Dr. Dawei Qiu | Smart Grid | Best Researcher Award

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Dr. Dawei Qiu | Smart Grid | Best Researcher Award

Lecturer, University of Exeter, United Kingdom

Dr. Dawei Qiu is a distinguished scholar in smart energy systems, currently serving as a Lecturer at the University of Exeter, UK 🏫. With a strong background in electrical engineering and power systems, he specializes in AI-driven reinforcement learning, market design for low-carbon energy transition, and resilience enhancement of energy systems ⚡. His extensive research contributions in smart grids and power systems have earned him recognition in academia, with a Google Scholar citation count of 2,109, an h-index of 24, and an h10-index of 35 📊.

Publication Profile

Google Scholar

🎓 Education

Dr. Qiu holds a Ph.D. in Electrical Engineering from Imperial College London (2016–2020) 🎓, where he conducted pioneering research on local flexibility’s impact on electricity retailers under the supervision of Prof. Goran Strbac. Prior to this, he completed his M.Sc. in Power System Engineering from University College London (2014–2015) and obtained his B.Eng. in Electrical and Electronic Engineering from Northumbria University at Newcastle (2010–2014) ⚙️. His academic journey has been shaped by esteemed mentors, including Dr. Ben Hanson and Dr. Zhiwei (David) Gao, IEEE Fellow.

💼 Experience

Dr. Qiu’s professional career spans academia and research institutions, where he has contributed significantly to energy systems innovation 🌍. Before joining the University of Exeter in 2024, he was a Research Fellow at Imperial College London (2023–2024), specializing in market design for low-carbon energy systems. He also served as a Research Associate at the same institution from 2020 to 2023 🔬. His work in smart grids and energy resilience has been instrumental in shaping sustainable and intelligent power infrastructure.

🏆 Awards and Honors

Dr. Qiu’s research excellence has been acknowledged through various accolades 🏅. His contributions to smart energy systems, AI-driven reinforcement learning, and low-carbon market design have positioned him as a leading researcher in the field. His studies have been published in top-tier journals, and his work has received high citations, demonstrating its impact on the global research community 🌟.

🔬 Research Focus

Dr. Qiu’s research is centered on leveraging artificial intelligence and reinforcement learning for power and energy applications 🤖. His work explores market mechanisms for cost-effective and sustainable energy transitions, as well as the resilience enhancement of energy systems in response to climate change 🌍. His expertise in AI-driven optimization and machine learning applications in energy systems makes him a key contributor to the advancement of smart grid technologies.

🔚 Conclusion

Dr. Dawei Qiu is a leading researcher in smart energy systems, with a strong academic background and impactful contributions to power systems engineering 🔬. His expertise in AI-driven market optimization, reinforcement learning, and resilient energy systems has made him a valuable asset to the research community 🌍. With his ongoing work at the University of Exeter, he continues to drive innovation in low-carbon and intelligent energy solutions ⚡.

🔗 Publications

A knowledge-based safe reinforcement learning approach for real-time automatic control in a smart energy hub – Applied Energy (Under review, 2025) 🔗 Link

Enhanced Meta Reinforcement Learning for Resilient Transient Stabilization – IEEE Transactions on Power Systems (Under review, 2025) 🔗 Link

Machine learning-based economic model predictive control for energy hubs with variable energy efficiencies – Energy (First round revision, 2024) 🔗 Link

A Review of Resilience Enhancement Measures for Hydrogen-penetrated Multi-energy Systems – Proceedings of the IEEE (Under review, 2025) 🔗 Link

Coordinated Optimal Dispatch Based on Dynamic Feasible Operation Region Aggregation – IEEE Transactions on Smart Grid (First round revision, 2024) 🔗 Link

A Sequential Multi-Agent Reinforcement Learning Method for Coordinated Reconfiguration of Substation and MV Distribution Networks – IEEE Transactions on Power Systems (Under review, 2024) 🔗 Link

Enhancing Microgrid Resilience through a Two-Layer Control Framework for Electric Vehicle Integration and Communication Load Management – IEEE Internet of Things Journal (Under review, 2024) 🔗 Link

Coordinated Electric Vehicle Control in Microgrids Towards Multi-Service Provisions: A Transformer Learning-based Risk Management Strategy – Energy (Under review, 2024) 🔗 Link

Adaptive Resilient Control Against False Data Injection Attacks for a Multi-Energy Microgrid Using Deep Reinforcement Learning – IEEE Transactions on Network Science and Engineering (Under review, 2024) 🔗 Link

Muhammad Imam | FOG computing | Best Researcher Award

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Assist Prof Dr. Muhammad Imam | FOG computing | Best Researcher Award

Assistant Professor, King Fahd University of Petroleum & Minerals, Saudi Arabia

Dr. Muhammad Y. Imam is a distinguished Cybersecurity Leader and Consultant with over 20 years of experience in the fields of cybersecurity, cryptography, and blockchain. He has a proven track record of combining entrepreneurship with technical expertise, excelling in problem-solving and innovative solutions. Currently an Assistant Professor at KFUPM, Dr. Imam is committed to enhancing cybersecurity education and practice in the region. 🌐🔐

Publication Profile

ORCID

 

Strengths for the Award

  1. Extensive Expertise in Cybersecurity: Dr. Imam has over 20 years of experience in cybersecurity, with a strong background in areas such as cryptography, blockchain, and malware detection. This extensive knowledge positions him as a leader in the field.
  2. Innovative Research Contributions: His PhD research focused on botnet mitigation techniques, showcasing his ability to develop novel solutions for complex problems. This work is crucial in addressing emerging threats in cybersecurity.
  3. Academic and Administrative Leadership: As an Assistant Professor at KFUPM and former Director of the Business Incubator, Dr. Imam demonstrates strong leadership skills. He has been actively involved in various committees, contributing to policy-making and curriculum development.
  4. Impactful Publications: With a range of publications in reputable journals, including works on secure PIN-entry methods and malware classification, Dr. Imam has made significant contributions to academic literature in cybersecurity.
  5. Strong Network and Collaboration: His involvement with various organizations, such as ARAMCO and Saudi Airlines, highlights his ability to bridge academia and industry, fostering collaborations that enhance research impact.
  6. Commitment to Education: Dr. Imam’s experience in teaching, professional training, and mentoring underscores his dedication to educating the next generation of cybersecurity professionals.

Areas for Improvement

  1. Broader Research Focus: While Dr. Imam has a strong background in cybersecurity, expanding his research to include emerging fields like artificial intelligence and machine learning in security applications could further enhance his profile.
  2. Enhanced Public Engagement: Increasing participation in public forums or conferences to share his research findings could amplify his impact and visibility within the global cybersecurity community.
  3. Collaboration with Diverse Disciplines: Engaging with researchers from different fields, such as sociology or behavioral science, could provide a more holistic approach to understanding cybersecurity issues, particularly in user behavior and security practices.
  4. Grant Acquisition: Actively pursuing more research grants and funding opportunities could help elevate his projects and provide resources for broader research initiatives.

Education

Dr. Imam earned his Ph.D. in Electrical and Computer Engineering from Carleton University in Ottawa, Canada, in 2013, focusing on cybersecurity, particularly in developing techniques for botnet mitigation. He also holds a Master’s degree from KFUPM, where he graduated in June 2004, and a Bachelor’s degree from the same institution, completed in May 2000. 🎓📚

Experience

Since September 2013, Dr. Imam has served as an Assistant Professor in the Computer Engineering Department at KFUPM, where he is involved in teaching, professional training, and research projects with industry partners. He previously directed the Business Incubator at KFUPM’s Entrepreneurship Institute, managing incubation and acceleration programs to support new startups. His leadership extends to various committees, including chairing the Cybersecurity Committee at KFUPM since January 2023. 👨‍🏫💼

Research Focus

Dr. Imam’s research interests are centered around cybersecurity, focusing on cryptography, network security, and malware detection. His innovative work includes developing advanced solutions for data privacy and risk management, addressing contemporary challenges in information security. 🔍💻

Awards and Honors

Throughout his career, Dr. Imam has been recognized for his contributions to cybersecurity education and practice, receiving accolades for his research and leadership in various academic and professional capacities. He has also been involved in multiple initiatives to improve cybersecurity awareness and education in Saudi Arabia and beyond. 🏅👏

Publications

F. Binbeshr, L. Y. Por, M. L. M. Kiah, A. A. Zaidan, and M. Imam, “Secure PIN-Entry Method Using One-Time PIN (OTP),” IEEE Access, vol. 11, pp. 18121-18133, 2023.

Al Mousa, M. Al Qomri, and M. Imam, “The Predicament of Privacy and Side-Channel Attacks,” International Journal of Development and Conflict, vol. 12, no. 2, pp. 182–191, 2022.

L. Ghouti and M. Imam, “Malware Classification Using Compact Image Features and Multiclass Support Vector Machines,” IET Information Security, vol. 14, no. 4, pp. 419–429, 2020.

M. Mahmoud, M. Nir, and A. Matrawy, “A Survey on Botnet Architectures, Detection and Defences,” International Journal of Network Security, vol. 17, no. 3, pp. 272–289, 2015.

M. Mahmoud, S. Chiasson, and A. Matrawy, “Does Context Influence Responses to Firewall Warnings?,” 2012 eCrime Researchers Summit, Las Croabas, PR, USA, 2012, pp. 1-10.

Conclusion

Dr. Muhammad Y. Imam exemplifies the qualities of a strong candidate for the Best Researcher Award. His extensive expertise in cybersecurity, innovative research contributions, leadership roles, and commitment to education make him a standout figure in the field. Addressing areas for improvement, such as expanding his research focus and enhancing public engagement, could further strengthen his contributions and influence in the cybersecurity landscape. Given these strengths and opportunities, Dr. Imam is well-positioned to receive recognition for his impactful work and leadership in the realm of cybersecurity.

Bhargavi Krishnamurthy | Internet of Things | Best Researcher Award

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Dr. Bhargavi Krishnamurthy | Internet of Things | Best Researcher Award

Associate Professor, Siddaganga Institute of Technology, India

Bhargavi Krishnamurthy is a dedicated Computer Science researcher specializing in machine learning, high-performance computing, and computer security. With a strong academic foundation and international research experience, she has made significant contributions to the field through her innovative projects and publications.

Publication Profile

Scopus

Strengths for the Award

  1. Strong Academic Background: Bhargavi Krishnamurthy has an impressive academic history, including a Ph.D. in Computer Science and Engineering (CSE) with a focus on the application of machine learning in improving HPC performance. Her postdoctoral research in Software Engineering of Machine Learning systems at the University of Memphis adds to her credibility.
  2. Relevant Research Experience: Bhargavi’s research is in a highly relevant and impactful area, combining machine learning, software engineering, and high-performance computing (HPC). This multidisciplinary approach is crucial in today’s research landscape.
  3. Publications and Conferences: She has presented her research at various reputable international conferences, showcasing her work in areas like remote health monitoring, smart wearables, cloud solutions, and predictive analysis in e-commerce. This indicates a consistent contribution to her field.
  4. Global Exposure: Her postdoctoral experience at an international university (University of Memphis) reflects her exposure to global research standards and collaboration, which is a significant asset for any researcher.

Areas for Improvement

  1. Broader Publication Record: While Bhargavi has presented at conferences, it would be beneficial to see more peer-reviewed journal publications, which typically have a more rigorous review process and greater impact in the academic community.
  2. Focused Research Direction: Bhargavi’s research spans multiple topics within computer science, which is commendable. However, a more focused research trajectory with deeper contributions in one specific area might enhance her profile as an expert in that domain.
  3. Collaboration and Grants: Evidence of successful collaboration with other researchers, securing research grants, and contributing to large-scale projects could further bolster her candidacy for the award.

🎓 Education:

Bhargavi earned her Ph.D. in Computer Science and Engineering from Visveswaraya Institute of Technology in December 2020, focusing her thesis on enhancing HPC performance using machine learning. She holds an M.Tech in Computer Science and Engineering from Siddaganga Institute of Technology, Tumakuru (2012) with a CGPA of 9.02 and first-class distinction, and a B.E. in Computer Science and Engineering from Visveswaraya Institute of Technology (2009) with first-class honors. She also completed her Pre-University and SSLC education from Karnataka boards, achieving first-class grades in both.

💼 Experience:

Bhargavi served as a Postdoctoral Research Scholar at the Game Theory and Computer Security laboratory (GTCS) in the Department of Computer Science at the University of Memphis, USA, from August 2021 to February 2022. During this tenure, she conducted research on the software engineering aspects of machine learning systems. Her academic journey includes extensive research and project work during her Ph.D. and M.Tech studies, contributing to advancements in computer science.

🔬 Research Focus:

Her research primarily explores the application of machine learning to improve the performance of high-performance computing systems. Additionally, Bhargavi has delved into areas such as quality of service in wireless medical sensor networks, query translation between SQL and XPath, context-aware computing, secure data sharing using attribute-based encryption, cloud-based demographic management solutions, and predictive analysis in e-commerce.

🏆 Awards and Honours:

Throughout her academic career, Bhargavi has consistently achieved first-class distinctions, including a CGPA of 9.02 in her M.Tech and first-class honors in her B.E., reflecting her dedication and excellence in her studies.

📝 Publications:

Bhargavi Krishnamurthy has authored and co-authored several research papers presented at international conferences and published in reputable journals. Notable publications include:

“CAs-based QoS Scheme for Remote Health Monitoring over WMSN” – Presented at the International Conference on Advanced Computing, Networking and Security, NITK Surathkal, 2012. Link (Published Year: 2012, Conference Proceedings) – Cited by X articles.

“Join Queries Translation from SQL to XPath” – Published in IEEE proceedings, Tirunelveli, India, 2013. Link (Published Year: 2013, IEEE Conference) – Cited by Y articles.

“Context Aware Smart Watch” – Presented at the International Conference on Emerging Computation and Technologies (ICECIT), Elsevier Procedia, SIT, Tumkur, 2013. Link (Published Year: 2013, Elsevier Procedia) – Cited by Z articles.

“Secure Sharing of Car Using ABE” – Published in Proceedings of IRF International Conference, Mysore, 2014. Link (Published Year: 2014, Conference Proceedings) – Cited by A articles.

“Cloud based Solution to Manage Demographic Demand and Supply of Skills” – Presented at the Indian Technology Congress, NIMANS Convention Hall, Bangalore, 2014. Link (Published Year: 2014, Conference Proceedings) – Cited by B articles.

“Predictive Analysis of E-Commerce Products” – Presented at the International Conference on Intelligent Computing and Communication, Springer, MIT College of Engineering, Pune, 2017. Link (Published Year: 2017, Springer Conference Proceedings) – Cited by C articles.

Conclusion

Bhargavi Krishnamurthy is a strong candidate for the Research for Best Researcher Award, given her solid academic foundation, relevant research experience, and contributions to significant areas in computer science. To further strengthen her case, focusing on a specific research niche, expanding her publication record in high-impact journals, and demonstrating leadership in collaborative projects or grant acquisition would be beneficial.

 

Adel Hanna | Civil Engineering | Best Researcher Award

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Prof Dr. Adel Hanna | Civil Engineering | Best Researcher Award

Civil Engineering, Concordia University, Montreal, Canada

Dr. Adel M. Hanna, Ph.D., P. Eng., F.ASCE, is a distinguished Professor in the Department of Building, Civil, and Environmental Engineering at Concordia University. With a career spanning over four decades, he is renowned for his exceptional contributions to foundation engineering, including groundbreaking research, extensive publications, and influential leadership roles in professional societies.

Profile

Scopus

 

Education 📚

Dr. Hanna completed his Ph.D. in Geotechnical Engineering at the Technical University of Nova Scotia (Dalhousie University) in 1978, focusing on the bearing capacity of footings on layered soils. Prior to that, he earned his M. Eng. from Cairo University and his B. Eng. from Ain-Shams University, both with a specialization in geotechnical and structural engineering.

Experience 👨‍🔬

As a pioneer in geotechnical engineering education, Dr. Hanna introduced the field to Concordia University in 1978. He has since led extensive research endeavors, served as a consultant on various projects globally, and supervised over 100 Master’s and Doctorate degrees. His expertise extends to foundation design, soil-structure interaction, dynamics, and mechanics of foundations, among other areas.

Research Interests 🔬

Dr. Hanna’s research interests encompass a wide range of topics within foundation engineering, including experimental, numerical, and analytical investigations on shallow and deep foundations, difficult soils, and the effects of differential settlement on superstructures. He is also passionate about advancing the understanding of soil-structure interaction and dynamic behaviors of foundations.

Awards 🏆

Dr. Hanna’s contributions to the field have been recognized with prestigious awards such as the G. Geoffrey Meyerhof Award in 2010 for his outstanding contribution to foundation engineering. His dedication and excellence have also earned him recognition from professional societies like the American Society of Civil Engineers (ASCE), where he is a Fellow.

Publications

📝 Here are some of Dr. Hanna’s notable publications:

Hanna, A. M., & Meyerhof, G. G. (1978). “Bearing Capacity of Footings under Vertical and Inclined Loads on Layered Soils.” Geotechnique. Cited by this article.

Hanna, A. M. (2003). “Foundation Engineering for Difficult Soils.” Journal of Geotechnical and Geoenvironmental Engineering. Cited by this article.

Hanna, A. M. (2010). “Soil-Structure Interaction in Shell-Type Foundations.” Canadian Geotechnical Journal. Cited by this article.