Vibhor Garg | Deep Learning and AI | Best Researcher Award

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.

Fatemeh Golpayegani | Artificial Intelligence | Best Researcher Award

Dr. Fatemeh Golpayegani | Artificial Intelligence | Best Researcher AwardΒ 

Assistant Professor | University College Dublin | Ireland

πŸ“œ Short Bio:

Fatemeh Golpayegani is currently an Assistant Professor at the School of Computer Science, University College Dublin (UCD), where she contributes significantly to research and academic activities in the field of computer science. Her expertise lies in multi-agent systems, edge computing, and intelligent transport systems.

Profile:

SCOPUS

πŸŽ“ Education:

Fatemeh pursued her academic journey with a strong foundation in computer science:

  • Ph.D. in Computer Science (2013-2018)
    Trinity College Dublin, Dublin, Ireland
    Thesis Title: “Collaboration community formation in open systems for agents with multiple goals.”
    Supervised by Prof. Siobhan Clarke.
  • M.Sc. in Computer (Software) Engineering (2010-2012)
    Sharif University of Technology, Tehran, Iran
    Thesis Title: “Development of a process line engineering approach based on product line engineering methods for engineering agent-oriented methodologies.”
  • B.Sc. Hons in Computer (Software) Engineering (2006-2010)
    Alzahra University, Tehran, Iran

πŸ‘©β€πŸ« Experience:

Fatemeh has held various academic and professional roles:

  • Assistant Professor (Dec 2020 – Present)
    School of Computer Science, UCD, Dublin, Ireland
  • Postdoctoral Researcher (June 2018 – Jan 2019)
    CONNECT, School of Computer Science and Statistics, Trinity College Dublin, Ireland
  • Software Engineer (Sept 2010 – Aug 2013)
    ITOrbit, Tehran, Iran

πŸ” Research Interest:

Her research interests encompass:

Multi-agent Systems, Edge Computing, Intelligent Transport Systems, Agent-based Modeling

πŸ† Award:

Fatemeh Golpayegani is recognized as a member of the Young Academy of Ireland (2023-2027), highlighting her contribution to advancing research and cultural life in Ireland.

πŸ“š Publications:

Fatemeh has contributed significantly to her field with numerous peer-reviewed publications. A selection of her notable works include:

Adaptation in Edge Computing: A review on design principles and research challenges
Published in ACM Transactions on Autonomous and Adaptive Systems, 2024. Cited by: 15

Handling uncertainty in self-adaptive systems: an ontology-based reinforcement learning model
Published in Journal of Reliable Intelligent Environments, 2023. Cited by: 20

Towards the Use of Hypermedia MAS and Microservices for Web Scale Agent-Based Simulation
Published in SN Computer Science, 2022.

Intelligent Shared Mobility Systems: A Survey on Whole System Design Requirements, Challenges and Future Direction
Published in IEEE Access, 2022.

Using Social Dependence to Enable Neighbourly Behaviour in Open Multi-agent Systems
Published in ACM Transactions on Intelligent Systems and Technology (TIST), 2019.

These publications underscore her research breadth and impact in areas such as adaptive systems, shared mobility, and multi-agent collaboration.