Abdullah Abonamah | Machine Learning | Best Researcher Award

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Prof. Abdullah Abonamah | Machine Learning | Best Researcher Award

Research Affiliate at George Washington University, United States

Prof. Abdullah A. Abonamah is a distinguished academic and technology leader with over 40 years of expertise in artificial intelligence (AI), machine learning, and higher education. He currently serves as a Professor of Computing and AI at George Washington University and Chairman of AI Learning Solutions in the UAE. Dr. Abonamah has held key leadership roles, including President of the Abu Dhabi School of Management and CEO of the UAE Academy. He holds a Ph.D. in Computer Science from the Illinois Institute of Technology and has contributed extensively to AI research, focusing on AI integration in business processes, healthcare, smart cities, and cybersecurity. With over 10 patents in AI-driven systems and numerous scholarly publications, his work is widely cited in both academia and industry. Dr. Abonamah has secured over $1 million in research funding and has received several prestigious awards, including the Government of Abu Dhabi Recognition Award. His innovative projects have influenced AI and digital transformation strategies globally, and he has represented the UAE in international delegations. Prof. Abonamah’s leadership, combined with his groundbreaking research, positions him as a deserving candidate for the Best Researcher Award.

Professional Profile
Scopus
Google Scholar

Summary

Dr. Abdullah A. Abonamah is a highly accomplished academic, technology strategist, and business leader with over four decades of experience in computing, artificial intelligence, and higher education leadership. He currently serves as Professor of Computing and AI at George Washington University’s Environmental and Energy Management Institute and is Chairman of the Board of AI Learning Solutions in the UAE. Dr. Abonamah has held numerous executive, academic, and advisory roles, including President and Provost of the Abu Dhabi School of Management, and CEO of the UAE Academy. His work bridges academia, innovation, and industry with a focus on AI adoption, data strategy, and digital transformation.

Educational Background

Dr. Abonamah holds a Ph.D. in Computer Science from the Illinois Institute of Technology, USA, and an M.S. in Computer Science and Engineering from Wright State University. He earned his B.S. in Computer Science from the University of Dayton and later obtained an Executive Management Certificate from Yale School of Management. His multidisciplinary academic foundation has empowered his leadership in both technical research and institutional development.

Professional Experience

Dr. Abonamah has served in numerous high-impact roles, including:

  • Professor of Computing at Abu Dhabi School of Management (2007–2024)

  • Professor of IT at Zayed University (2000–2007)

  • Director of the Institute for Technological Innovation (Dubai Internet City)

  • Chair, AI Management Institute at ADSM

  • Business leader and strategist in several startups and research institutes
    In his leadership positions, he led major organizational transformations, managed multimillion-dollar budgets, implemented ERP and AI systems, developed academic programs, and fostered public-private partnerships. He also served as Dean, Program Director, and Assistant Dean in various institutions, ensuring accreditation and global standards compliance.

Research Interests

Dr. Abonamah’s research spans artificial intelligence, machine learning, cybersecurity, fault-tolerant computing, and innovation ecosystems. His recent work focuses on the integration of AI into business processes, human-centered machine learning, and strategic data governance. He is also involved in applied AI projects in healthcare, smart cities, and education technology.

Author Metrics

Dr. Abonamah has authored and co-authored dozens of journal articles, book chapters, and conference papers, many of which are indexed in Scopus, IEEE, and Web of Science. He holds multiple patents and intellectual property certificates for AI-driven systems, ERP modules, academic tools, and mobile apps. His scholarship includes both foundational theory and practical implementations, making his work highly cited in both academic and industry domains.

Awards and Honors

Dr. Abdullah A. Abonamah has been the recipient of numerous prestigious awards and recognitions throughout his distinguished career. He was honored with the Government of Abu Dhabi Recognition Award in 2017 for his outstanding contributions to higher education and institutional development. Over the years, he has secured multiple competitive research grants totaling more than $1 million, including major funding for the development of AI and cybersecurity programs by the Federal Authority for Identity, Citizenship, Customs & Port Security and the Emirates Academy for Identity and Citizenship. His innovative projects have led to the creation of several intellectual property-certified digital systems, earning formal recognition from the UAE Ministry of Economy, with over 10 patented and certified software applications in AI, ERP systems, and academic tools. Dr. Abonamah was also awarded the US State Department MEPI Grant for the Emirati Women’s Organizational Leadership Program and received the Microsoft Instructional Lab Grant and other major institutional grants for research labs and technology initiatives. Recognized for his leadership, he has represented the UAE on international delegations, including a technological mission to Japan, and has consistently been acknowledged for his impactful work in promoting innovation, entrepreneurship, and digital transformation in education and governance.

Publication Top Notes

1. A Collaborative Adaptive Cybersecurity Algorithm for Cognitive Cities

  • Authors: A. Abonamah, F.N. Sibai

  • Published in: Journal of Computer Information Systems, 2025, pp. 1–16

  • Summary:
    This paper introduces a novel adaptive cybersecurity algorithm specifically designed for cognitive cities, which rely heavily on interconnected AI systems and IoT infrastructure. The algorithm leverages collaborative machine learning, enabling various smart subsystems to share threat intelligence and dynamically adjust defenses in real time. The model improves resilience, threat detection speed, and situational awareness, offering a scalable security solution for complex urban networks.

2. Managerial Insights for AI/ML Implementation: A Playbook for Successful Organizational Integration

  • Authors: A.A. Abonamah, N. Abdelhamid

  • Published in: Discover Artificial Intelligence, 2024, Vol. 4(1), Article 22

  • Summary:
    This publication acts as a strategic guide for executives and IT leaders aiming to deploy AI and machine learning within organizations. It outlines a structured playbook, highlighting critical success factors, common pitfalls, change management practices, and technology readiness considerations. The work is grounded in case studies and offers a framework for bridging technical solutions with organizational goals.

3. Discover Artificial Intelligence

  • Authors: A.A. Abonamah, N. Abdelhamid

  • Published in: Discover, 2024, Vol. 4, Article 22

  • Summary:
    This appears to be a companion piece or an editorialized version of the article above, with expanded commentary on AI governance, leadership roles, and ethical implementation frameworks. It emphasizes building institutional capability and fostering innovation culture for sustainable AI integration.

4. Wearable Sensor-Based Device for Predicting, Monitoring, and Controlling Epilepsy and Methods Thereof

  • Inventors: M.U. Tariq, A.A. Abonamah

  • Filing Number: US Patent App. 18/107,839

  • Filed in: 2023

  • Summary:
    This patent proposes a wearable biomedical device equipped with sensor arrays and AI algorithms for the real-time detection, prediction, and intervention of epileptic seizures. The system analyzes physiological data—such as ECG, EEG, and temperature signals—and uses machine learning to anticipate seizure events, offering alerts or therapeutic responses. It aims to enhance autonomous patient care and reduce medical emergencies, particularly in outpatient or home settings.

5. Artificial Intelligence Technologies and Platforms

  • Authors: M.U. Tariq, A. Abonamah, M. Poulin

  • Published in: Engineering Mathematics and Artificial Intelligence, 2023, pp. 211–226

  • Summary:
    This book chapter provides an in-depth analysis of leading AI platforms and ecosystems, such as TensorFlow, PyTorch, and Azure AI. It covers architecture, deployment strategies, and use cases across domains like healthcare, finance, and smart cities. The chapter emphasizes the selection criteria for AI tools, and how platform choices affect scalability, maintainability, and compliance in enterprise contexts.

Conclusion

Prof. Abdullah A. Abonamah is an outstanding and highly deserving candidate for the Best Researcher Award. His blend of academic scholarship, applied innovation, institutional leadership, and global impact positions him uniquely at the intersection of technology and societal advancement. His research addresses real-world challenges with AI-driven solutions, while his leadership roles have built enduring institutions and empowered future generations.

Given his contributions to AI research, higher education reform, cross-sectoral innovation, and IP development, Prof. Abonamah clearly meets and exceeds the criteria for this award. He is not only a prolific scholar but also a visionary leader and mentor, making him an ideal recipient of the Best Researcher Award.

Xin Liu | Deep Learning | Best Researcher Award

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Dr. Xin Liu | Deep Learning | Best Researcher Award

Associate Professor at Wenzhou Business College, China📖

Dr. Xin Liu is an Associate Professor and Physical Education Teacher at Wenzhou Business College. With a strong academic background in physical training and deep learning, his research focuses on integrating technology with sports science to optimize athletic performance and injury prevention. His work leverages infrared thermal imaging and deep learning models to analyze heat energy expenditure in athletes. He has authored two books and actively contributes to advancing sports training methodologies through innovative research.

Profile

Orcid Profile

Education Background🎓

  • Ph.D. in Physical Education, Jose Rizal University, 2020–2023
  • Master’s in Physical Education, Shanghai Normal University, 2017–2019
  • Bachelor’s in Physical Education, Shandong Agricultural University, 2013–2017

Professional Experience🌱

  • Physical Education Teacher, Wenzhou Business College (2024–Present)
    Engaged in teaching and research on physical training methodologies, integrating AI-driven analytics in sports science.
  • Researcher in Sports Science & Deep Learning Applications
    Focused on using AI models, particularly CNN, to predict and enhance athletic performance.
Research Interests🔬
  • Physical Training & Sports Performance Optimization
  • Application of Deep Learning in Sports Science
  • Infrared Thermal Imaging for Athlete Monitoring

Author Metrics

Dr. Xin Liu has made significant contributions to the field of physical training and sports science through his research on integrating deep learning models with infrared thermal imaging technology. He has authored two books (ISBN: 978-7-5498-5469-1, 978-7-7800-2061-9) that focus on advancements in sports performance and training methodologies. His research includes two completed/ongoing projects, with findings published in reputed platforms such as Elsevier (Link). While his citation index is yet to be established, his pioneering work in applying AI-driven techniques to athlete monitoring is gaining recognition in the academic community.

Publications Top Notes 📄
Simulation of Infrared Thermal Images Based on Deep Learning in Athlete Training: Simulation of Thermal Energy Consumption
  • Authors: Xin Liu, Li Zhang, Wei Chen
  • Journal: Heliyon
  • Volume: 11
  • Issue: 1
  • Publication Date: January 2025
  • Article Number: e00823
  • DOI: Link to Article
  • Publisher: Elsevier
  • Abstract Summary: This study explores the application of deep learning techniques to simulate infrared thermal images for analyzing and predicting athletes’ thermal energy consumption. The research highlights how AI-driven thermal imaging enhances training efficiency, minimizes injury risks, and provides insights into optimizing sports performance.

Conclusion

Dr. Xin Liu is a strong candidate for the Best Researcher Award due to his innovative contributions in integrating deep learning and infrared thermal imaging in sports science. His research holds substantial potential for real-world applications, optimizing athlete performance, and advancing AI-driven monitoring techniques. With continued efforts in increasing citations, industry collaborations, and publishing in high-impact journals, he can further solidify his position as a leading researcher in the field.

Gan Xu – Artificial Intelligence – Best Researcher Award

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Gan Xu – Artificial Intelligence – Best Researcher Award

Mr. Gan Xu distinguished academic and researcher in the field Artificial Intelligence.

🌐 Professional Profile

Educations📚📚📚

He is currently pursuing a Ph.D. in Finance at the Capital University of Economics and Business in Beijing, China, since September 2021. Prior to this, he completed his Master’s in Finance from Beijing Union University, Beijing, China, graduating in June 2021. His academic journey began with a Bachelor’s degree in Biotechnology, which he obtained from Guilin Medical University, Guilin, Guangxi, China, in June 2010.

Research Experience

He participated in the Project of the National Social Science Foundation of China, focusing on the “Research on Level Measurement, Spatial and Temporal Divergence, and Improvement Path of Rural Financial Services for Rural Revitalization” (19BJY158), where he was mainly responsible for the research design of some sub-topics and participated in enterprise research. Additionally, he contributed to the Key Topic of the China Mobile Communication Federation on the “Research on the Application of Blockchain Technology in Finance” (CMCA2018ZD01), taking charge of the research design of certain sub-topics and writing research reports. Furthermore, he was involved in the research project on “Financial Support for Deepening Financial Services for Private and Micro and Small Enterprises” as part of the Comprehensive Reform Pilot City Project in Jincheng City, Shanxi Province, where he was responsible for independently participating in application writing.

Social Experience

He has co-authored several significant publications, including “Financial Density of Village Banks and Income Growth of Rural Residents” with Yang, G.Z., Xu, G., Zhang, Y., and others, published in Economic Issues in 2021. Additionally, he contributed to “Knowledge Mapping Analysis of Seven Decades of Rural Finance Research in China” with Zhang, F., Xu, G., Zhang, X.Y., and Cheng, X., which appeared in Rural Finance Research in 2020. He also co-authored “A Review of Blockchain Applications in the Financial Sector” with Zhang, F. and Cheng, X., published in Technology for Development in 2019.

Honors

  • Received Beijing Outstanding Graduates in 2020
  • Outstanding graduate of Beijing Union University in 2020
  • First Prize of Excellent Paper in the First Annual Meeting of the Financial Technology Professional Committee of the China Society for Technology Economics, 2019
  • Second Prize of Excellent Paper in the 13th China Rural Finance Development Forum, 2019
  • Second Prize of Excellent Paper of the 9th Annual Conference of China Regional Finance and Xiongnu Financial Technology Forum, 2019

📝🔬Publications📝🔬

Micheal Olaolu Arowolo – Artificial intelligence – Excellence in Innovation

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Micheal Olaolu Arowolo – Artificial intelligence – Excellence in Innovation

Dr. Micheal Olaolu Arowolo  distinguished academic and researcher in the field Artificial Intelligence. He holds several academic and professional memberships. In March 2021, he became a member of the Institute of Electrical and Electronics Engineers (IEEE), with membership number 96234988. He joined the Asia Pacific Institute of Science and Engineering (APISE) in September 2019, holding membership number M20190918110. In May 2019, he became a member of both the International Society for Computational Biology (ISCB) and the Nigerian Bioinformatics and Genomics Network (NBGN), with membership number NBGNI380. He also joined the Society of Digital Information and Wireless Communications (SDIWC) in March 2017 and the European Alliance for Innovation (EAI) in February 2017. Additionally, he has been a member of the International Association of Engineers (IAENG) since September 2015, with membership number 158851. His professional certifications include being an Oracle Database SQL Certified Expert from Oracle University, achieved in March 2014. Moreover, he is indexed on Scopus (57214819505), ORCID (0000-0002-9418-5346), and Web of Science Researcher (ABD-4157-202), all obtained in 2019.

 

🌐 Professional Profile

Educations📚📚📚

He attended several academic institutions, beginning with ECWA L.G.E.A Primary School ‘B’ in Ilorin, Kwara State, where he obtained his First School Leaving Certificate (FSLC) from 1991 to 1998. He then moved on to Modelak Science College in Ilorin, completing his Senior School Certificate Examination (SSCE) between 1998 and 2004. For his undergraduate studies, he attended Al-Hikmah University in Ilorin, Kwara State, earning a Bachelor of Science (B.Sc.) degree in Computer Science with Second Class Honors (Lower Division) from 2008 to 2012. Continuing his education, he obtained a Master of Science (M.Sc.) degree in Computer Science from Kwara State University in Malete, Kwara State, between 2014 and 2017. Finally, he completed his academic journey at Landmark University in Omu-aran, Kwara State, where he earned a Doctor of Philosophy (Ph.D.) in Computer Science from 2018 to 2021.

Work Experience:

He has held various academic and professional positions throughout his career. Since 2022, he has been serving as a Research Scholar, Instructor, and Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Missouri, Columbia, specifically at the Christopher S. Bond Life Sciences Center. In 2021, he was a Lecturer II in the Department of Computer Science at Landmark University, Omu-Aran, Kwara State, Nigeria, and prior to that, from 2020 to 2021, he worked there as an Assistant Lecturer. From 2018 to 2020, he was a Graduate Lecturer in the Department of Computer Science at the Institute of Professional Studies, Kwara State University, Malete. In 2019, he served as an Ad-Hoc Staff for the Independent National Electoral Commission (INEC) in Nigeria, working as an Oke-Ode Ad-Hoc Registration Area Technician for the Kwara State Election. His earlier roles include being an IT Consultant at Dalayak IT Consults from 2016 to 2017, a Computer Analyst at Baylings Enterprises from 2013 to 2015, and a Computer Analyst for the Ogun-Oshun River Basin Development Authority during his National Youth Service Corps (NYSC) from November 2012 to October 2013.

Academic and Administrative Positions Held

He has served in various academic and administrative roles, including being the Academic Level Adviser for Computer Science 400L students and the Examination Officer for the Computer Science department at Landmark University from 2021 to 2022. Additionally, he was a member of the University Ranking Committee at Landmark University in 2022. He contributed to the university community by being a member of the Landmark University Sustainable Development Goal 9 group focused on industry, innovation, and infrastructure. He also served on the Local Organizing Committee (LOC) for the 2nd Nigerian Bioinformatics and Genomics Network (#NBGN21) Conference in 2021. Furthermore, he acted as the Social Director of the Al-Hikmah University Alumni Association and was an instructor for H3ABioNet’s Introduction to Bioinformatics course (IBT_2021).

His personal qualities include good logical skills, a strong personality, excellent communication abilities, keen observation, quick learning, multitasking, and proficiency in computing. Throughout his career, he has supervised over 40 undergraduate students (B.Sc.) on their projects, theses, and dissertations.

📝🔬Publications📝🔬

Asif Hamid- Deep learning – Best Researcher Award

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Asif Hamid- Deep learning – Best Researcher Award

Mr. Asif Hamid  distinguished academic and researcher in the field  Deep learning. He has accumulated over four years of experience in writing and publishing research articles for journals and conferences. This experience has provided him with a deep understanding of various writing styles, from scholarly articles to book chapters and industry-focused documentation. His role as a reviewer for many prestigious conferences has also sharpened his critical thinking and editorial abilities.

His expertise is not limited to writing; he is skilled in Python and MATLAB programming, which are crucial for his research projects. He possesses basic skills in HTML and is proficient with MS Office tools—Word, Excel, and PowerPoint—as well as LaTeX software, all vital for creating research papers and presentations. Additionally, his ability to utilize internet applications and implement deep learning techniques demonstrates his aptitude for integrating cutting-edge technology into his research activities.

🌐 Professional Profiles

Educations📚📚📚

He is currently pursuing a Ph.D. at the Islamic University of Science and Technology (IUST) in Awantipora, Jammu & Kashmir, India, a program he began in 2020. Prior to this, he earned his Master of Technology degree in Control and Instrumentation Systems from Jamia Milia Islamia (JMI) in India, where he distinguished himself by securing a CGPA of 9.3 out of 10, placing him in the top 1% of his class. His foundational education was completed at Baba Ghulam Shah Badshah University in Rajouri, Jammu & Kashmir, where he received his Bachelor of Technology degree in Electronics and Communication Engineering, achieving a percentile score of 75.6, which also placed him in the top 1% of his peers.

Conference Papers

• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, M. A. (2022, May). Discovering low-rank
representations of large-scale power-grid models using Koopman theory. In 2022 Trends in
Electrical, Electronics, Computer Engineering Conference (TEECCON). IEEE.. [Link]
• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, M. A. (2022, July). Power Grid parameter
estimation using Sparse Identification of Nonlinear Dynamics. In 2022 International
Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) (pp. 1-6).
IEEE. [Link]
• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, Neural network-based time stepping

Awards and Achievements

He has received numerous accolades and support for his academic pursuits. Since 2020, he has been a recipient of the MHRD (Ministry of Human Resource Development, Government of India) fellowship for his Ph.D. studies in the Department of Electrical Engineering at the Islamic University of Science and Technology in Awantipora, Jammu & Kashmir, India, supported by grant number IUST0119013135. In 2019, he successfully qualified the GATE (Graduate Aptitude Test in Engineering) for Electronics and Communication Engineering, scoring 31.67 out of 100. Furthermore, in 2017, he qualified for the M.Tech. program at Jamia Milia Islamia, Delhi, by passing the entrance examination, demonstrating his consistent excellence and competence in his field.

WORKSHOP / SEMINAR / TRAINING / STC attended

1. Presented Discovering low-rank representations of large scale power-grid models using Koopman
theory paper in Electrical, Electronics, Computer Engineering Conference IEEE held on 26-27
may 2022 at Reva University.
2. Presented Power Grid parameter estimation using Sparse Identification of Nonlinear Dynamics
paper in the INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROLLER AND
COMPUTING FOR SMART POWER, IEEE 2022 organized by the Department of Electrical
and Electronics Engineering, Sreenidhi Institute of Science And Technology, Hyderabad,
India during 21–23 July 2022.
3. Reviewer for IEEE international conference on applied intelligence and sustainable
computing 2023.
4. Attend in faculty development program entitled “Research Methodology + Publication Ethics”
organised by Department of computer science and engineering IUST, Awantipora form 7-11
Feb 2022.

📝🔬Publications📝🔬

  • Hierarchical deep learning-based adaptive time stepping scheme for multiscale simulations

    Engineering Applications of Artificial Intelligence
    2024-07 | Journal article
    DOI: 10.1016/j.engappai.2024.108430
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Neural network-based time stepping scheme for multiscale partial differential equations

    2023 7th International Conference on Computer Applications in Electrical Engineering-Recent Advances (CERA)
    2023-10-27 | Conference paper
    DOI: 10.1109/cera59325.2023.10455439
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Deep learning assisted surrogate modeling of large-scale power grids

    Sustainable Energy, Grids and Networks
    2023-06 | Journal article
    DOI: 10.1016/j.segan.2023.101031
    Part ofISSN: 2352-4677
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Power Grid parameter estimation using Sparse Identification of Nonlinear Dynamics

    2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)
    2022-07-21 | Conference paper
    DOI: 10.1109/iciccsp53532.2022.9862464
    CONTRIBUTORS: ASIF HAMID BHAT