Winston Dunn | Artificial Intelligence |  Best Researcher Award

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Dr. Winston Dunn | Artificial Intelligence |  Best Researcher Award

The University Of Kansas Medical Center | United States

Author Profiles

Scopus

Orcid ID

Early Academic Pursuits

Dr. Winston Dunn began his academic journey with a Bachelor of Science in Biochemistry from the University of British Columbia. He pursued his medical degree at Ross University School of Medicine and later completed advanced training at The Chicago Medical School. His strong foundation in internal medicine was built through residency at the Mayo Graduate School of Medicine, followed by specialized fellowships in Gastroenterology at the University of California, San Diego, and in Transplant Hepatology at Mayo Clinic. Parallel to his clinical training, he enriched his expertise with a Master’s in Public Health, highlighting his commitment to blending clinical practice with population health perspectives.

Professional Endeavors

Dr. Dunn’s academic career began as an Instructor in Medicine at the Mayo Clinic College of Medicine (2009–2010). He then joined the University of Kansas Medical Center as an Assistant Professor (2010–2016), rising to Associate Professor (2016–2025), and currently serves as Professor in the Division of Gastroenterology. His steady progression reflects consistent excellence in teaching, research, and clinical leadership. Additionally, his professional licensure across multiple states and board certifications in Internal Medicine, Gastroenterology, and Transplant Hepatology highlight his depth of expertise.

Contributions and Research Focus

Dr. Dunn’s research is primarily centered on liver diseases, with a special focus on nonalcoholic steatohepatitis (NASH), metabolic dysfunction-associated steatohepatitis (MASH), cirrhosis, and outcomes after hepatitis C treatment. He has been the principal investigator in numerous Phase II and Phase III clinical trials, collaborating with leading pharmaceutical companies and institutions. His studies explore genetic predictors of liver disease outcomes, non-invasive biomarkers, and novel therapeutics aimed at reversing fibrosis and improving survival. He also contributed to improving models of care, diagnosis, and patient referral systems in hepatology.

Impact and Influence

Dr. Dunn’s work has had significant clinical implications, advancing knowledge in liver transplantation, NASH therapeutics, and hepatology practice. His role in high-impact trials, including those supported by Gilead Sciences, Novo Nordisk, and Madrigal Pharmaceuticals, positions him as a leader in shaping the future of liver disease management. His active service on the AASLD Alcoholic Liver Disease Steering Committee and Education Subcommittee further demonstrates his influence on clinical guidelines, education, and policy within the hepatology community.

Academic Citations and Recognition

Dr. Dunn’s contributions have been recognized through multiple awards, including the Sheila Sherlock Clinical and Translational Research Award (2012), the AASLD Advanced Transplant Hepatology Fellowship Award (2009), and induction as a Fellow of the American Association for the Study of Liver Diseases (FAASLD) in 2023. His research has generated numerous publications and citations, reflecting his impact on both scientific literature and clinical practice.

Legacy and Future Contributions

With an established record of academic excellence, groundbreaking research, and mentorship, Dr. Dunn’s legacy lies in advancing hepatology through both innovative research and translational impact. His ongoing leadership in pivotal trials will likely redefine therapeutic standards for NASH and related liver conditions. As a Professor at the University of Kansas Medical Center, he is poised to continue mentoring future hepatologists while contributing to international collaborations that influence the global fight against liver disease.

Conclusion

In summary, Dr. Winston Dunn exemplifies the qualities of a distinguished academic physician-scientist. His rigorous training, progressive academic career, and pioneering research in hepatology underscore his suitability for honors such as the Best Researcher Award. With a career dedicated to bridging clinical care, research innovation, and education, Dr. Dunn stands as a role model whose work continues to shape the future of liver disease management and patient outcomes worldwide.

Notable Publications

“Artificial Intelligence for Predictive Diagnostics, Prognosis, and Decision Support in MASLD, Hepatocellular Carcinoma, and Digital Pathology" 

  • Author: Nicholas Dunn; Nipun Verma; Winston Dunn
  • Journal: Journal of Clinical and Experimental Hepatology
  • Year: 2025

"Prevalence and Predictors of Suspected Metabolic Dysfunction‐Associated Steatotic Liver Disease in Adolescents in the United States" 

  • Author: Sheila L. Noon; Lauren F. Chun; Tin Bo Nicholas Lam; Nhat Quang N. Thai; Winston Dunn; Jeffrey B. Schwimmer‏
  • Journal: Alimentary Pharmacology & Therapeutics
  • Year: 2025

"Comparison Between Dynamic Models for Predicting Response to Corticosteroids in Alcohol‐Associated Hepatitis: A Global Cohort Study" 

  • Author: Francisco Idalsoaga; Luis Antonio Díaz; Leonardo Guizzetti; Winston Dunn; Heer Mehta; Jorge Arnold; Gustavo Ayares; Rokhsana Mortuza; Gurpreet Mahli; Alvi H. Islam et al.
  • Journal: Alimentary Pharmacology & Therapeutics
  • Year: 2025

"Moderate alcohol-associated hepatitis: A real-world multicenter study" 

  • Author: Francisco Idalsoaga; Luis Antonio Díaz; Winston Dunn; Heer Mehta; Karen Muñoz; Vicente Caldentey; Jorge Arnold; Gustavo Ayares; Rokhsana Mortuza; Shiv K. Sarin et al.
  • Journal: Hepatology Communications
  • Year: 2025

"An artificial intelligence-generated model predicts 90-day survival in alcohol-associated hepatitis: A global cohort study" 

  • Author: Winston Dunn; Yanming Li; Ashwani K. Singal; Douglas A. Simonetto; Luis A. Díaz; Francisco Idalsoaga; Gustavo Ayares; Jorge Arnold; María Ayala-Valverde; Diego Perez et al.
  • Journal: Hepatology
  • Year: 2024

Mian Usman Sattar | Artificial Intelligence | Best Researcher Award

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Dr. Mian Usman Sattar | Artificial Intelligence | Best Researcher Award

University of Derby | United Kingdom

Author Profiles

Scopus

Orcid ID

Google Scholar

Early Academic Pursuits

Dr. Mian Usman Sattar’s academic journey reflects a sustained commitment to excellence in computing, informatics, and information systems. He began with a Postgraduate Diploma in Communication and Computer Technology from Government College University, Lahore (2002), followed by an M.Sc. in Computer Science (2004). His pursuit of international exposure led him to the United Kingdom, where he earned a Postgraduate Diploma in Computer Science (2008) and an MS in IT Management from the University of Sunderland (2010). His academic trajectory culminated in a Ph.D. in Informatics from the Malaysian University of Science and Technology (2022), under the guidance of Prof. Dr. Ang Ling Weay. Currently, he is further enhancing his expertise through a PG Certificate leading to FHEA from the University of Derby, UK (expected 2025).

Professional Endeavors

Dr. Sattar’s career spans academia, industry, and research leadership. His current role as Lecturer and Program Leader (Information Technology) at the University of Derby involves teaching diverse modules such as IT Product Design, Web Technologies, and Analytics Ethics. Prior to this, he served as Assistant Professor of Business Intelligence at Beaconhouse National University (2020–2023), where he introduced contemporary courses in analytics and emerging technologies. His earlier tenure as Assistant Professor of Information Systems at the University of Management and Technology (2014–2020) saw him direct academic programs, establish industry collaborations, and lead departmental initiatives. Beyond academia, he has contributed to industry as Deputy Manager (MIS) at AIAK International, UK, and as Unit Head for Training at Haseen Habib Corporation in Pakistan.

Contributions and Research Focus

Dr. Sattar’s research is anchored in Business Intelligence, Data Analytics, Enterprise Systems, and Information Security. He has secured multiple high-value research grants, including funding from the Pakistan Science Foundation, TWAS-COMSTECH, Malaysia Digital Economy Corporation, and the Malaysia Toray Science Foundation. His contributions extend beyond individual research, encompassing the creation of specialized academic tracks, development of curricula in disruptive technologies, and integration of industrial alliances such as with Microsoft Dynamics, Oracle, SAP, and Coursera.

Impact and Influence

Over two decades, Dr. Sattar has influenced academic landscapes in Pakistan, Malaysia, and the UK. He has mentored students on cutting-edge topics like Generative AI, Industry 4.0, and immersive technologies. As a conference chair, keynote speaker, and session leader, he has shaped dialogues on emerging business technologies. His role as a reviewer for numerous high-impact journals-including Sustainability, Frontiers in Medicine, and ACM Transactions-demonstrates his standing in the scholarly community.

Academic Citations and Recognitions

Dr. Sattar’s scholarly work is recognized through fellowships, travel grants, and the Higher Education Commission’s approval as a Ph.D. supervisor. His funded projects, often exceeding £30,000–£60,000 in value, have advanced applied research in artificial intelligence, data analytics, and enterprise systems. He is regularly invited to deliver talks at international conferences, reflecting the academic community’s acknowledgment of his expertise.

Legacy and Future Contributions

Dr. Sattar’s legacy lies in building academic bridges between industry and education, modernizing curricula, and fostering innovation-driven learning environments. His future trajectory points toward deepening his engagement with AI-driven business intelligence, strengthening global research collaborations, and influencing policy in higher education technology integration. By combining pedagogical innovation with robust research, he continues to prepare students for the demands of a data-driven global economy.

Conclusion

Dr. Mian Usman Sattar’s career exemplifies the synergy between scholarship, industry expertise, and educational leadership. From pioneering business intelligence programs to mentoring the next generation of data scientists, his work reflects both depth and breadth in the evolving field of information systems. His international academic footprint, sustained research output, and leadership roles position him as a transformative figure whose contributions will continue to shape the intersection of technology and business education.

Notable Publications

"Beyond Polarity: Forecasting Consumer Sentiment with Aspect- and Topic-Conditioned Time Series Models" 

  • Author: Mian Usman Sattar; Raza Hasan; Sellappan Palaniappan; Salman Mahmood; Hamza Wazir Khan
  • Journal: Information
  • Year: 2025

"From promotion to empathy: a content analysis of brand responses to social justice movements" 

  • Author: Dilshad, W.; Sattar, U.; Ghaffar, A.
  • Journal: Bulletin of Management Review
  • Year: 2025

"Enhancing Supply Chain Management: A Comparative Study of Machine Learning Techniques with Cost–Accuracy and ESG-Based Evaluation for Forecasting and Risk Mitigation" 

  • Author: Mian Usman Sattar; Vishal Dattana; Raza Hasan; Salman Mahmood; Hamza Wazir Khan; Saqib Hussain
  • Journal: Sustainability
  • Year: 2025

"Exploring the impact of augmented reality on medical students’ intrinsic motivation: a three-dimensional analysis" 

  • Author: Sattar, U.; Khan, H. W.; Ghaffar, A.; Raza, S.
  • Journal: Journal of Management & Social Science
  • Year: 2025

"Enhancing customer segmentation through factor analysis of mixed data (FAMD)-based approach using K-means and hierarchical clustering algorithms" 

  • Author: Sattar, U.; Ufeli, C. P.; Hasan, R.; Mahmood, S.
  • Journal: information
  • Year: 2025

Dongfang Zhao | Machine Learning | Best Researcher Award

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Prof. Dongfang Zhao | Machine Learning | Best Researcher Award

Prof. Dongfang Zhao at University of Washington, United States

🌟 Dongfang Zhao, Ph.D., is a Tenure-Track Assistant Professor at the University of Washington Tacoma and a Data Science Affiliate at the eScience Institute. With a Ph.D. in Computer Science from Illinois Institute of Technology (2015) and PostDoc from the University of Washington, Seattle (2017), Dr. Zhao’s career spans academic excellence and groundbreaking research in distributed systems, blockchain, and machine learning. His work, recognized with federal grants and best paper awards, has significantly impacted cloud computing, HPC systems, and AI-driven blockchain solutions. Dr. Zhao is an influential editor, reviewer, and committee member in prestigious venues. 📚💻✨

Professional Profile:

Google Scholar

Orcid

Education and Experience 

🎓 Education:

  • Postdoctoral Fellowship, Computer Science, University of Washington, Seattle (2017)
  • Ph.D., Computer Science, Illinois Institute of Technology, Chicago (2015)
  • M.S., Computer Science, Emory University, Atlanta (2008)
  • Diploma in Statistics, Katholieke Universiteit Leuven, Belgium (2005)

💼 Experience:

  • Tenure-Track Assistant Professor, University of Washington Tacoma (2023–Present)
  • Visiting Professor, University of California, Davis (2018–2023)
  • Assistant Professor, University of Nevada, Reno (2017–2023)
  • Visiting Scholar, University of California, Berkeley (2016)
  • Research Intern, IBM Almaden Research Center (2015), Argonne National Laboratory (2014), Pacific Northwest National Laboratory (2013)

Professional Development

📊 Dr. Dongfang Zhao is a leading voice in distributed systems, blockchain technologies, and scalable machine learning. He contributes to academia as an Associate Editor for the Journal of Big Data and serves on the editorial board of IEEE Transactions on Distributed and Parallel Systems. A sought-after reviewer and conference organizer, Dr. Zhao actively shapes the future of AI and cloud computing. With a deep commitment to mentorship, he has guided doctoral students to successful careers in academia and industry. His collaborative initiatives reflect a passion for addressing real-world challenges through computational innovation. 🌐✨📖

Research Focus

🔬 Dr. Zhao’s research emphasizes cutting-edge developments in distributed systems, blockchain, machine learning, and HPC (high-performance computing). His work delves into creating energy-efficient, scalable blockchain platforms like HPChain and developing frameworks for efficient scientific data handling. His contributions include lightweight blockchain solutions for reproducible computing and innovations in AI-driven systems like HDK for deep-learning-based analyses. Dr. Zhao’s interdisciplinary approach fosters impactful collaborations, addressing pressing technological needs in cloud computing, scientific simulations, and data analytics. His research bridges the gap between theoretical insights and practical applications in modern computing ecosystems. 🚀📊🧠

Awards and Honors 

  • 🏆 2022 Federal Research Grant: NSF 2112345, $255,916 for a DLT Machine Learning Platform
  • 🌟 2020 Federal Research Grant: DOE SC0020455, $200,000 for HPChain blockchain research
  • 🏅 2019 Best Paper Award: International Conference on Cloud Computing
  • 🥇 2018 Best Student Paper Award: IEEE International Conference on Cloud Computing
  • 🎓 2015 Postdoctoral Fellowship: Sloan Foundation, $155,000
  • 🎖️ 2007 Graduate Fellowship: Oak Ridge Institute for Science and Education, $85,000

Publication Top Notes:

1. Regulated Charging of Plug-In Hybrid Electric Vehicles for Minimizing Load Variance in Household Smart Microgrid

  • Authors: L. Jian, H. Xue, G. Xu, X. Zhu, D. Zhao, Z.Y. Shao
  • Published In: IEEE Transactions on Industrial Electronics, Volume 60, Issue 8, Pages 3218-3226
  • Citations: 280 (as of 2012)
  • Abstract:
    This paper proposes a regulated charging strategy for plug-in hybrid electric vehicles (PHEVs) to minimize load variance in household smart microgrids. The method ensures that the charging process aligns with household power demand patterns, improving grid stability and efficiency.

2. ZHT: A Lightweight, Reliable, Persistent, Dynamic, Scalable Zero-Hop Distributed Hash Table

  • Authors: T. Li, X. Zhou, K. Brandstatter, D. Zhao, K. Wang, A. Rajendran, Z. Zhang, …
  • Published In: IEEE International Symposium on Parallel & Distributed Processing (IPDPS)
  • Citations: 212 (as of 2013)
  • Abstract:
    This paper introduces ZHT, a zero-hop distributed hash table designed for high-performance computing systems. It is lightweight, scalable, and reliable, making it suitable for persistent data storage in distributed environments.

3. Optimizing Load Balancing and Data-Locality with Data-Aware Scheduling

  • Authors: K. Wang, X. Zhou, T. Li, D. Zhao, M. Lang, I. Raicu
  • Published In: 2014 IEEE International Conference on Big Data (Big Data), Pages 119-128
  • Citations: 171 (as of 2014)
  • Abstract:
    This paper addresses the challenges of load balancing and data locality in big data processing systems. A novel data-aware scheduling algorithm is proposed to improve efficiency and performance in high-performance computing environments.

4. FusionFS: Toward Supporting Data-Intensive Scientific Applications on Extreme-Scale High-Performance Computing Systems

  • Authors: D. Zhao, Z. Zhang, X. Zhou, T. Li, K. Wang, D. Kimpe, P. Carns, R. Ross, …
  • Published In: 2014 IEEE International Conference on Big Data (Big Data), Pages 61-70
  • Citations: 154 (as of 2014)
  • Abstract:
    FusionFS is a distributed file system tailored for extreme-scale high-performance computing systems. It provides efficient data storage and retrieval, supporting data-intensive scientific applications and overcoming the bottlenecks in traditional storage systems.

5. Enhanced Data-Driven Fault Diagnosis for Machines with Small and Unbalanced Data Based on Variational Auto-Encoder

  • Authors: D. Zhao, S. Liu, D. Gu, X. Sun, L. Wang, Y. Wei, H. Zhang
  • Published In: Measurement Science and Technology, Volume 31, Issue 3, Article 035004
  • Citations: 105 (as of 2019)
  • Abstract:
    This study enhances fault diagnosis for machines using a data-driven approach. By leveraging variational auto-encoders (VAEs), the method effectively handles small and unbalanced datasets, achieving high diagnostic accuracy for industrial applications.

Nithya Rekha Sivakumar | Deep Learning | Best Researcher Award

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Dr. Nithya Rekha Sivakumar | Deep Learning | Best Researcher Award

Associate Professor, Princess Nourah Bint Abdulrahman University, Saudi Arabia📖

Dr. Nithya Rekha Sivakumar is an accomplished academician and researcher, currently serving as an Associate Professor of Computer Science at the College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia. She holds a Ph.D. in Computer Science from Periyar University, India, specializing in Mobile Computing and Wireless Networks with Fuzzy and Rough Set Techniques, funded by a prestigious UGC BSR Fellowship. Dr. Sivakumar also earned her M.Phil. in Data Mining, MCA in Computer Applications, and B.Sc. in Computer Science. With over 15 years of academic experience, she has served in diverse roles across reputed institutions in India and Saudi Arabia. Her research interests include wireless networks, mobile computing, data mining, and intelligent systems, with extensive contributions as a researcher, reviewer, and speaker in international conferences and journals. A recipient of multiple awards, including the “Best Distinguished Researcher Award,” she has secured research grants and actively evaluates Ph.D. theses globally. Dr. Sivakumar is also a member of IEEE and IAENG and continues to contribute to advancements in computing through teaching, research, and scholarly activities.

Profile

Orcid Profile

Google Scholar Profile

Education Background🎓

Dr. Rekha earned her Ph.D. in Computer Science from Periyar University, India, in 2014, supported by the prestigious UGC BSR Fellowship. Her doctoral research focused on mobile computing and wireless networks with fuzzy and rough set techniques. She also holds an M.Phil. in Computer Science from PRIST University (2009), an MCA from IGNOU (2007), and a B.Sc. in Computer Science from Bharathiar University (1996).

Professional Experience🌱

Dr. Rekha has over 15 years of academic and research experience. She has been with Princess Nourah Bint Abdul Rahman University since 2017, progressing from Assistant to Associate Professor. Prior to this, she served as an Assistant Professor at Qassim Private Colleges, Saudi Arabia, and held teaching roles in leading Indian institutions such as Vivekanandha College of Arts and Sciences and Excel Business School. She has also contributed to non-academic roles, including as a Java Programmer and high school teacher.

Research and Service🔬

Dr. Rekha’s research interests span mobile computing, e-governance, and advanced data mining techniques. She has evaluated over 20 Ph.D. theses as a foreign examiner and served as a reviewer for esteemed journals such as IEEE Access, Springer, and Elsevier. A sought-after speaker, she has been invited to international seminars and conferences across the globe, sharing her expertise in computational science and emerging technologies.

Dr. Rekha continues to inspire through her teaching, research, and unwavering commitment to advancing the field of computer science.

Author Metrics 

Dr. Nithya Rekha Sivakumar has an impressive author profile, with a strong presence in international research communities. She has published over 40 papers in reputed journals and conferences, many indexed in Scopus and Web of Science, reflecting her contributions to fields like wireless networks, mobile computing, and data mining. Her work has garnered significant recognition, with an h-index of 12 and over 400 citations, underscoring the impact and relevance of her research. She has authored and co-authored book chapters published by renowned publishers such as Springer and Wiley, further highlighting her expertise. As a sought-after reviewer for top-tier journals, she actively contributes to maintaining the quality of scientific publications. Dr. Sivakumar’s research outputs, combined with her active engagement in scholarly dissemination, establish her as a leading voice in her domain.

Honors and Research Grants

Dr. Rekha has received numerous accolades, including the “Best Distinguished Researcher Award” (2015-2016) and multiple research grants from Princess Nourah Bint Abdul Rahman University, amounting to SAR 40,000 through the Fast Track Research Funding program. She has also been recognized for her doctoral research by the University Grants Commission, India, and secured a travel grant from the Indian Department of Science and Technology to present her work internationally

Publications Top Notes 📄

“Increasing Fault Tolerance Ability and Network Lifetime with Clustered Pollination in Wireless Sensor Networks”

  • Authors: TKNVD Achyut Shankar, Nithya Rekha Sivakumar, M. Sivaram, A. Ambikapathy
  • Journal: Journal of Ambient Intelligence and Humanized Computing
  • Year: 2020
  • Impact: The paper focuses on improving the fault tolerance and lifespan of wireless sensor networks through an innovative clustered pollination-based approach.

“Stabilizing Energy Consumption in Unequal Clusters of Wireless Sensor Networks”

  • Author: NR Sivakumar
  • Journal: Computational Materials and Continua
  • Volume: 64
  • Pages: 81-96
  • Year: 2020
  • Impact: This paper addresses energy stabilization in wireless sensor networks by proposing techniques to manage energy distribution across unequal clusters, enhancing network sustainability.

“Enhancing Network Lifespan in Wireless Sensor Networks Using Deep Learning-based Graph Neural Network”

  • Authors: NR Sivakumar, SM Nagarajan, GG Devarajan, L Pullagura, et al.
  • Journal: Physical Communication
  • Volume: 59
  • Article No.: 102076
  • Year: 2023
  • Impact: The paper investigates how deep learning-based graph neural networks can be used to enhance the lifespan of wireless sensor networks, marking a significant contribution to AI-powered network optimization.

“Simulation and Evaluation of the Performance on Probabilistic Broadcasting in FSR (Fisheye State Routing) Routing Protocol Based on Random Mobility Model in MANET”

  • Authors: NR Sivakumar, C Chelliah
  • Conference: 2012 Fourth International Conference on Computational Intelligence
  • Year: 2012
  • Impact: This study explores the performance of the Fisheye State Routing (FSR) protocol in mobile ad hoc networks (MANETs), with an emphasis on the effects of random mobility models on network behavior.

“An IoT-based Big Data Framework Using Equidistant Heuristic and Duplex Deep Neural Network for Diabetic Disease Prediction”

  • Authors: NR Sivakumar, FKD Karim
  • Journal: Journal of Ambient Intelligence and Humanized Computing
  • Year: 2023
  • Impact: This paper presents an IoT-based framework utilizing big data and deep learning for predicting diabetic diseases, offering a new approach to healthcare prediction systems through advanced technologies.

Conclusion

Dr. Nithya Rekha Sivakumar is a deserving candidate for the Best Researcher Award. Her impressive research accomplishments, strong publication record, innovative contributions to wireless networks and mobile computing, and active engagement in the academic community make her an outstanding researcher. Although there are areas for improvement, particularly in interdisciplinary collaboration and public outreach, her overall research trajectory and impact are exemplary. Dr. Sivakumar’s continuous pursuit of excellence in her field and her ability to address contemporary challenges in mobile computing, data mining, and wireless networks position her as a leading researcher in her domain. She is highly recommended for the Best Researcher Award.