Mr. Ahmed Ghazi BLAIECH | Artificial intelligence | Best Researcher Award

Mr. Ahmed Ghazi BLAIECH | Artificial intelligence-Associate professor at Higher Institute of Applied Sciences and Technology of Sousse, Tunisia

Ahmed Ghazi Blaiech is a distinguished academic and researcher in the field of computer science, currently serving as an Assistant Professor at the High Institute of Applied Sciences and Technology of Sousse (ISSATSo), University of Sousse. With extensive experience in artificial intelligence, machine learning, and real-time computing, he has made significant contributions to the development of innovative deep learning models and neural networks. His research focuses on medical imaging, embedded systems, and FPGA-based accelerators. Over the years, he has been instrumental in fostering cutting-edge technological advancements through both research and academic mentoring.

Profile:

Orcid | Scopus | Google Scholar

Education:

Ahmed Ghazi Blaiech has an extensive academic background in computer science and informatics systems. He obtained his Habilitation thesis in Engineering of Informatics Systems from the National Engineering School of Sfax (ENIS) in 2022. Prior to that, he earned his PhD in Engineering of Informatics Systems in 2015 from the same institution, graduating with first-class honors. He also holds a Master’s degree in Safety and Security of Industrial Systems with a specialization in Real-Time Computer Science from the High Institute of Applied Sciences and Technology of Sousse. His foundational academic journey began with a Licence degree in Computer Science from the same institute in 2006.

Experience:

Dr. Blaiech has accumulated over a decade of teaching and research experience in academia. Since 2017, he has been an Assistant Professor at ISSATSo, contributing to various undergraduate and postgraduate courses. Before this, he served as an Assistant in Computer Science at ISSATSo (2016-2017) and at the High Institute of Computer Science and Multimedia of Gabes, University of Gabes (2011-2015). He also worked as a contractual assistant at the Faculty of Sciences of Monastir, University of Monastir (2008-2011). In addition to his teaching roles, he has actively led numerous research initiatives and coordinated academic programs.

Research Interests:

Dr. Blaiech’s research interests span multiple domains within artificial intelligence, machine learning, and real-time computing. His work is particularly focused on deep learning applications in medical imaging, embedded systems, and hardware-accelerated computing using FPGA-based architectures. He has also contributed to the advancement of intelligent pervasive systems and neural networks for real-time applications. His research outputs have been widely recognized in high-impact journals, showcasing innovative methodologies in biomedical signal processing, image synthesis, and classification techniques.

Awards and Recognitions:

Throughout his career, Dr. Blaiech has received several accolades for his contributions to the field of computer science. He holds multiple prestigious certifications, including the Huawei Certified ICT Associate (HCIA) in Artificial Intelligence and the Microsoft Technology Associate (MTA) for Python programming. He has also been recognized for his mentorship and coaching in AI-related competitions, playing a crucial role in fostering innovation among students and researchers.

Publications:

Dr. Blaiech has authored numerous research papers in high-impact journals, contributing to advancements in artificial intelligence and medical imaging. Some of his notable publications include:

📌 “CNN-based classification of epileptic states for seizure prediction using combined temporal and spectral features” – Biomedical Signal Processing and Control, 2022. DOI 📖

📌 “An innovative medical image synthesis based on dual GAN deep neural networks for improved segmentation quality” – Applied Intelligence, 2022. DOI 📖

📌 “Comparison by multivariate auto-regressive method of epileptic seizures prediction for real patients and virtual patients” – Biomedical Signal Processing and Control, 2021. DOI 📖

📌 “Innovative deep learning models for EEG-based vigilance detection” – Neural Computing and Applications, 2020. DOI 📖

📌 “A Novel Hardware Systolic Architecture of a Self-Organizing Map Neural Network” – Computational Intelligence and Neuroscience, 2019. DOI 📖

📌 “A New Hardware Architecture for Self-Organizing Map Used for Colour Vector Quantization” – Journal of Circuits, Systems, and Computers, 2019. DOI 📖

📌 “A Survey and Taxonomy of FPGA-based Deep Learning Accelerators” – Journal of Systems Architecture, 2019. DOI 📖

Conclusion:

Dr. Ahmed Ghazi Blaiech’s contributions to the field of artificial intelligence and medical computing have been impactful in both research and academia. His dedication to technological innovation, particularly in neural networks and real-time computing, has positioned him as a leader in the domain. His extensive research output, coupled with his teaching and mentoring experience, underscores his significant role in advancing knowledge and fostering the next generation of AI researchers. Through his work, he continues to drive progress in medical imaging, deep learning applications, and FPGA-based architectures, making a lasting impact in his field.

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.

Ahmed Ghazi BLAIECH | Artificial intelligence | Best Researcher Award