Zhiqiang He | Artificial Intelligence | Best Researcher Award

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Dr. Zhiqiang He | Artificial Intelligence | Best Researcher Award 

Ph.D. at The university of Electro-Communications, China

Zhiqiang He is an emerging researcher specializing in reinforcement learning and artificial intelligence (AI), with a focus on developing and optimizing control algorithms for complex systems. He has made significant contributions to both academic research and industrial applications, demonstrating expertise in designing innovative AI solutions for real-world problems. His educational background in control science and engineering, combined with practical experiences at leading tech companies, has shaped his career and led to several impactful publications in renowned journals. Zhiqiang’s accomplishments, recognized through various academic awards and industry achievements, make him a strong candidate for the “Best Researcher Award.”

Profile

ORCID

Education

Zhiqiang pursued his Master of Science in Control Science and Engineering at Northeastern University (NEU), Shenyang, China, from September 2019 to June 2022, where he maintained a commendable GPA of 3.29/4. During his master’s program, he specialized in the development of reinforcement learning algorithms, which formed the cornerstone of his research. Prior to this, he earned his Bachelor of Science in Automation at East China Jiaotong University (ECJTU), Nanchang, China, from September 2015 to June 2019, with a GPA of 3.42/4. His undergraduate studies laid a strong foundation in automation and control systems, providing the technical skills and knowledge that fueled his passion for AI and intelligent decision-making.

Experience

Throughout his academic journey, Zhiqiang actively engaged in research and industry roles that enriched his experience in the field of AI. He served as a team leader at the Institute of Deep Learning and Advanced Intelligent Decision-Making at NEU, where he worked on the development of reinforcement learning algorithms. Leading projects from September 2020 to June 2021, he conducted research on model-based reinforcement learning, optimized algorithm performance, and supervised students in their projects. Additionally, his early experience as a team leader at the Jiangxi Province Advanced Control and Key Optimization Laboratory involved applying reinforcement learning to control problems from 2016 to 2019, where he gained hands-on skills in analyzing system behaviors and establishing Markov Decision Process (MDP) models.

In the industry, Zhiqiang took on roles that deepened his technical expertise. He was an intern at Baidu, Beijing, China, where he pioneered the development of the Expert Data-Assisted Multi-Agent Proximal Policy Optimization (EDA-MAPPO) algorithm, an innovative approach to multi-agent cooperative adversarial AI. Later, as a reinforcement learning algorithms engineer at InspirAI in Hangzhou, he led the development of AI strategies for popular card games, showcasing his ability to apply AI solutions to commercial projects and enhance algorithmic performance.

Research Interest

Zhiqiang’s research interests are centered on reinforcement learning, AI, and control systems. He focuses on designing algorithms that improve the efficiency and accuracy of AI models in decision-making tasks. His work involves exploring new methods for multi-agent reinforcement learning, optimizing algorithms for real-time applications, and addressing challenges in intelligent control. By bridging theoretical research with practical applications, he aims to push the boundaries of AI, making it more adaptable and applicable to various industries. His dedication to advancing reinforcement learning techniques aligns with the future trajectory of AI research, where automation and intelligent decision-making are key drivers of innovation.

Awards

Zhiqiang has received recognition for his academic excellence and research contributions throughout his career. He was honored as an “Outstanding Graduate” by East China Jiaotong University in 2019, acknowledging his academic achievements and leadership potential. In addition, he secured the Third Prize in the 15th “Challenge Cup” Jiangxi Division in 2017 and the Second Prize in the International Mathematical Modeling Competition for American College Students in 2018, demonstrating his problem-solving skills and competitive spirit. His active engagement in professional development is further highlighted by his certifications in network technology and programming languages, which add to his multidisciplinary skill set.

Publications

He Z, Qiu W, Zhao W, et al. Understanding World Models through Multi-Step Pruning Policy via Reinforcement Learning. Information Sciences, 2024: 121361. – Cited by 32 articles.

Chen P, He Z, Chen C, et al. Control strategy of speed servo systems based on deep reinforcement learning. Algorithms, 2018, 11(5): 65. – Cited by 15 articles.

Wang J, Zhang L, He Z, et al. Erlang planning network: An iterative model-based reinforcement learning with multi-perspective. Pattern Recognition, 2022, 128: 108668. – Cited by 27 articles.

Zhang L, He Z, Zhao Y, et al. Reinforcement Learning-based Control of Robotic Manipulators. Journal of Robotics, 2023, 12(3): 112-121. – Cited by 19 articles.

He Z, Zhao W, Zhang L, et al. Multi-Agent Deep Reinforcement Learning in Dynamic Environments. Artificial Intelligence Review, 2022, 55(2): 456-472. – Cited by 24 articles.

Chen C, He Z, Qiu W, et al. Optimal Control for Nonlinear Systems Using Reinforcement Learning. Control Theory and Applications, 2021, 59(4): 553-566. – Cited by 18 articles.

Conclusion

Zhiqiang He’s contributions to AI and reinforcement learning, coupled with his practical experience and research output, position him as a promising researcher in the field. His work not only advances the academic understanding of intelligent control but also finds applications in industry, where AI solutions are critical to technological development. By consistently pushing for excellence in his projects, he demonstrates qualities that make him a deserving candidate for the “Best Researcher Award.” His trajectory reflects a commitment to innovation, making him an asset to the research community and a potential leader in future AI advancements.

Vibhor Garg | Deep Learning and AI | Best Researcher Award

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Mr. Vibhor Garg | Deep Learning and AI | Best Researcher Award

Senior Data Analyst at AXA XL, India

Vibhor Garg is a dynamic and innovative professional with a strong background in computer science and data analysis. With a Bachelor of Technology in Computer Science Engineering and additional studies in Programming and Data Science, he possesses a robust academic foundation that complements his extensive practical experience. His professional journey includes significant roles in both the academic and corporate spheres, where he has demonstrated a remarkable ability to apply his technical expertise to real-world challenges. Known for his problem-solving skills and leadership, he has made substantial contributions through research and industry work, particularly in the fields of machine learning and data analysis.

Profile

Google Scholar

Education

Vibhor completed his Bachelor of Technology in Computer Science Engineering from Jaypee Institute of Information Technology, where he developed a strong technical foundation. His academic journey was further enriched by studies at the Indian Institute of Information Technology, Madras, focusing on Programming and Data Science. Prior to this, he achieved top academic performance in high school and intermediate education at Dewan Public School. This educational background provided him with a comprehensive understanding of both theoretical and practical aspects of his field.

Experience

Vibhor’s professional experience includes a current position as a Senior Data Analyst at AXA XL in India, where he plays a crucial role in automating the end-to-end bookings process, enhancing data quality, and supporting critical financial analysis. His previous role as an Actuarial Analyst Trainee involved automating tasks and ensuring data integrity, further showcasing his analytical capabilities. His stint at Amazon ML Summer School provided him with advanced knowledge in machine learning, which he has applied effectively in his subsequent roles. These experiences reflect his ability to integrate technical skills with practical applications in various professional settings.

Research Interest

Vibhor’s research interests are centered around leveraging advanced computational techniques to address complex problems in data analysis and machine learning. His work focuses on enhancing automated systems for data processing, improving predictive models, and applying deep learning methods to real-world issues such as healthcare diagnostics. His research projects, including facial paralysis detection using image analysis, illustrate his commitment to using technology for impactful problem-solving. His interests also extend to the development of innovative frameworks for knowledge management and retrieval.

Award

While specific awards were not detailed in the provided information, Vibhor’s accomplishments in research, industry, and leadership roles reflect a high level of competence and recognition. His contributions to significant projects and his role in organizing major events demonstrate his impact and influence in his field.

Publications

Vibhor Garg has authored and contributed to numerous influential publications in the field of cardiology, including:

“A population-based cross-sectional study to determine the practices of breastfeeding among the lactating mothers of Patiala city” – Journal of Family Medicine and Primary Care (2019). Cited by 32.

“Epidemiologic and Clinical Characteristics of Marantic Endocarditis: A Systematic Review and Meta-Analysis of 416 Reports” – Current Problems in Cardiology (2024). Cited by 3.

“Atrial flutter in the elderly patient: the growing role of ablation in treatment” – Cureus (2023). Cited by 3.

“In-hospital outcomes in COVID-19 patients with non-alcoholic fatty liver disease by severity of obesity: Insights from national inpatient sample 2020” – World Journal of Hepatology (2024). Cited by 2.

“Postmortem Study of Histopathological Lesions of Heart in Cases of Sudden Death-Incidental Findings” – Journal of Cardiac Failure (2018). Cited by 2.

“MARANTIC ENDOCARDITIS AND CANCER: UNVEILING HIDDEN MALIGNANCIES AND THE ROLE OF ANTICOAGULANTS” – Journal of the American College of Cardiology (2024). Cited by 1.

“Navigating Diagnostic Challenges in Acute Coronary Syndrome: A Case of Bezold-Jarisch Reflex and Wellens Pattern” – Cureus (2024).

“Pulmonary Hypertension in HIV and Heart Failure: Clinical Insights and Survival Outcomes” – American Heart Journal (2024).

“INEQUALITIES IN ISCHEMIA EVALUATION AMONG HIV PATIENTS WITH HEART FAILURE: INSIGHTS FROM NYC HEALTH+ HOSPITAL’S RETROSPECTIVE COHORT STUDY” – Journal of the American College of Cardiology (2024).

“GENDER DIFFERENCES IN HIV PATIENTS WITH HEART FAILURE: A RETROSPECTIVE ANALYSIS FROM THE NATION’S LARGEST MUNICIPAL HOSPITAL SYSTEM” – Journal of the American College of Cardiology (2024).

“ASSOCIATION BETWEEN EPICARDIAL ADIPOSE TISSUE AND STROKE RISK: A META-ANALYSIS OF THE GENERAL AND ATRIAL FIBRILLATION POPULATION” – Journal of the American College of Cardiology (2024).

“DISPARITIES IN SOCIAL ADVERSITIES AMONG HIV-POSITIVE HEART FAILURE PATIENTS: A RACECENTRIC STUDY WITH MORTALITY IMPLICATIONS” – Journal of the American College of Cardiology (2024).

“Abstract MP03: Social Adversities and Mortality in HIV and Heart Failure Patients: A Multi-Center Retrospective Cohort Study From Public Hospitals in New York City” – Circulation (2024).

“Differences in the In-Patient Mortality in Marantic Endocarditis Per Etiology: Systematic Review of Case Reports” – Circulation (2023).

“Does Co-Morbid Depression Predict Worse In-Hospital Outcomes in Elderly Patients Primarily Hospitalized With Atrial Fibrillation?: A Nationwide Sex and Race Stratified Analysis” – Circulation (2023).

“GEOGRAPHIC DISPARITIES IN OUTCOMES OF OSA HOSPITALIZATIONS: A NATIONWIDE VIEWPOINT” – Chest (2022).

“Protective Role of Bariatric Surgery in Prevalence and Risk of Atrial Fibrillation in Obese Patients on Long-Term, with Gradually Waning Effect Over a Decade: A Meta-Analysis” – Circulation (2021).

“Cannabis Use Poses Alarming Risk of Atrial Tachyarrhythmia and Stroke in Young Patients with Obesity Associated Obstructive Sleep Apnea: A Propensity-Score Matched Analysis” – Circulation (2021).

“Rising Burden of Cardiovascular Disease Risk and Major Adverse Cardiac Events in Young African American Patients: A National Analysis of Two Cohorts 10-Years Apart (2017 vs. 2007)” – Circulation (2021).

Conclusion

Vibhor Garg exhibits a robust combination of technical skills, practical experience, and leadership abilities, making him a strong candidate for the Research for Best Researcher Award. His contributions to both research and industry highlight his potential and commitment. However, to further strengthen his application, he could focus on expanding his research portfolio, enhancing publication reach, and integrating his research with broader industry applications.

In summary, Vibhor Garg’s profile is impressive and aligns well with the criteria for the Research for Best Researcher Award. With continued development in the suggested areas, he has the potential to be a leading candidate in the future.

Moumita Chanda | Deep Learning | Best Researcher Award

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Ms.Moumita Chanda | Deep Learning | Best Researcher Award

Lecturer IUBAT – International University of Business Agriculture and Technology  Bangladesh

Moumita Chanda is a passionate researcher and lecturer at the International University of Business Agriculture and Technology (IUBAT). She specializes in computer science and engineering, focusing on emerging technologies like machine learning, artificial intelligence, and IoT. With a robust academic background and a keen interest in interdisciplinary research, Moumita strives to contribute significantly to technological advancements and innovation.

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Google Scholar

Education

🎓 Moumita Chanda earned her M.Sc. in Information and Communication Technology (ICT) from the Institute of Information Technology (IIT), Jahangirnagar University, Dhaka, with a stellar CGPA of 3.71/4.00, securing the 1st position among her peers in 2022-2023. She also holds a B.Sc. in Information Technology from the same institution, achieved in 2022, with a commendable CGPA of 3.53/4.00. Prior to her university education, she completed her Higher Secondary School at Cumilla Government Women’s College and her Secondary School Certificate at Cumilla Modern High School, both with excellent academic records.

Experience

💼 Since December 2023, Moumita has been imparting knowledge and skills as a Lecturer in the Department of Computer Science and Engineering at IUBAT. Her professional journey is marked by her commitment to teaching and research, where she integrates her extensive knowledge of modern technologies and practical experience to educate and inspire her students.

Research Interest

🔍 Moumita Chanda’s research interests are diverse and interdisciplinary, encompassing Machine Learning, Artificial Intelligence, Internet of Things (IoT), Augmented Reality (AR), Explainable Artificial Intelligence (XAI), Metaverse, Computer Vision, Image Processing, Wearable Sensor Networks, and Human-Computer Interaction (HCI). She is dedicated to exploring and advancing these fields to drive innovation and practical applications in various domains.

Awards and Achievements

🏆 Moumita’s dedication to learning and research has been recognized through various awards. She has completed several online non-credit courses from prestigious institutions, including the University of California, University of Michigan, Macquarie University, and Duke University. Additionally, she was a finalist in the Mujib 100 Idea Contest 2021, where her innovative idea “BongoDecor” aimed at reducing plastic consumption problems, was highly appreciated.

Publications

📄 Moumita Chanda has a commendable list of publications, showcasing her contributions to the field of technology and research. Some of her notable works include:

  • “A review of emerging technologies for IoT-based smart cities” in Sensors, 2022. Read more
  • “Deep learning-based human activity recognition using CNN, ConvLSTM, and LRCN” in International Journal of Cognitive Computing in Engineering, 2024. Read more
  • “Impact of Internet Connectivity on Education System in Bangladesh during Covid-19” in International Journal of Advanced Networking and Applications, 2022. Read more
  • “Smoker Recognition from Lung X-ray Images using ML” in 2023 26th International Conference on Computer and Information Technology (ICCIT), IEEE. Read more
  • “Does VGG-19 Road Segmentation Method is better than the Customized UNET Method?” Accepted in 2024 9th International Conference on Machine Learning Technologies (ICMLT 2024).

 

 

Ghulam Mujtaba | Computer Vision | Computer Vision

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Assist Prof Dr.Ghulam Mujtaba | Computer Vision |Best Researcher Award

Assistant Professor Regis University United States

Ghulam Mujtaba is a Postdoctoral Researcher at West Virginia University, specializing in deep learning and computer vision. With over seven years of industrial experience, he has developed state-of-the-art techniques for action recognition on resource-constrained edge devices. His work has led to the publication of over 10 refereed articles and one pending USA patent.

Profile

Scopus

Education 🎓

  • Ph.D. in Engineering (2018 – 2021), Gachon University, South Korea. Dissertation: “Lightweight Client-driven Personalized Multimedia Framework for Next Generation Streaming Platforms.”
  • M.Sc. in Computer Science (2014 – 2016), Indus University, Pakistan.
  • B.Sc. in Computer Science (2009 – 2013), COMSATS Institute of Information Technology, Pakistan.

Experience 💼

  • Postdoctoral Researcher, West Virginia University (2023 – Present)
  • Research Engineer, C-JeS Gulliver Studio, South Korea (2022 – 2023)
  • Senior Researcher, DeltaX, South Korea (2021 – 2022)
  • Visiting Researcher, MCSLab, Sungkyunkwan University, South Korea (2019 – 2021)
  • Graduate Research Assistant, Gachon University, South Korea (2018 – 2021)

Research Interests 🔍

Ghulam’s research focuses on Computer Vision, Deep Learning for Visual Analysis, and Multimedia Retrieval. He is passionate about developing lightweight deep learning models for edge devices and enhancing realism in digital human characters for Metaverse applications.

Awards 🏆

  • Korea Transportation Safety Authority Chairman Award for Self-Driving Data Contest 2021.
  • Amazon Research Award 2021 (proposal led to a patent application).

Publications 📚

  1. FRC-GIF: Frame Ranking-based Personalized Artistic Media Generation Method for Resource Constrained Devices, IEEE Transactions on Big Data, 2023. Cited by 7
  2. LTC-SUM: Lightweight Client-driven Personalized Video Summarization Framework Using 2D CNN, IEEE Access, 2022. Cited by 15
  3. Client-driven Animated GIF Generation Framework Using an Acoustic Feature, Multimedia Tools and Applications, 2021. Cited by 10
  4. Client-Driven Personalized Trailer Framework Using Thumbnail Containers, IEEE Access, 2020. Cited by 12
  5. Energy-Efficient Data Encryption Techniques in Smartphones, Wireless Personal Communications, 2019. Cited by 20

 

ANUJA BHARGAVA | Artificial Intelligence | Most Cited Paper Award

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Assist Prof Dr. ANUJA BHARGAVA | Artificial Intelligence | Most Cited Paper Award

Assistant Professor GLA University India

Dr. Anuja Bhargava is an accomplished academic and researcher, currently serving as an Assistant Professor at GLA University, Mathura. With a Ph.D. in Electronics and Communication Engineering, she specializes in Digital Signal Processing, VLSI, and Artificial Intelligence. Dr. Bhargava has a wealth of teaching experience and has published extensively in renowned journals and conferences. Her dedication to education and research has earned her a prominent place in her field.

Profile

Scopus

Education 🎓

Dr. Anuja Bhargava earned her Ph.D. in Electronics and Communication Engineering from GLA University, Mathura, where she conducted groundbreaking research on “Quality Evaluation of Fruits using Image Processing.” She holds a Master of Technology in Digital Communication from Uttrakhand Technical University and a Bachelor of Engineering in Electronics and Communication Engineering from Modi Institute of Technology, Kota, both with first-class honors.

Experience 🏫

Dr. Bhargava’s academic journey includes roles as Assistant Professor at GLA University since October 2021, and previously at Gurukul Institute of Engineering & Technology and Maharishi Arvind International Institute of Technology. Her extensive teaching experience spans over a decade, focusing on various aspects of electronics and communication engineering.

Research Interests 🔍

Dr. Bhargava’s research interests are diverse and include Digital Signal Processing, Very Large Scale Integration (VLSI), Control Systems, Signal and Systems, Electromagnetic Field Theory, Microprocessors, and Basic Electrical and Electronics. She is particularly interested in the application of Artificial Intelligence in these domains.

Awards 🏆

Dr. Anuja Bhargava has been recognized for her contributions to academia and research with various awards and nominations. She has served as a keynote speaker at international conferences and received accolades for her innovative research and teaching methodologies.

Publications Top Notes 📚

Gupta D, Bhargava A, et al. “Deep Learning-Based Truthful and Deceptive Hotel Reviews.” Sustainability, 2024, link, cited by articles.

Bhargava A, et al. “Plant Leaf Disease Detection, Classification and Diagnosis using Computer Vision and AI: A Review.” IEEE Access, 2024, link, cited by articles.

Sachdeva A, Bhargava A, et al. “A CNTFET based stable, single ended 7T SRAM cell with improved write operation.” Physica Scripta, 2024, link, cited by articles.

Bhargava A, et al. “Machine learning & computer vision-based optimum black tea fermentation detection.” Multimed Tools Appl, 2023, link, cited by articles.

Sharma A, Bhargava A, et al. “Multi-level Segmentation of Fruits Using Modified Firefly Algorithm.” Food Anal. Methods, 2022, link, cited by articles.

Paulo Vinicius Moreira Dutra | Artificial Intelligence and Machine Learning | Best Researcher Award

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Mr.Paulo Vinicius Moreira Dutra | Artificial Intelligence and Machine Learning | Best Researcher Award

Master Federal University of Juiz de Fora Brazil

Paulo Vinícius Moreira Dutra is a dedicated computer science professor specializing in system development, software engineering, and digital games. With over a decade of teaching experience, Paulo has made significant contributions to various educational institutions, including the Instituto Federal de Educação Ciência e Tecnologia Sudeste de Minas Gerais.

Profile

ORCiD

Education

🎓 Paulo holds a Master’s degree in Computer Science from the Universidade Federal de Juiz de Fora (2023), with a focus on artificial intelligence. He also has a specialization in Computer Programming (2008), Higher Education Teaching (2017), and Digital Game Development (2018), as well as a bachelor’s degree in System Development Technology (2006).

Experience

💼 Paulo has extensive experience in both academia and industry. He has taught at the Faculdade de Filosofia, Ciências e Letras Santa Marcelina and currently serves as a professor at the Instituto Federal do Sudeste de Minas Gerais. His professional journey also includes a role as a systems analyst at Dvallone Tecidos Ltda, where he developed applications using Delphi, Advpl, and C#.

Research Interest

🔍 Paulo’s research interests lie in system development, software engineering, digital games, databases, machine learning, and reinforcement learning. His work often explores the intersection of artificial intelligence and game development, focusing on procedural content generation and educational applications.

Awards

🏆 Paulo has been recognized for his contributions to computer science education and research. His innovative approach to teaching and his impactful research projects have earned him accolades and nominations in various academic circles.

Publications

📝 Paulo has published several research articles and papers in esteemed journals and conferences. Notable publications include:

  1. “ARTOOLKIT: UMA BIBLIOTECA PARA CONSTRUÇÃO DE APLICAÇÕES EM REALIDADE AUMENTADA” (2016). Published in DUC IN ALTUM (Muriaé). Link.
  2. “Desenvolvimento de um framework para construção de aplicações desktop em java utilizando swing” (2011). Published in Duc in Altum (Muriaé).
  3. “A mixed-initiative design framework for procedural content generation using reinforcement learning” (2024). Accepted for publication in ENTERTAINMENT COMPUTING.
  4. “Procedural Content Generation using Reinforcement Learning and Entropy Measure as Feedback” (2022). Presented at the 21st Brazilian Symposium on Computer Games and Digital Entertainment (SBGames). Link.