Mr. Mohamed Hamroun | Healthcare | Breakthrough Research Award

Mr. Mohamed Hamroun | Healthcare | Breakthrough Research Award

Mr. Mohamed Hamroun | Healthcare | XLIM/ University of Limoges | France

Dr. Mohamed Hamroun is an accomplished computer scientist and engineer specializing in artificial intelligence, image processing, and multimodal information retrieval. Currently serving as a researcher and lecturer at the 3iL School and the XLIM Laboratory at the University of Limoges, France, he has made significant contributions to the fields of deep learning, computer vision, and semantic data indexing. His multidisciplinary expertise spans across AI, VR/AR systems, big data analytics, and intelligent information retrieval systems, positioning him as a leading researcher in computational intelligence and multimedia data analysis. Through his work, Dr. Hamroun has advanced both theoretical understanding and practical applications of machine learning and artificial intelligence for complex visual and semantic data challenges.

Professional Profile

Google Scholar

Summary of Suitability for the “Breakthrough Research Award” 

Dr. Mohamed Hamroun is an exceptionally qualified candidate for the Research for Breakthrough Research Award, demonstrating a strong academic foundation, extensive research experience, and impactful scientific contributions in the fields of artificial intelligence (AI), image processing, deep learning, and multimodal information retrieval.

Education

Dr. Hamroun’s academic journey reflects a deep commitment to advancing computer science and AI-driven data analysis. He earned his Ph.D. in Computer Science from the University of Bordeaux, where his doctoral research focused on “Indexing and retrieval by visual, semantic, and multi-level content of multimedia documents,” under the supervision of Professors Henri Nicolas and Ikram Amous. His doctoral work bridged the gap between computational semantics and large-scale multimedia information retrieval. He later completed his Habilitation to supervise research at the University of Limoges, where his postdoctoral contributions were consolidated into a major research theme titled “Contributions to indexing and information retrieval: application to generalist and medical multimodal data,” under the guidance of Professor Damien Sauveron. Before his doctoral studies, he obtained a Computer Engineering degree from the University of Sfax, Tunisia, and a Bachelor’s degree in Computer Science from the same institution. His undergraduate and graduate projects revolved around multilingual search engine development and database management systems, establishing his foundation in applied informatics and intelligent systems.

Professional Experience

Dr. Hamroun’s professional experience demonstrates a steady trajectory of academic excellence and applied innovation. He began his career as an R&D Engineer at SIM-SOFT in Tunisia, where he was involved in software development and data-driven industrial applications. Following this, he pursued his Ph.D. research jointly between the University of Bordeaux and the University of Sfax, working on hybrid semantic and visual content retrieval models. After completing his Ph.D., he joined the XLIM Laboratory at the University of Limoges as a Postdoctoral Researcher, where he focused on the integration of deep learning and ontology-based frameworks for medical and multimedia data analysis. Later, he was appointed as a Lecturer at EILCO Engineering School in France, contributing to both teaching and research in computer science and artificial intelligence. He now holds the position of Associate Professor at 3iL Engineering School, affiliated with the XLIM Laboratory, where he supervises research projects and mentors graduate students in AI, machine learning, and multimedia information systems.

Research Interests

Dr. Hamroun’s research interests cover a wide spectrum of computational and artificial intelligence domains. His core expertise includes image and signal processing, deep learning architectures for data classification and clustering, virtual and augmented reality applications, and semantic data mining. His studies often combine statistical learning, ontology modeling, and multimodal data fusion to enhance human-computer interaction and knowledge extraction. A significant part of his current research focuses on developing intelligent systems for multimodal medical data retrieval and applying AI to improve healthcare diagnostics and decision support. His recent work also extends to federated learning frameworks and semantic interpretation in multimedia environments, bridging applied computer science with real-world AI applications.

Awards

Dr. Hamroun has been recognized for his innovative research in artificial intelligence and multimedia information systems through various academic honors and nominations. His outstanding work in deep learning-based image analysis and computational semantics has earned him recognition among peers in the international AI research community. He has contributed as a co-author to several highly cited papers and participated in collaborative European research projects aimed at integrating AI into real-world industrial and medical systems. His nomination for the award highlights his leadership in combining artificial intelligence with practical problem-solving across domains such as emotion recognition, diabetic foot ulcer diagnosis, and semantic retrieval.

Publication Top Notes

  • Title: Emotion recognition from speech using spectrograms and shallow neural networks
    Authors: A. Slimi, M. Hamroun, et al.
    Year: 2020
    Citations: 47

  • Title: DFU-Siam: A novel diabetic foot ulcer classification with deep learning
    Authors: M. S. A. Toofanee, M. Hamroun, et al.
    Year: 2023
    Citations: 43

  • Title: A survey on intention analysis: successful approaches and open challenges
    Authors: M. Hamroun
    Year: 2020
    Citations: 21

  • Title: An interactive engine for multilingual video browsing using semantic content
    Authors: M. B. Halima, M. Hamroun, et al.
    Year: (arXiv preprint, circa 2013)
    Citations: 16

  • Title: DFU-Helper: Innovative framework for longitudinal diabetic foot ulcer evaluation using deep learning
    Authors: M. S. A. Toofanee, M. Hamroun, et al.
    Year: 2023
    Citations: 11

Dr. Xiaosuo Wang | Point-of-Care | Best Researcher Award

Dr. Xiaosuo Wang | Point-of-Care | Best Researcher Award

Dr. Xiaosuo Wang | Point-of-Care | The University of Sydney | Australia

Assoc. Prof. Dr. Dr. Xiaosuo Wang is an accomplished academic and biomedical researcher at The University of Sydney, Australia, renowned for his contributions to cardiac metabolism, molecular sensing, and translational biomedical engineering. With a solid academic foundation culminating in a Ph.D. in Biomedical Engineering from a leading Australian university, Dr. Wang has dedicated his career to exploring the complex interplay between metabolic remodeling, molecular expression, and cardiac function. His professional experience encompasses teaching, mentoring, and conducting multidisciplinary research across biomedical signal analysis, metabolic sensing, and age-associated cardiovascular studies, combining advanced imaging, computational modeling, and molecular profiling techniques. Over the years, Dr. Wang has developed a deep research interest in the mechanisms of heart failure, mitochondrial bioenergetics, metabolic regulation, and the role of novel biomarkers in cardiac health, contributing to advancements in personalized medicine and therapeutic strategies. His research skills are reflected in his expertise in multi-omics integration, biosensor development, data-driven analysis, and experimental validation, supporting high-quality publications in internationally recognized journals such as European Journal of Heart Failure, Circulation Research, and Aging Cell. Dr. Wang has authored 38 peer-reviewed papers with 772 citations and an h-index of 17, underscoring the global recognition and scholarly impact of his work. He has collaborated with over 200 international co-authors, demonstrating his commitment to fostering scientific cooperation and innovation. His achievements have been recognized through multiple academic honors, invited lectureships, and leadership roles in research consortia advancing metabolic sensing technologies. Beyond research, he actively engages in mentoring doctoral students and postdoctoral scholars, contributing to the development of the next generation of biomedical engineers and clinicians. Dr. Wang’s professional affiliations include memberships in IEEE, the American Heart Association, and the Australasian Society for Biomaterials, reflecting his dedication to interdisciplinary advancement and scientific service. His continuous pursuit of excellence has positioned him as a thought leader in the intersection of engineering and medicine, promoting innovation in sensing-based diagnostics and metabolic therapies.

Professional Profile: ORCID | Scopus

Selected Publications 

  1. Wang, X., et al. (2025). Mechanical unloading is accompanied by reverse metabolic remodelling in the failing heart: Identification of a novel citraconate-mediated pathway. European Journal of Heart Failure,

  2. Wang, X., et al. (2025). The Heart Has Intrinsic Ketogenic Capacity that Mediates NAD+ Therapy in HFpEF. Circulation Research, 2 citations.

  3. Wang, X., et al. (2025). The Human Cardiac “Age-OME”: Age-Specific Changes in Myocardial Molecular Expression. Aging Cell,

  4. Wang, X., et al. (2024). Metabolic Reprogramming in the Heart: Integrating Molecular Sensing and Therapeutic Insights. Frontiers in Cardiovascular Medicine, 15 citations.

  5. Wang, X., et al. (2023). Bioenergetic Sensing and Molecular Adaptation in Cardiac Aging and Failure. Journal of Molecular and Cellular Cardiology, 20 citations.

Dr. Suvendu Mohanty | Health Monitoring | Best Sensor for Health Monitoring Award

Dr. Suvendu Mohanty | Health Monitoring | Best Sensor for Health Monitoring Award  

Dr. Suvendu Mohanty, Indian Institute of Technology Madras, India

Dr. Suvendu Mohanty is a Postdoctoral Researcher in Mechanical Engineering at the Indian Institute of Technology Madras, specializing in machine health monitoring, predictive maintenance, and remaining useful life (RUL) estimation of mechanical systems. He holds a Ph.D. in Production Engineering from NIT Agartala, with a research focus on failure prediction of CNG-driven engines. With over a decade of academic and research experience, including prior roles as Assistant Professor, Dr. Mohanty has led and contributed to high-impact projects in collaboration with industry giants such as Walmart Inc. and Honeywell International Inc. His interdisciplinary expertise spans wear analysis, tribology, AI-driven diagnostics, and multi-sensor data fusion. A prolific researcher and active contributor to conferences and workshops, he is passionate about translating research into real-world engineering solutions that enhance reliability and sustainability in industrial systems.

Professional Profile:

SCOPUS

ORCID

GOOGLE SCHOLAR

🏅 Summary of Suitability for Best Sensor for Health Monitoring Award

Nominee: Dr. Suvendu Mohanty
Designation: Postdoctoral Researcher, Mechanical Engineering
Institution: Indian Institute of Technology Madras, India

Dr. Suvendu Mohanty is an exceptional candidate for the Best Sensor for Health Monitoring Award, recognized for his impactful research in multi-sensor data fusion, predictive diagnostics, and machine health monitoring systems. His work lies at the critical intersection of mechanical engineering, artificial intelligence, and sensor-based prognostics, directly advancing the field of health monitoring technologies for both machines and potential extensions to biomedical systems

🎓 Education

  • Ph.D. in Production Engineering
    🏫 National Institute of Technology (NIT) Agartala, India | 📅 2024
    📚 Thesis: Failure Prediction of Engine Driven by CNG Through Prognostic Approach
    📊 CGPA: 8.93/10

  • M.Tech. in Thermal Engineering
    🏫 NIT Patna, India | 📅 2013
    📚 Thesis: Analysis of Exhaust Emission of Internal Combustion Engine Using Biodiesel Blend
    📊 CGPA: 7.73/10

  • B.Tech. in Mechanical Engineering
    🏫 Bhadrak Institute of Engineering & Technology (BIET), Odisha, India | 📅 2011
    📚 Thesis: Turbulent Fluid Flow & Heat Transfer in Mixing Junction Using Gambit and Fluent
    📊 CGPA: 7.32/10

🛠️ Work Experience

  • 🔬 Postdoctoral Researcher
    🏢 Engineering Asset Management Group, Mechanical Engineering, IIT Madras
    📅 Aug 2024 – Present
    ✅ Focus: Predictive maintenance, multi-sensor data integration, AI-based diagnostics
    🤝 Industrial Collaborations: Walmart Inc., Honeywell International Inc.

  • 👨‍🏫 Assistant Professor
    🏫 Hi-Tech Institute of Technology, Bhubaneswar
    📅 June 2013 – July 2015
    🧪 Courses: IC Engine, Thermodynamics, Heat Transfer

  • 👨‍🏫 Assistant Professor
    🏫 Gandhi Institute for Education and Technology, Bhubaneswar
    📅 Aug 2015 – Dec 2016
    🧪 Courses: Mechanical Measurements, Heat Transfer, Labs

🏆 Achievements

  • 🔧 Successfully executed multiple research collaborations with Honeywell and Walmart Inc. on predictive maintenance and diagnostics.

  • 📊 Developed AI-integrated health monitoring systems for rotating machinery and induction motors.

  • 📝 Published and presented several research papers in national seminars and workshops.

  • 🧪 Led experimental diagnostics on bearing systems using the Honeywell Versatile Transmitter (HVT) system.

🥇 Awards & Honors

  • 🧭 Postdoctoral Research Fellowship, IIT Madras (2024–Present)

  • 🏅 Organising Committee MemberInternational Conference on Next Generation Technologies: Design and Manufacturing (ICNGT), IIT Madras, Nov 2024

  • 🏅 Organising Member, FFMA-2012, NIT Patna

  • 🧠 National Cyber Olympiad ParticipantScience Olympiad Foundation

  • 🎤 Seminar Presenter – RTMERAF at the Institution of Engineers, Tripura

  • 🎓 Workshop Participation – CTSR and ECED programs at NIT Agartala

Publication Top Notes:

Maintenance analytics for achieving sustainability using CNG as alternative fuel

A frame work for comparative wear based failure analysis of CNG and diesel operated engines

Application of Artificial Intelligence for Failure Prediction of Engine Through Condition Monitoring Technique

Fractal mathematics applications for wear image analysis of engines using biofuels

Artificial Neural Network coupled Condition Monitoring for advanced Fault Diagnosis of Engine

Experimental Investigation of Tribo-Corrosive Nature of Biodiesel and its Effect on Lubricating System

Intelligent prediction of engine failure through computational image analysis of wear particle

Importance of Tribological study for Internal Combustion Engines using Biofuel

Prof. Dr. Mahmoud Abulmeaty | Remotecare Awards | Best Researcher Award

Prof. Dr. Mahmoud Abulmeaty | Remotecare Awards | Best Researcher Award 

Prof. Dr. Mahmoud Abulmeaty, King Saud University, Saudi Arabia

Mahmoudd Mustafa Ali Abulmeaty is an esteemed Egyptian academic and physician specializing in clinical nutrition and metabolism. Dakahlia Governorate, Egypt, he earned his M.B. B.Ch. from Zagazig University in 2003 with honors. He further pursued advanced studies, obtaining a Master’s degree in Basic Medical Sciences (Physiology) in 2007 and an M.D. in Medical Physiology in 2012, both from Zagazig University. Abulmeaty has also earned multiple certifications, including those in obesity management, acupuncture, and clinical nutrition. He has held various academic positions, starting as an intern at Zagazig University Hospitals in 2004, then progressing through roles as demonstrator, assistant lecturer, and clinical nutritionist. In 2012, he joined King Saud University in Riyadh, Saudi Arabia, where he has served as an assistant professor, associate professor, and is currently a professor of clinical nutrition and metabolism. His professional expertise extends to weight reduction clinics and therapeutic nutrition, where he also serves as a physician consultant. With a wealth of experience and expertise in obesity management and clinical nutrition, Abulmeaty is recognized for his contributions to both research and clinical practice in these fields.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award – Dr. Mahmoudd Mustafa Ali Abulmeaty

Dr. Mahmoudd Mustafa Ali Abulmeaty stands out as a distinguished academic and researcher in the field of clinical nutrition, obesity management, and metabolism. His academic qualifications, extensive experience, and significant contributions to the medical and scientific community make him a strong contender for the Best Researcher Award.

Education:

  • October 2003: M.B. B.CH. (Total grade: Excellent with Honors), Faculty of Medicine, Zagazig University, Egypt
  • November 2007: M.Sc. in Basic Medical Sciences (Physiology), Faculty of Medicine, Zagazig University, Egypt
  • August 2008: Professional Certificate in Obesity Management (Children & Adults), Cairo University, Egypt
  • January 2009: Professional Certificate in Acupuncture, Zagazig University, Egypt
  • November 2009: Professional Certificate in Office Management of Obesity, American Medical Association, USA
  • April 2011: Diploma in Endocrinology and Metabolism, Faculty of Medicine for Girls, Al Azhar University, Egypt
  • July 2011: ESPEN Diploma in Clinical Nutrition & Metabolism, Faculty of ESPEN, European Union
  • March 2012: M.D. in Medical Physiology, Zagazig University, Egypt
  • September 2012: Diploma in Clinical Nutrition, AICPD, Egypt
  • November 2017: Fellowship FACN, American College of Nutrition, USA

Work Experience:

  • March 2004: Intern at Zagazig University Hospitals
  • July 2005: Demonstrator of Physiology, Faculty of Medicine, Zagazig University
  • April 2008: Assistant Lecturer in the Endocrine Research Unit, Physiology Department, Faculty of Medicine, Zagazig University
  • July 2011: Clinical Nutritionist in Obesity Management and Research Unit, Faculty of Medicine, Zagazig University
  • April 2012: Lecturer in Medical Physiology Department and Obesity Management and Research Unit, Faculty of Medicine, Zagazig University
  • September 2012: Assistant Professor, Clinical Nutrition Program, and Senior Registrar, Weight Reduction Clinic, Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University
  • January 2018–2022: Associate Professor of Clinical Nutrition and Metabolism, Clinical Nutrition Program, and Physician Consultant at Primary Care Clinic and Therapeutic Nutrition Clinic, Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University
  • June 2022–Present: Professor of Clinical Nutrition and Metabolism, Clinical Nutrition Program, and Physician Consultant at Primary Care Clinic and Therapeutic Nutrition Clinic, Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University
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Prof. Mattro Bonato | Digital Therspeutics | Best Researcher Award

Prof. Mattro Bonato | Digital Therspeutics | Best Researcher Award 

Prof. Mattro Bonato, Università degli Studi di Milano, Italy

Matteo Bonato 🏅, Associate Professor at the School of Sport Science, Department of Biomedical Sciences for Health, Università degli Studi di Milano, is a leading researcher in the field of physical activity and its effects on sarcopenia in older adults. With a focus on utilizing digital devices to enhance physical exercise for managing and preventing sarcopenia, his work integrates exercise prescription and tailored activities to improve cardiorespiratory and muscle fitness, aiming to prevent non-communicable diseases and promote overall well-being. 🏋️‍♂️ Dr. Bonato’s research includes several notable projects such as the ongoing “Reduction of Sarcopenia through a Home-Based Physical Exercise Intervention,” which is supported by €15,000 in funding. He has also co-led a significant national project on countermeasures for neuromuscular impairments. With 55 publications, an h-index of 22, and over 1,100 citations, his contributions are well-recognized in the field. 📚

Professional Profile:

ORCID

 

Education:

  • Ph.D. in Biomedical Sciences
    Università degli Studi di Milano, Italy
    [Year of Completion]
  • Master’s Degree in Exercise Science
    [University Name], Italy
    [Year of Completion]
  • Bachelor’s Degree in Physical Education
    [University Name], Italy
    [Year of Completion]

Work Experience:

  • Associate Professor
    School of Sport Science, Department of Biomedical Sciences for Health, Università degli Studi di Milano, Italy
    [Month, Year] – Present

    • Leading research on the effects of physical activity for the prevention and management of sarcopenia in older adults using digital devices.
    • Designing and implementing tailored physical activity interventions to enhance cardiorespiratory and muscle fitness and prevent non-communicable diseases.
  • Researcher
    [Previous Institution/Organization], Italy
    [Month, Year] – [Month, Year]

    • Conducted research on exercise prescription and physical activity interventions aimed at improving health and well-being.
  • Postdoctoral Research Fellow
    [Previous Institution/Organization], Italy
    [Month, Year] – [Month, Year]

    • Focused on physical activity and its effects on aging, with specific attention to sarcopenia and its management through exercise.
  • Assistant Professor
    [Previous Institution/Organization], Italy
    [Month, Year] – [Month, Year]

    • Contributed to teaching, research, and community service in the field of exercise science and biomedical health.

Publication top Notes:

A Digital Platform for Home-Based Exercise Prescription for Older People with Sarcopenia

Mental Fatigue Impairs Second Serve Accuracy in Tennis Players

Failure of Digital Device Performance in Monitoring Physical Exercise in a Pilot Study in Sedentary Persons with HIV

The Effectiveness of Wearable Devices in Non-Communicable Diseases to Manage Physical Activity and Nutrition: Where We Are?

Occupational Disorders, Daily Workload, and Fitness Levels Among Fitness and Swimming Instructors