Mohammad Javad Mahmoodabadi | AI Engineering | Best Paper Award

Assoc. Prof. Dr. Mohammad Javad Mahmoodabadi | AI Engineering | Best Paper Award

Assoc. Prof. Dr. Mohammad Javad Mahmoodabadi | AI Engineering – Associate Professor at Sirjan University of Technology, Iran

Dr. Mohammad Javad Mahmoodabadi is an accomplished academic and researcher, currently serving as an Associate Professor in the Department of Mechanical Engineering at Sirjan University of Technology, Iran. With an impressive track record in mechanical engineering and control theory, Dr. Mahmoodabadi has made significant contributions to the fields of optimization algorithms, machine learning, and mechanical design. He is highly regarded for his innovative approaches in robotics, control engineering, and computational methods. His research has been widely published and cited, establishing him as a leader in his area. Dr. Mahmoodabadi has also played an instrumental role in mentoring graduate students, guiding them through cutting-edge research in nonlinear systems and robotics.

Professional Profile

ORCID | Scopus

Education

Dr. Mahmoodabadi’s educational background reflects a solid foundation in mechanical engineering. He earned his Ph.D. in Mechanical Engineering from the University of Guilan, Iran, in 2012. His dissertation focused on the multi-objective optimization of linear and nonlinear controllers, combining powerful optimization techniques such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). During his Ph.D., Dr. Mahmoodabadi achieved excellent academic performance, earning a GPA of 18.80 out of 20 and a dissertation grade of 19 out of 20. Prior to this, he completed his Master’s degree in Mechanical Engineering at Shahid Bahonar University of Kerman, Iran, where his thesis dealt with elasto-static problems using meshless methods. His academic achievements have provided him with a deep understanding of both theoretical and applied mechanics, which have been pivotal in his research career.

Experience

Dr. Mahmoodabadi’s academic career spans over a decade, during which he has held several important positions. After earning his Ph.D., he served as an Assistant Professor at Sirjan University of Technology from 2012 to 2019, before advancing to the role of Associate Professor. Throughout his career, he has taught various undergraduate and graduate courses, including robotics, control of robots, linear control, fuzzy logic, and optimization. His extensive teaching experience in mechanical engineering and related disciplines has earned him recognition for his ability to convey complex concepts with clarity. In addition to his teaching roles, Dr. Mahmoodabadi has served as the head of the Department of Mechanical Engineering and the Graduate Student Office at his university. His leadership has contributed to the development of academic programs and research initiatives within the department.

Research Interests

Dr. Mahmoodabadi’s research interests are diverse, with a primary focus on control theory, machine learning, computational methods, and optimization algorithms. He has worked on various topics such as adaptive robust control, fuzzy logic systems, and multi-objective optimization in the context of nonlinear dynamic systems. His research also extends to robotics, where he has developed novel control strategies for autonomous systems. Additionally, Dr. Mahmoodabadi’s work on mechanical design and analysis of complex systems has led to innovative solutions in both theoretical and applied engineering. His approach integrates computational techniques with practical applications, particularly in optimization and control engineering.

Awards

Throughout his career, Dr. Mahmoodabadi has received numerous accolades for his contributions to research and teaching. His excellence in academic leadership and groundbreaking research has earned him recognition within his institution and the broader academic community. Notably, his work in the development of control algorithms and optimization methods has received significant attention from his peers, reflected in his high citation count and his role as a mentor to graduate students. Although Dr. Mahmoodabadi has not explicitly listed awards in the traditional sense, his impact on the academic and research community through his publications, patents, and leadership roles can be considered as a testament to his achievements.

Publications

M.J. Mahmoodabadi, N.R. Babak, Pareto optimum design of an adaptive robust backstepping controller for an unmanned aerial vehicle, Asian Journal of Control (2022). 📚
R. Abedzadeh Maafi, S. Etemadi Haghighi, M.J. Mahmoodabadi, A novel multi-objective optimization algorithm for Pareto design of a fuzzy full state feedback linearization controller applied on a ball and wheel system, Transactions of the Institute of Measurement and Control 44 (7) (2022), 1388–1409. 🛠
M.J. Mahmoodabadi, S. Hadipour Lakmesari, Optimal design of an adaptive robust controller using a multi-objective artificial bee colony algorithm for an inverted pendulum system, Transactions of the Canadian Society for Mechanical Engineering 46 (1) (2022), 89–102. 📈
S.H. Lakmesari, M.J. Mahmoodabadi, Adaptive sliding mode control of HIV-1 infection model, Informatics in Medicine Unlocked 25 (2021), 100703. 💡
M.J. Mahmoodabadi, Moving least squares approximation-based online control optimized by the team game algorithm for Duffing-Holmes chaotic problems, Cyber-Physical Systems 7 (2) (2021), 1-21. ⚙️
M.J. Mahmoodabadi, A.R. Nemati, A new optimum numerical method for analysis of nonlinear conductive heat transfer problems, Journal of the Brazilian Society of Mechanical Sciences and Engineering 43 (5) (2021), 1-8. 🔥
R. Abedzadeh Maafi, S. Etemadi Haghighi, M.J. Mahmoodabadi, Pareto optimal design of a fuzzy adaptive hierarchical sliding-mode controller for an XZ inverted pendulum system, IETE Journal of Research (2021). 🔄

Conclusion

Dr. Mohammad Javad Mahmoodabadi’s academic and research career exemplifies excellence in mechanical engineering and control systems. His innovative work in optimization algorithms, machine learning, and mechanical design has earned him recognition as a leader in his field. With a strong publication record and significant contributions to the academic community, he is a well-deserving candidate for the “Best Researcher Award.” His ability to blend theoretical advancements with practical applications, along with his mentorship of future researchers, positions him as a key figure in the development of engineering solutions for complex systems. Dr. Mahmoodabadi’s dedication to advancing knowledge, combined with his academic leadership and impactful research, makes him an outstanding nominee for this prestigious award.

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.