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.

Zhang Zhang | Algorithms | Best Researcher Award

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Mr. Zhang Zhang | Algorithms | Best Researcher Award

Phd Student at Beijing Normal University, China📖

Zhang Zhang is a Ph.D. candidate in Complex Systems Analysis at Beijing Normal University, with visiting research experience at the University of California, San Diego, and the University of Padua. His research focuses on AI by Complexity, Machine Learning for Complex Systems, and Complex Networks. He has authored multiple high-impact papers and has received several prestigious awards for his academic excellence and contributions to network science.

Profile

Google Scholar Profile

Education Background🎓

  • Ph.D. in Complex Systems Analysis, Beijing Normal University (2019–Present)
  • Visiting Ph.D. Student, University of California, San Diego (2023–2024)
  • Visiting Ph.D. Student, University of Padua (2022–2023)
  • B.A. in Information Security, Hangzhou Dianzi University (2013–2017)

Professional Experience🌱

  • Research Assistant, Beijing Normal University (2018–2019)
  • Teaching Experience: Taught Python Programming, Machine Learning, and Deep Learning Principles; developed online courses on deep learning with significant engagement.
  • Reviewer for Information Science and Neural Computing and Applications.
Research Interests🔬
  • AI by Complexity
  • Machine Learning for Complex Systems
  • Complex Networks

Author Metrics

  • Total Citations: 252
  • h-index: 7
  • Publications: Featured in Nature Communications, Applied Network Science, Physical Review E, and top AI/complex networks conferences.

Awards & Honors

  • First-Class Scholarship (2020, 2022, 2023) – Beijing Normal University
  • China Scholarship Council (CSC) Scholarship – National High-Level Joint Doctoral Training Program (2022)
  • Best Team Award – Mediterranean School of Complex Networks (2022)
Publications Top Notes 📄

1. The Cinderella Complex: Word embeddings reveal gender stereotypes in movies and books

  • Authors: H. Xu, Z. Zhang, L. Wu, C.J. Wang
  • Journal: PLOS One
  • Volume/Issue: 14(11)
  • DOI: 10.1371/journal.pone.0225385
  • Year: 2019
  • Citations: 89
  • Abstract: This study investigates how word embeddings reveal gender stereotypes in movies and literature, highlighting biases in linguistic representations over time.

2. A General Deep Learning Framework for Network Reconstruction and Dynamics Learning

  • Authors: Z. Zhang, Y. Zhao, J. Liu, S. Wang, R. Tao, R. Xin, J. Zhang
  • Journal: Applied Network Science
  • Volume/Issue: 4, 1-17
  • DOI: 10.1007/s41109-019-0184-x
  • Year: 2019
  • Citations: 64
  • Abstract: This paper presents a deep learning-based framework for reconstructing networks and learning their dynamics from time-series data, with applications in neuroscience and finance.

3. An Interpretable Deep-Learning Architecture of Capsule Networks for Identifying Cell-Type Gene Expression Programs from Single-Cell RNA-Sequencing Data

  • Authors: L. Wang, R. Nie, Z. Yu, R. Xin, C. Zheng, Z. Zhang, J. Zhang, J. Cai
  • Journal: Nature Machine Intelligence
  • Volume/Issue: 2(11), 693-703
  • DOI: 10.1038/s42256-020-00233-8
  • Year: 2020
  • Citations: 53
  • Abstract: This study introduces an interpretable deep-learning model using capsule networks to analyze gene expression patterns, improving accuracy in single-cell sequencing studies.

4. Universal Framework for Reconstructing Complex Networks and Node Dynamics from Discrete or Continuous Dynamics Data

  • Authors: Y. Zhang, Y. Guo, Z. Zhang, M. Chen, S. Wang, J. Zhang
  • Journal: Physical Review E
  • Volume/Issue: 106(3), 034315
  • DOI: 10.1103/PhysRevE.106.034315
  • Year: 2022
  • Citations: 20
  • Abstract: A theoretical framework to reconstruct network structures and node dynamics from both discrete and continuous data, providing insights into complex system behavior.

5. Inferring Network Structure with Unobservable Nodes from Time Series Data

  • Authors: M. Chen, Y. Zhang, Z. Zhang, L. Du, S. Wang, J. Zhang
  • Journal: Chaos: An Interdisciplinary Journal of Nonlinear Science
  • Volume/Issue: 32(1)
  • DOI: 10.1063/5.0071531
  • Year: 2022
  • Citations: 14
  • Abstract: A novel approach to infer hidden structures in dynamic networks where some nodes remain unobservable, with applications in neuroscience and social networks.

Conclusion

Zhang Zhang is an excellent candidate for the Best Researcher Award based on his strong academic contributions, international exposure, and impactful research in Complex Networks and AI by Complexity. His publication record, citations, and involvement in high-quality research collaborations position him as a highly deserving researcher. Strengthening his industry impact, increasing citations, and taking on more leadership roles in research projects would further solidify his case for this prestigious award.

Eman Abdullah Aldakheel – Deep learning- Academic Achievement Award

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Eman Abdullah Aldakheel – Deep learning- Academic Achievement Award

🌐 Professional Profile

Educations📚📚📚

She earned her Doctor of Philosophy in Computer Science from the University of Illinois at Chicago in Fall 2019, with her dissertation titled “Deadlock Detector and Solver (DDS).” She completed her Master of Science in Computer Science at Bowling Green State University in Fall 2011, with her thesis titled “A Cloud Computing Framework for Computer Science Education.” Her academic journey began with a Bachelor of Science in Computer Science from Imam Abdulrahman bin Faisal University (formerly Dammam University) in Fall 2006, where she graduated with honors.

In her academic career, she began as an Instructor at New Horizons Institute in Khobar, KSA, during Summer 2007, where she trained students at various levels on ICDL and IC3 certificates and taught courses in Computer Mathematics, Secretary duties, office management, and office technology. She then taught basic computer skills and Microsoft Office applications at Dammam University (now Imam Abdulrahman bin Faisal University) in Fall 2007. Prior to this, she worked as a Teacher at Riyadh Al-Islam Schools in Spring 2007, where she taught basic computer skills to girls, ranging from elementary to high school students.

Since Fall 2012, she has been serving as a faculty member at Princess Nourah Bint Abdulrahman University in Riyadh, KSA

Work experience

As a Lecturer and Assistant Professor, she teaches a range of courses including Foundations of Programming (GN 044), Discrete Structures (CS100), Programming Language I (CS110), Programming Language II (CS111), Computer Organization (CS206), Natural Language Processing (CAI 350), Graduation Project I (CS487), and Graduation Project II (CS488). She is involved in designing and recording a programming basics course and a data structures course as electronic courses for the programming diploma program. She participates in faculty committees and collaborative initiatives to improve the curriculum and attends seminars to stay updated on the latest trends in technology and teaching methods. She also serves as a scientific contact at the University of Southern California in the field of video game design and is the Computer Sciences’ program leader.

In her non-academic experience, she served as Vice President, Director of Public Relations, and Director of the Cultural and Information Committee at King Abdulaziz and his Companions Foundation for the Gifted from Summers 2002 to 2007. During her tenure, she built a summer science program for talented students, encouraged their inventiveness, and gained significant managerial skills through her six years of work with the President of the program.

Certifications or Professional Registrations:

She holds several notable certifications and professional registrations, including membership in the Golden Key International Honor Society and the Phi Kappa Phi Honor Society. She also possesses the Huawei HCIA-AI Certificate. Her current professional memberships include the Computing Research Association, the Association for Computing Machinery (ACM), and the IEEE Computer Society.

 

Honors and Awards:

She has received several honors and awards, including participation in the CRA-Women Grad Cohort Workshop, and has been recognized with the ACM’s SRC Travel Award and the HPDC Travel Award. Her service activities encompass planning programs and activities for talented students, building and designing electronic courses, and supervising the student magazine for the College of Computer and Information. She is also involved in various committees, including judging and supervising hackathons.

In terms of granted projects, she is currently working on the Researchers Supporting Project at Princess Nourah bint Abdulrahman University (Project number: PNURSP2023R409) for the year 2023. She is also leading two projects funded by the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia: “Detection and Identification of Plant Leaf Diseases using YOLOv4” (Project number RI-44-0618) from November 2022 to May 2024, and “Use of Modern Machine Learning Techniques to Combat Extremism and the Role of Women” (Project number WE-44-0279) from November 2022 to May 2024.

📝🔬Publications📝🔬

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📝🔬

Pavithra sekar – Deep Learning – Best Researcher Award

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Pavithra sekar -Deep Learning – Best Researcher Award

Dr. Pavithra sekar distinguished academic and researcher in the field Deep Learning.

🌐 Professional Profile

Educations📚📚📚

She holds a Bachelor of Engineering (B.E.) in Computer Science Engineering, which she completed in April 2006 with a percentage of 75.6%, earning a first-class with distinction from Vel Tech Engineering College, affiliated with Anna University. She further advanced her education by obtaining a Master of Engineering (M.Tech) in Information Technology in June 2011, achieving a percentage of 8.43 and graduating with first-class honors from Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, also affiliated with Anna University. She completed her academic journey with a Ph.D. in Information Technology, awarded on January 24, 2020, from St. Peter’s Institute of Higher Education and Research.

PROFESSIONAL EXPERIENCE:

She possesses about 17 years of experience in the field of education, encompassing teaching, administration, and research. Currently, she holds the position of Assistant Professor Sr in the School of Computer Science and Engineering at Vellore Institute of Technology, Chennai. Her career includes roles such as Assistant Professor (Sr) in the Department of Computer Science and Engineering at VIT Chennai since December 15, 2023. Previously, she served as Assistant Professor (SG) and IPR coordinator in the Department of Information Technology from March 31, 2021, to December 7, 2022, at Rajalakshmi Engineering College. Prior to that, she was Assistant Professor & Assistant HOD in the Computer Science & Engineering Department at VelTech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College for 9.6 years, from July 6, 2011, to January 25, 2021. She began her career as a lecturer in the Department of Information Technology at VelTech MultiTech Dr. Rangarajan Dr. Sakunthala Engineering College from August 24, 2006, to September 25, 2009.

 

DEVELOPMENT ACTIVITIES

She possesses a thorough understanding of her subject area, demonstrating an exceptional ability to effectively communicate complex concepts to her students. Her strong communication and comprehension skills enhance her role in internal administrative tasks within educational institutions. She has a proven track record in coordinating various activities such as symposiums, student projects, and conferences, where she provides guidance and support to ensure successful outcomes. Her extensive experience includes roles as Class Coordinator, Conference Coordinator, Project Coordinator for contests, and organizing events like the MOTOROLA FAER EVENT. Additionally, she has served as ISO coordinator, handled NBA coordination, and participated actively in autonomous file activities. She is involved in setting question papers for autonomous colleges and universities and has excelled in roles such as Class In-Charge, Student Mentor, and AICTE CII-Survey participant. She diligently maintains semester-wise result analysis reports, prepares weekly schedules, and curates course materials for effective teaching. Her commitment to excellence is evident in achieving over 90% results across all subjects and receiving a publication award of 16,000. Notably, she achieved a perfect 100% result in key subjects like Computer Programming, Operating System, Computer Architecture, Advanced Computer Architecture, and Problem Solving And Python Programming.

📝🔬Publications📝🔬

1. S. Pavithra and K. Venkata Vikas, “Detecting Unbalanced Network Traffic Intrusions With Deep
Learning,” in IEEE Access, vol. 12, pp. 74096-74107, 2024, doi: 10.1109/ACCESS.2024.3405187.
2. . Pavithra, T. Veeramani, S. Sree Subha, J.P. Sathish Kumar, S. Shanmugan, Ammar H.
Elsheikh, F.A. Essa, “Revealing prediction of Perched Cum Off-Centered Wick Solar Still
Performance using network based on Optimizer algorithm” Process Safety and
Environmental Protection,Volume 161,2022, Pages 188-200,ISSN 0957-
5820,https://doi.org/10.1016/j.psep.2022.03.0092022, .(SCI, Scopus).)(Impact factor: 7.92).
3. Meena, M., Kavitha, A., Karthick, Pavithra.S “Effect of decorated photoanode of
https://doi.org/10.1007/s12034-022-02828-9 .(SCI, Scopus).)(Impact factor: 1.92).
4. S.Pavithra, P.M Anu “An Efficient Data Aggregation with Optimal Recharging in Wireless
Rechargeable Sensor Networks” (Submission code: IJAIP-221302) for the International
Journal of Advanced Intelligence Paradigms (IJAIP) Inderscience
DOI: 10.1504/IJAIP.2022.10040244,2022 (Scopus). Impact factor ( 0.63)
5. S.Pavithra Assistive Chatbot device to support Visually Impaired Person to access
Transport Mode Status Using Deep Learning Model ARPN Journal of Engineering and
Applied Sciences waiting for Publication 2022. (Scopus).
6. S.Pavithra, R.Karthikeyan P.M Anu “Detection and classification of 2D and 3D Hyper
Spectral Image Using Enhanced Harris Corner Detector” “Scalable Computing: Practice and
Experience, ISSN 1895-1767, Volume 21, Issue 1, pp. 93–100, DOI

Jameer kotwal- Deep Learning – Best Researcher Award

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Jameer kotwal- Deep Learning – Best Researcher Award

Mr. Jameer Kotwal distinguished academic and researcher in the field Deep Learning.  He has been actively involved in various academic and technological endeavors. In 2020, he developed the “Time Table Lecture Announcer” system, which was displayed outside the classroom. The following year, in 2021, he worked on implementing a “Facial Attendance System” using a Siamese Deep Learning model, with deployment outside the project lab.

Moreover, his engagement extends to educational institutions, where he has contributed to curriculum development and faculty training programs. At Sandip Institute of Technology & Research, he participated in the Faculty Orientation Program (FOP) conducted by Savitribai Phule Pune University (SPPU) for the revised syllabus of the Bachelor of Engineering (BE) program in 2019, specifically focusing on the Deep Learning Lab. Similarly, at Shree Ramchandra College of Engineering, he was involved in the Faculty Development Program (FDP) for the revised BE syllabus in Deep Learning in 2023.

Furthermore, he has facilitated workshops and sessions on advanced topics. Notably, at Nutan Maharashtra Institute of Engineering & Technology (NMIET), he conducted sessions on NVIDIA and CUDA technologies in 2020. Additionally, he has contributed to teaching Advanced Data Structures at Keystone School of Engineering in 2019 and Laboratory Practice-IV at Dr. D. Y. Patil Institute of Engineering, Management & Research in 2018. His involvement dates back to 2012 when he taught Compiler Design at Dr. D. Y. Patil Talegaon.

🌐 Professional Profile

Educations📚📚📚

He pursued his Ph.D., with the thesis submitted to Amity University Raipur. Prior to that, he completed his M.E. in Computer Engineering from G.H. Raisoni College of Engineering & Management, Pune, achieving a CGPA of 6.93, securing a First Class. His undergraduate degree, a B.E. in Computer Engineering, was earned from SVERI College of Engineering, Pandharpur, under Solapur University, where he attained a First Class with a percentage of 64.14. Additionally, he completed a Diploma in Computer Engineering from Government Polytechnic Solapur under the Maharashtra State Board of Technical Education (MSBTE Mumbai), achieving a First Class with a percentage of 66.88.

He has achieved significant recognition and accolades throughout his career. Notably, he secured the second position at the Amity Incubation Centre for his presentation on “Plant Disease Identification using Deep Learning.” Furthermore, he has served as a mentor for various teams in the Smart India Hackathon, including Team 8 bit in 2022, where they focused on “Handwritten Text in Indian Languages” and won the first prize of Rs.1 lakh. Similarly, in 2020, he mentored Team SV_Gravity, who worked on “Virtual Moon Reality,” leading them to secure the first prize of Rs.1 lakh.

Additionally, he participated in the Bhabha Atomic Research Centre Exhibition and seminar titled “Atomic Energy for Peace, Power, and Prosperity” in 2018 at PCCOER, Ravet, Pune. His contributions have been recognized with the Best Teacher Award at NMIET and PCCOER, reflecting his dedication and excellence in education and mentorship.

📝🔬Publications📝🔬
  • Jameer kotwal Tanvi Bhosale,, Biradar, A., Bhat, K., Barhate, S., (2023). Applied Deep Learning for Safety in Construction Industry.Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-6004-8_15.
  • Jameer Kotwal Harshal Thakare Dhanashri Wani, Dhiraj Sangale Abhijeet Walunj,” Deep Reinforcement Learning And Object Detection For Adaptive Traffic Signal”, Journal of Seybold Report , Volume 15 Issue 8 Pages 2020.
  • Jameer Kotwal Varun Pilakavil, Hitesh Chaudhari, Pratik Khedekar, Aniket Deotale,” Real Time Product Price Monitoring & Analysis Application for E-Commerce Websites”, International Research Journal of Engineering and Technology, Volume 1 Issue 1 Pages 1237
  • Jameer Kotwal Harshal Thakare Dhanashri Wani, Dhiraj Sangale Abhijeet Walunj,” Deep Reinforcement Learning and Image Processing for Adaptive Traffic Signal Control”,IJSRET, Volume 6, Issue 1, Jan-Feb-2020.
  • Jameer Kotwal Shivakumar Iyer, Manisha Chate, Shubhangi Dhawan, Shivani Thorve, “An Web Based Emergency Alert System”,JETIR(UGC approved), Volume 6, Issue.1,Pages.388.
  • Jameer Kotwal, Dr.Sachin Babar,” Solving Monte-Carlo Method by Using GPU and CPU”,IJCSIT,Volume 8 Issue 3 Pages 324-326.
  • Jameer G Kotwal, Tanuja S Dhope ,”Solving Task Allocation to the Worker Using Genetic Algorithm,”International Journal of Computer Science and Information Technologies,Vol.6,Issue.4,Pages.3736-3741.
  • Jameer Kotwal, Prajkta Varhade, Komal Koli ,”Text clustering for computer investigation with search optimization “,International Journal of Engineering & Computer Science,4,Issue.11,Pages.14921.
  • Jameer Kotwal,Aishwarya Jadhav,Kasture,Gayatri,Amruta,” Pulse Rate Monitoring Device Based On Arduino and Android Platform”, International Journal for Research in Applied Science & Engineering Technology (IJRASET) (UGC approved), ISSN: 2321-9653; Volume 6 Issue III, March 2018.
  • Jameer Kotwal,Harnoor sodhi,Tejaswini,Khade,” Secured Access Control Using Secret key and OTP for Cloud Computing Services”, International Journal for Research in Applied Science & Engineering Technology (IJRASET), ISSN: 2321-9653; Volume 6 Issue III, March 2018.
  • Jameer Kotwal,Amol Roundal,Neeraj, “Speed Alert System for GPS-enabled Smartphone’s with Android operating system” “,International Journal of Computer Science and Information Technologies,Vol.6,Issue.1,Pages.745.
  • Jameer Kotwal,Tanuja Dhope,”Unbalanced Assignment Problem by Using Modified Approach “,International Journal of Advanced Research in Computer Science and Software Engineering ,Vol.5,Issue.7,Pages.451.
  • Jameer Kotwal, Snehal Pawar, Shraddha Pansare, Madhura Khopade, Pratibha Mahalunkar (2015),”Android App For Meter Reading” in: International Journal of Engineering & Computer Science ,Vol.4,Issue.1,Pages 9853-9856.

Esha Aftab – Neural Models – Best Researcher Award

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Esha Aftab – Neural Models – Best Researcher Award

Ms. Esha Aftab  distinguished academic and researcher in the field Neural Models.  She possesses a strong foundation in various undergraduate courses such as Introduction to Computing, Object-Oriented Programming (C++), Data Structures and Algorithms, Database Systems, Digital Logic Design, and Design and Analysis of Algorithms. Her technical proficiencies encompass a wide range of technologies and languages including C#, ASP, .NET Framework, PRISM Framework, MATLAB, MS SQL Server 2005, Oracle, Java, JavaScript, Java ME, and OpenGL.

🌐 Professional Profiles

Educations📚📚📚

She is currently pursuing her PhD at Punjab University College of Information Technology, with a focus on advancing her knowledge and expertise in her field. Prior to this, she completed her M.Sc in Computer Science at Lahore University of Management Sciences (LUMS) in 2012, achieving a commendable CGPA of 3.66 out of 4.0. Her academic journey commenced with a Bachelor’s degree in Computer Science from the National University of Computer & Emerging Sciences (NU-FAST), Lahore, where she graduated in 2009 with an impressive CGPA of 3.74 out of 4.0. Her educational background reflects a consistent dedication to academic excellence and a strong commitment to her field of study.

Work Experience

She has amassed a wealth of experience across academia and industry. Currently serving as an Assistant Professor at Punjab University College of Information Technology (PUCIT) since 2019, her role involves conducting programming and technical courses, with a particular focus on subjects such as Data Structures, Algorithms, and Machine Learning. Prior to this, she held the position of Lecturer at NUCES-FAST from 2012 to 2019, where she contributed significantly to the academic environment. Additionally, she served as Visiting Faculty in 2012, delivering the ‘Applied Programming’ course for MSc students. Her industry experience includes a stint as a Software Engineer at Techlogix Pvt. Limited from 2009 to 2010, where she was involved in designing and developing automated business processes for clients like Ufone, Motorola, and Nestle. Her projects ranged from enterprise application integration for Ufone using IBM WebSphere Integration Developer to implementing automated business processes for Motorola using Savvion BPM Software and devising algorithms for Nestle’s Milk Balancing System. She adeptly utilized various development tools such as Microsoft Visual Studio 2008, Silverlight, Telerik Toolkit, and .Net Framework to deliver innovative solutions across her diverse roles.

Technical Proficiencies
 She is adept at working in different development environments such as Linux (Ubuntu), MS Visual Studio (2008/2010), Netbeans IDE, Eclipse, Savvion BPM Software, and IBM Websphere Toolkit. Noteworthy among her major projects is her contribution to a Computer Vision Research Project focused on developing a Shape and color-based Jigsaw Puzzle Solver, achieving successful results in shape-based jigsaw piece identification and implementing piece placement algorithms using image stitching techniques. Additionally, she has contributed to a research-based project on Image Annotation, employing statistical methods to label images according to their content. Her diverse skill set and hands-on experience in both academic and research settings underscore her proficiency and versatility in the field of computer science

Academic Achievements

 Silver Medalist: 2nd position in BCS (FAST)
 Dean’s List Honor Certificate (FAST)

 

📝🔬Publications📝🔬

Jorge Laureano Moya Rodríguez – Neural Networks – Best Researcher Award

Posted on by ResearchW

Jorge Laureano Moya Rodríguez – Neural Networks

 Prof Dr.  Jorge Laureano Moya Rodríguez distinguished academic and researcher in the field Neural Network.  Jorge Laureano Moya Rodríguez is a Professor Emeritus at the Central University “Marta Abreu” de las Villas. Cuba. He received his Ph.D. in Mechanical Engineering at this university in 1994. He published over a three hundred papers in professional journals and he has authored several books in mechanical and electrical engineering. He has several international and national awards, including some from the Academy of Sciences of Cuba. He has lectured in different Universities of Spain, México, Nicaragua and Brazil. He is currently visiting professor at the Federal University of Bahia in Brazil. Dr. Moya’s research interests are Multiobjective Optimization, Logistics, Computer Aided Design, and Computer Aided Engineering.

Ele é também membro da ERASMUS MUNDUS ASSOCIATION (EMA) e da Associação Mexicana de Modelagem Numérica e Engenharia (AMMNI). Reconhecido como bolsista de produtividade em Pesquisa pelo CNPq (nível 2) e consultor ad hoc do CNPq, ele contribui como árbitro para diversas revistas científicas e instituições acadêmicas em países como Venezuela, Colômbia, Peru e Cuba. Com uma ampla lista de mais de 50 projetos de pesquisa concluídos e implementados em Cuba, ele é considerado Professor de Mérito pela Universidade Central Marta Abreu de Las Villas. Sua atuação como professor abrange cursos de pós-graduação e disciplinas de mestrado em várias universidades, incluindo a Universidade Federal do Espírito Santo (Brasil), Universidade Veracruzana (México), Universidade Técnica do Estado de Aragua (Venezuela) e Universidade Nacional de Engenharia (Nicarágua). Ele também coordenou o Mestrado em Engenharia Mecatrônica em várias universidades na Venezuela e trabalhou como professor convidado em diversas instituições no México, Peru e Espanha. Anteriormente, ele foi pesquisador do ITEGAM, professor visitante na Universidade Federal do Espírito Santo e na Universidade Federal da Bahia.

 

🌐 Professional Profiles

Educations: 📚🎓

Jorge Laureano Moya Rodríguez, known in bibliographic citations as J. L. M. Rodríguez, J. L. Moya, Jorge Moya, Jorge Laureano Moya Rodríguez, J. Moya, Jorge Rodríguez, Jorge L. Moya Rodríguez, or variations thereof, is affiliated with the University Federal da Bahia, where he works within the Program of Industrial Engineering Postgraduate Studies.

He completed a postdoctoral position in 2011 at the Universidad de Oviedo, UNIOVI, Spain, funded by the Agencia Española de Colaboración Internacional, AECI, Spain. The research was in the field of Engineering.

In 2008, he undertook a postdoctoral fellowship at the Universidad de Oviedo, UNIOVI, Spain, funded by ERASMUS MUNDUS, EM, Germany. The research focus was in Engineering.

In 2005, he conducted postdoctoral research at the Universidad Católica de Leuven, KLU, Belgium, supported by VLIR, VLIR, Belgium. The research was within the field of Engineering.

Publication