H Nematzadeh, R Enayatifar, M Mahmud, E Akbari
    Year: 2019
    Cited by: 66
  • Title: Emergency role-based access control (E-RBAC) and analysis of model specifications with alloy
    Authors: F Nazerian, H Motameni, H Nematzadeh
    Year: 2019
    Cited by: 52
  • Title: Predicting air pollution in Tehran: Genetic algorithm and back propagation neural network
    Authors: M Asghari, H Nematzadeh
    Year: 2016
    Cited by: 51
  • Title: A novel image security technique based on nucleic acid concepts
    Authors: M Yadollahi, R Enayatifar, H Nematzadeh, M Lee, JY Choi
    Year: 2020
    Cited by: 33
  • Title: Mapping to convert activity diagram in fuzzy UML to fuzzy petri net
    Authors: H Motameni, A Movaghar, I Daneshfar, H Nemat Zadeh, J Bakhshi
    Year: 2008
    Cited by: 30
  • Title: Automatic ensemble feature selection using fast non-dominated sorting
    Authors: S Abasabadi, H Nematzadeh, H Motameni, E Akbari
    Year: 2021
    Cited by: 28
  • Title: A mixed solution-based high agreement filtering method for class noise detection in binary classification
    Authors: M Samami, E Akbari, M Abdar, P Plawiak, H Nematzadeh, ME Basiri, …
    Year: 2020
    Cited by: 24
  • Title: Comparison of Decision Tree Methods in Classification of Researcher’s Cognitive Styles in Academic Environment
    Authors: ZN Balagatabi, R Ibrahim, HN Balagatabi
    Year: 2015
    Cited by: 24

Nunzio Alberto Borghese | Computer Science | Best Researcher Award

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Prof. Nunzio Alberto Borghese | Computer Science | Best Researcher Award

Full professor at Università degli Studi di MIlano, Italy

Professor N. Alberto Borghese is a renowned researcher in computational intelligence and its application to real-world problems. He graduated magna cum laude in Electrical Engineering from Politecnico di Milan and has held significant academic positions, including Full Professor at the University of Milan. His research focuses on innovative methods such as multi-scale hierarchical neural networks, adaptive clustering, and statistical data processing, with particular emphasis on limited processing time. He has made notable contributions to e-Health and robotics, integrating AI, service robots, virtual communities, and smart objects to improve healthcare and welfare systems. With over 90 journal papers, 140+ conference papers, and 16 international patents, he has a strong academic and industrial impact. He has led several high-profile projects funded by the European Commission and Italian government, including REWIRE, MOVECARE, and AIRCA. His work continues to advance the intersection of AI, robotics, and healthcare, addressing critical societal needs.

Professional Profile 

Education

Professor N. Alberto Borghese received his education in Electrical Engineering, graduating magna cum laude in 1986 from Politecnico di Milan, one of Italy’s leading institutions. This strong academic foundation laid the groundwork for his extensive research career. His academic journey furthered through his role as a tenured researcher at the National Research Council (CNR) from 1987 to 2000, where he began developing his expertise in computational intelligence. This led to his appointment as an Associate and later Full Professor at the Department of Computer Science, University of Milan (UNIMI). At UNIMI, he also directs the Laboratory of Applied Intelligent Systems, where he has mentored students and led cutting-edge research projects. Professor Borghese’s education and professional development have been marked by continuous innovation, research leadership, and a commitment to applying his knowledge to real-world challenges, particularly in e-Health, robotics, and AI.

Professional Experience

Professor N. Alberto Borghese has had a distinguished professional career, beginning as a tenured researcher at the National Research Council (CNR) from 1987 to 2000. During this time, he built a strong foundation in computational intelligence. He then transitioned to the University of Milan (UNIMI), where he became an Associate Professor and later a Full Professor in the Department of Computer Science. At UNIMI, he also directs the Laboratory of Applied Intelligent Systems, where he leads innovative research projects focused on AI, robotics, and e-Health. Throughout his career, he has contributed to over 90 journal papers, more than 140 conference papers, and holds 16 international patents. Professor Borghese has led several major research projects funded by the European Commission, including REWIRE, MOVECARE, and FITREHAB, and has been involved in multiple Italian government-funded initiatives. His work bridges academia and industry, addressing pressing societal needs in healthcare and welfare through technological advancements.

Research Interest

Professor N. Alberto Borghese’s research interests lie primarily in the field of computational intelligence, focusing on the development and application of advanced algorithms to solve real-world problems. He specializes in multi-scale hierarchical neural networks, adaptive clustering, and statistical data processing, with an emphasis on optimizing solutions for limited processing time. His work extends to the integration of Artificial Intelligence (AI) and robotics, particularly in the domains of e-Health and e-Welfare. Professor Borghese has pioneered the use of service robots, virtual communities, and smart objects, creating innovative platforms that enhance healthcare and welfare systems. His research also explores the intersection of AI with healthcare technologies such as exer-games, aiming to improve accessibility and promote well-being. Additionally, he has a strong focus on interdisciplinary collaboration, leading several European and Italian research projects that combine AI, robotics, and human-centered design to address societal challenges in health, aging, and rehabilitation.

Award and Honor

Professor N. Alberto Borghese has received numerous awards and honors throughout his distinguished academic and research career. His recognition stems from his innovative contributions to computational intelligence, AI, and robotics, particularly in the fields of e-Health and e-Welfare. With over 90 journal papers and 140+ conference papers, his research has garnered widespread acclaim, reflected in his h-index of 42. He has also been honored for his extensive intellectual property contributions, holding 16 international patents. His leadership in research has been recognized through his involvement in high-profile projects funded by the European Commission and Italian government, such as REWIRE (FP7), MOVECARE (H2020), and AIRCA (2023-2025). These honors not only underline his academic excellence but also highlight his impact on advancing technology in healthcare and welfare systems. His continued success in securing major funding and his role in shaping interdisciplinary research make him a highly respected figure in his field.

Conclusion

Based on his exceptional academic qualifications, pioneering research in computational intelligence and e-Health, leadership in high-profile projects, and impressive publication and patent record, N. Alberto Borghese is a highly suitable candidate for the Best Researcher Award. Addressing minor improvements in public engagement and cross-disciplinary impact could further strengthen his candidacy. Nonetheless, his proven expertise and contributions make him a deserving nominee.

Publications Top Noted

  • Kinematic determinants of human locomotion
    • Authors: N. Alberto Borghese, L. Bianchi, F. Lacquaniti
    • Year: 1996
    • Citations: 553
  • Different brain correlates for watching real and virtual hand actions
    • Authors: D. Perani, F. Fazio, N. A. Borghese, M. Tettamanti, S. Ferrari, J. Decety, …
    • Year: 2001
    • Citations: 402
  • Autocalibration of MEMS accelerometers
    • Authors: I. Frosio, F. Pedersini, N. A. Borghese
    • Year: 2008
    • Citations: 261
  • Time-varying mechanical behavior of multijointed arm in man
    • Authors: F. Lacquaniti, M. Carrozzo, N. A. Borghese
    • Year: 1993
    • Citations: 202
  • Internal models of limb geometry in the control of hand compliance
    • Authors: F. Lacquaniti, N. A. Borghese, M. Carrozzo
    • Year: 1992
    • Citations: 197
  • Reading the reading brain: a new meta-analysis of functional imaging data on reading
    • Authors: I. Cattinelli, N. A. Borghese, M. Gallucci, E. Paulesu
    • Year: 2013
    • Citations: 188
  • A functional-anatomical model for lipreading
    • Authors: E. Paulesu, D. Perani, V. Blasi, G. Silani, N. A. Borghese, U. De Giovanni, …
    • Year: 2003
    • Citations: 163
  • The role of vision in tuning anticipatory motor responses of the limbs
    • Authors: F. Lacquaniti
    • Year: 1993
    • Citations: 151
  • Exergaming and rehabilitation: A methodology for the design of effective and safe therapeutic exergames
    • Authors: M. Pirovano, E. Surer, R. Mainetti, P. L. Lanzi, N. A. Borghese
    • Year: 2016
    • Citations: 148
  • Self-adaptive games for rehabilitation at home
    • Authors: M. Pirovano, R. Mainetti, G. Baud-Bovy, P. L. Lanzi, N. A. Borghese
    • Year: 2012
    • Citations: 146
  • Transient reversal of the stretch reflex in human arm muscles
    • Authors: F. Lacquaniti, N. A. Borghese, M. Carrozzo
    • Year: 1991
    • Citations: 144
  • Computational intelligence and game design for effective at-home stroke rehabilitation
    • Authors: N. A. Borghese, M. Pirovano, P. L. Lanzi, S. Wüest, E. D. de Bruin
    • Year: 2013
    • Citations: 139
  • Automatic detection of powdery mildew on grapevine leaves by image analysis: Optimal view-angle range to increase the sensitivity
    • Authors: R. Oberti, M. Marchi, P. Tirelli, A. Calcante, M. Iriti, A. N. Borghese
    • Year: 2014
    • Citations: 128
  • Usability and effects of an exergame-based balance training program
    • Authors: S. Wüest, N. A. Borghese, M. Pirovano, R. Mainetti, R. van de Langenberg, …
    • Year: 2014
    • Citations: 121
  • Pattern recognition in 3D automatic human motion analysis
    • Authors: G. Ferrigno, N. A. Borghese, A. Pedotti
    • Year: 1990
    • Citations: 121

Sayyed Ahmed | Computer Science | Best Scholar Award

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Mr. Sayyed Ahmed | Computer Science | Best Scholar Award

Assistant Professor of  Aligarh Muslim University, India

Dr. Sayyed Usman Ahmed is a dedicated academic and researcher in the field of computer engineering, specializing in artificial intelligence and legal reasoning. He has been recognized for his contributions with awards such as the Best Paper Award (2022-23) and the Visvesvaraya Part-Time PhD Fellowship (2018-19). His teaching and research continue to inspire and shape the next generation of engineers and technologists.

Publication profile

Education

Dr. Sayyed Usman Ahmed holds a Ph.D. in Computer Engineering from Aligarh Muslim University (AMU), India, where he conducted research on “Decision Intelligence in Augmentation of Legal Reasoning” under the supervision of Prof. Nesar Ahmad. His thesis was submitted on March 6, 2024. He earned his M.Tech in Computer Engineering from Rajasthan Technical University (2012-2014) with a thesis on evaluating the efficiency and effectiveness of code reading techniques, supervised by Dr. Rajendra Purohit. He completed his B.Tech in Computer Engineering from AMU (2003-2007), with a project on fingerprint detection systems under the guidance of Prof. M. Sarosh Umar and Prof. Syed Atiqur Rahman.

Experience

Dr. Ahmed has extensive experience in academia and industry. He is currently an Assistant Professor at AMU, teaching courses in software engineering, data structures, information security, and programming labs. He has also served as a Deputy Head of the Information Technology department at Jodhpur Institute of Engineering and Technology, where he contributed significantly to teaching, course development, and departmental administration. In the industry, he has worked as an Application Software Engineer at Computer Science Corporation, focusing on software maintenance, bug fixes, and enhancements. Additionally, he has served in various capacities at the Computer Centre of AMU, including roles as a Programmer and Technical Consultant.

Research focus

Dr. Ahmed’s research interests encompass artificial intelligence, machine learning, natural language processing, and decision intelligence. He has published extensively in journals and conferences, focusing on areas such as sentiment analysis, depression detection from social media posts, rumor-free social networks, and news article summarization. His recent research includes a framework for legal case brief generation using natural language processing and smart contract generation through NLP and blockchain.

Publication top notes

1. Ahmad, T., Ahamad, M., Ahmed, S. U., Ahmad, N. (2022) Short question-answers
assessment using lexical and semantic similarity based features, Journal of Discrete
Mathematical Sciences and Cryptography, 25:7, 2057-2067, DOI:
10.1080/09720529.2022.2133245 [ESCI & Scopus]

2. Ahmed, S. U., Ahmad, T., Ahmad, N. (2022). Sentiment Analysis Techniques for
Depression Detection from Micro-Blogging Social Media Post. NueroQuantology
DOI: 10.14704/NQ.2022.20.12.NQ77265 [Scopus]

3. Ahmad, T., Ahmed, S. U., Ali, S. O., & Khan, R. (2020). Beginning with exploring the
way for rumor free social networks. Journal of Statistics and Management Systems, 23(2),
231-238. https://doi.org/10.1080/09720510.2020.1724623 [Web of Science]

4. Ahmad, T., Ahmed, S. U., Ahmad, N., Aziz, A., Mukul, L. (2020). News Article
Summarization: Analysis and Experiments on Basic Extractive Algorithms. International
Journal of Grid and Distributed Computing, 13(2), 2366 – 2379. [Web of Science]

5. Ahmed, S. U. (2018). Monitoring Unscheduled Leaves using IVR. Global Journal of
Computer Science and Technology, 18(1), 7–9. [Peer-reviewed]

6. Ahmed, S. U., & Purohit, R. (2014). Evaluating Efficiency and Effectiveness of Code
Reading Technique with an Emphasis on Enhancing Software Quality. International
Journal of Computer Applications, 2, 32-36. [Peer-reviewed]

7. Ahmed, S. U., Azmi, M. A., Badgujar, C., (2014). How to design and test safety critical
software systems. International Journal of Advances in Computer Science and Technology,
3(1), 19-22. [Peer-reviewed]

8. Ahmed, S. U., Sahare, S. A., & Ahmed, A. (2013). Automatic test case generation using
collaboration UML diagrams. World Journal of Science and Technology. 2, [Peerreviewed]

9. Ahmed, S. U., & Azmi, M. A. (2013). A Novel Model Based Testing (MBT) approach for
Automatic Test Case Generation. International Journal of Advanced Research in
Computer Science, 4(11), 81-83. [Peer-reviewed]

Journal Publications (Under Review)
1. Ahmed, S. U., Ahmed, N., Ahmad, T. (2023) A Rhetorical Role Relatedness (RRR)
framework for Legal Case Brief Generation Natural Language Processing Journal
(Elsevier, Submitted)