Artificial Intelligence and Medicine 2025

Amjad Parvaiz

MD, FRCS (Eng), FRCS (Gen)
Professor of Surgery, University of Portsmouth, UK
Department of Colorectal Surgery, Champalimaud Foundation, Lisbon, Portugal
Department of Colorectal Surgery, Hamad General Hospital, Doha, Qatar

Prof. Amjad Parvaiz is an internationally renowned colorectal surgeon specializing in laparoscopic and robotic surgery. He obtained his MBBS from King Edward Medical University, Lahore, in 1992 and later earned multiple Fellowships from the Royal College of Surgeons in Glasgow and England. Currently, he serves as the Head of Laparoscopic & Robotic Colorectal Surgery at the Champalimaud Foundation in Lisbon, Portugal, and is a Visiting Consultant and Head of Robotic Surgery at Hamad General Hospital, Qatar. Additionally, he holds a professorship at the University of Portsmouth and is an Honorary Professor at the University of Belgrade.

A pioneer in minimally invasive colorectal surgery, Prof. Parvaiz has performed and supervised over 5000 laparoscopic and robotic procedures, contributing significantly to training and research. He played a key role in the UK’s National Training Programme (Lapco) and founded the European Academy of Robotic Colorectal Surgery (EARCS). His research contributions include over 150 peer-reviewed publications and multiple book chapters.

Recognized globally for his contributions, Prof. Parvaiz has received numerous awards, including a National Medal for Excellence in Cancer Care. He has trained surgeons across Europe, Africa, and Asia, establishing international centers of excellence in colorectal surgery. His expertise has led to groundbreaking advancements in robotic rectal surgery, making him one of the leading figures in his field. Beyond medicine, he enjoys sports, mountaineering, and Urdu literature. His achievements continue to shape the future of minimally invasive colorectal surgery worldwide.

Bin Hu

PhD, FIEEE, FIET, FAAIA, the EiC of IEEE TCSS
School of Medical Technology, Beijing Institute of Technology, Beijing, China

Dr. Bin Hu is a (Full) Professor and the Dean of the School of Medical Technology at Beijing Institute of Technology, China. He is a National Distinguished Expert, Chief Scientist of 973, and a National Advanced Worker in 2020. He is a Fellow of IEEE/IET/AAIA and IET Fellow Assessor & Fellowship Advisor. He serves as the Editor-in-Chief for the IEEE Transactions on Computational Social Systems and an Associate Editor for IEEE Transactions on Affective Computing. He is one of Clarivate's Highly Cited Researchers and the World's Top 2% Scientists.

Girish N. Nadkarni

MD, MPH, CPH
System Chair, The Windreich Department of Artificial Intelligence and Human Health,
Director, The Hasso Plattner Institute for Digital Health at Mount Sinai,
The Irene and Dr. Arthur Fishberg Professor of Medicine Professor of Surgery,
The Icahn School of Medicine at Mount Sinai and the Mount Sinai Health System, New York City, NY, US

Dr. Girish N. Nadkarni is a physician-scientist and clinical informaticist, whose career is marked by leadership in artificial intelligence (AI) and precision medicine. He is currently the Fishberg Professor of Medicine, Chair of the Windreich Department of Artificial Intelligence and Human Health, Director of the Hasso Plattner Institute for Digital Health, and Inaugural System Chief of the Division of Data-Driven and Digital Medicine at the Icahn School of Medicine at Mount Sinai. He has spearheaded transformative and translational research leading to 376 original peer-reviewed research and 52 invited publications with over 40,000 citations and an h-index of 90. These include senior authored papers in journals including the Journal of American Medical Association, Annals of Internal Medicine, Journal of American College of Cardiology, and Lancet Digital Health. His work has advanced fields including precision cardiovascular and kidney care, including landmark studies using electrocardiograms for predicting outcomes, understanding the impact of predictive AI in healthcare, AI-bioprognostics for kidney disease, and several studies on APOL1 genetic risk for kidney disease. Dr. Nadkarni's innovations extend to entrepreneurship, where he co-founded several companies that have pioneered AI-based approaches, with some receiving FDA clearance. He is a principal investigator for seven concurrent R01 grants or equivalents, three industry contracts, and two NIH contracts for a cumulative amount of ~$40 million. Additionally, he holds numerous patents on AI and predictive applications in healthcare and co-invented the first FDA-approved AI-bioprognostic for kidney disease. His influence is reflected in external leadership roles, including Chair of the Taskforce on AI/Digital Health and Associate Editor of NPJ Digital Medicine. His mentorship has seen 14 of his mentees attain independent faculty roles, underscoring his commitment to fostering future leaders in medicine. He has received several honors including the ANIO Rising Star Award, the Carl Nacht Memorial Lecture, and the Harold Lamport Clinical Research Award.

Jun Deng

PhD
Professor, Department of Therapeutic Radiology and Department of Biomedical Informatics and Data Science, Yale University, New Haven, CT, US

Dr. Jun Deng is a Professor and Director of Physics Research at the Department of Therapeutic Radiology, a Professor at the Department of Biomedical Informatics & Data Science of Yale University School of Medicine, the Principal Investigator of Yale Smart Medicine Lab, and the leading member of the Digital Twins for Health (DT4H) Consortium. He received his PhD from the University of Virginia and finished his postdoctoral fellowship at Stanford University. With funding from NIBIB, NSF, NCI, DOE, and YCC, his research has been focused on artificial intelligence, machine learning, big data, and medical imaging for real-time clinical decision support, digital twins of cancer patients, early cancer detection, as well as AI-empowered mobile health.

Dr. Deng has been serving on the editorial board of numerous peer-reviewed journals, on the study sections of NIH, NSF, DOD, ACS, RSNA, ASTRO, and CPRIT since 2005, and as a scientific reviewer for various national and international science foundations and institutions since 2015. He is an elected fellow of the Institute of Physics, AAPM, ASTRO, and has been recently selected as one of the Key Thought Leaders of the NCI Cancer AI Accelerator Program, one of the Experts for the NIH AIM-AHEAD PAIR Program, and one of the Mentors for the NIH AIM-AHEAD Research Fellows Program.

Marlies P. Schijven

MD, PhD, MHSc
Professor of Surgery and Chair on Digital Health, Amsterdam University Medical Center, Amsterdam, Netherlands

Dr. Marlies Schijven is a board-qualified surgeon and a full Master's in Health Sciences. Her research is in digital health, with a special focus on surgery. Her work relates to the fields of mobile healthcare, simulation and serious gaming, and surgical innovations in the operating room, involving wearables and medical data recorder systems. 

Her clinical work focuses on surgery for GERD, achalasia, and upper GI motility disorders. Dr. Schijven is appointed both as principal educator and principal investigator. She is the project owner of the eHealth domain, including the electronic patient file (EPIC – MyChart). She is the founder of the Digital Health Research Institute at her University. She was appointed as the first CMIO (Chief Medical Information Officer) to the Dutch Government and is currently a (supervisory) board member of several institutions and governing organizations like Meander Medical Center and ZonMw, The Netherlands Organization for Health Research and Development. Dr. Schijven is internationally recognized as an expert in virtual and augmented reality medical simulation, serious gaming, validation studies and –processes, eHealth, and app development for healthcare and is actively researching the MedTech domain, guiding several PhD residents. She successfully acquired subsidiaries and won grand prizes. She is an Editor of BMJ Innovations, the Lancet Digital, and JMIR Serious Games and a Chief Editor of the Sage Journal Simulation and Gaming. She is also the Consortium Leader of KEEPCARING –A HORIZON-HLTH-2023-CARE-04 EU-Program.

Mustafa Kurban

PhD
Professor, Department of Orthotics and Prosthetics, Faculty of Health Sciences, Ankara University, Ankara, Turkey

Dr. Mustafa Kurban is a Full Professor in the Department of Prosthetics & Orthotics at Ankara University, Turkey. He earned his PhD in Physics from Middle East Technical University in 2016 and completed a postdoctoral fellowship in Materials Science & Engineering at the University of California, Riverside, from 2018 to 2019.

His research spans materials science, computational physics, nanotechnology, and sensor technologies, with a particular focus on nanostructured materials for applications in energy, environment, and healthcare. He has made significant contributions to the development of advanced materials for solar cells, batteries, and emission-reduction technologies. In recent years, his work has focused on integrating fiber optic sensor technologies into prosthetic systems, aiming to improve adaptability, real-time physiological monitoring, and patient comfort.

Prof. Kurban’s interdisciplinary expertise bridges theoretical modeling and experimental techniques, enabling innovations in semiconductors, energy storage, organic electronics, and biomedical sensor systems. His research includes bulk heterojunction solar cells, AI-driven materials science, optics, drug delivery systems, nanomaterials, 2D materials, organic molecules, and crystal structures. At AI and Medicine 2025, Prof. Kurban will present the role of wearable fiber optic sensor systems in prosthetic technology, demonstrating their potential to improve prosthetic performance, patient-specific adaptability, and integration with AI-driven healthcare solutions. His work aims to bridge the gap between sensor technology, artificial intelligence, and personalized medicine, fostering interdisciplinary collaborations and driving innovations in prosthetic and medical sensor applications.

Raymond Harshbarger

MD, FACS, FAAP
Associate Professor of Surgery, Neurosurgery, and Pediatrics, Dell Medical School, University of Texas at Austin, Austin, TX, US

Dr. Raymond J. Harshbarger is the Craniofacial & Pediatric Plastic Surgery Fellowship Founder and former Director for the ACGME-accredited Dell Children's Medical Center Program and is Chief of Plastic and Reconstructive Surgery at Ascension Seton Williamson Medical Center. He holds appointments at multiple hospitals in the University of Texas system and serves as Associate Professor of Surgery and Perioperative Care along with secondary appointments in Pediatrics and Neurosurgery at UT-Austin's Dell Medical School. Dr. Harshbarger is also an Adjunct Professor in the Department of Biomedical Engineering at UT-Austin. After completing his Doctor of Medicine degree at the University of Rochester, he trained in General/Plastic Surgery at the Brown University Program and completed a Craniofacial Surgery & Pediatric Plastic Surgery Fellowship at Children’s Hospital Los Angeles/USC Medical School and has completed additional training in TMJ surgery. He served as a Lieutenant Colonel in the US Army and directed the craniofacial reconstruction program from the Iraq/Afghanistan War at the Walter Reed Army Medical Center.

Dr. Harshbarger's clinical interests span both adult and pediatric craniomaxillofacial conditions. He also manages facial trauma and complex craniofacial reconstruction, including microsurgery. He has a passion for international humanitarian surgical work. He has participated in many cleft and craniofacial surgery missions to third-world countries including Vietnam, Honduras, Paraguay, and Peru. He has organized and led five missions to the Dominican Republic and over 20 missions to El Salvador where he currently performs orthognathic surgery and is assisting local physicians in creating a viable craniofacial center there.

Dr. Harshbarger also maintains an interest in clinical and basic science research, having conducted grant-funded research in the genetics of craniosynostosis. Currently, his interest lies in the development of alloplastic cranioplasty and improving craniofacial trauma care. His work has been featured in numerous publications, and he has enjoyed speaking at several national and international conferences and invited lectureships. He is a member of multiple societies including the American Cleft Palate-Craniofacial Association and currently serves on the board of directors for both the American Society of Craniofacial Surgery, the American Society of Maxillofacial Surgeons, and the American Association of Pediatric Plastic Surgeons.

Tolga Çukur

PhD
Director, National Magnetic Resonance Research Center (UMRAM),
Professor, Department of Electrical-Electronics Engineering and Neuroscience, Bilkent University, Ankara, Turkey

Dr. Tolga Çukur is a Professor in the Department of Electrical-Electronics Engineering and the Department of Neuroscience and the Director of the National Magnetic Resonance Research Center at Bilkent University. He received his PhD in Electrical Engineering from Stanford University in 2009 and pursued his postdoctoral studies at the University of California, Berkeley till 2013. He has published over 200 journal and conference articles in medical imaging, with a particular focus on medical image reconstruction and analysis. He currently serves as associate editor in IEEE Transactions on Medical Imaging, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Computational Imaging, and is an editorial board member for Magnetic Resonance in Medicine.

Dr. Çukur has been elected a Fellow of ISMRM (2024), and a Senior Member of IEEE (2017), and he has received numerous awards for his work including the TUBITAK Career Award (2015), TUBA-GEBIP Outstanding Young Scientist Award (2015), BAGEP Young Scientist Award (2017), IEEE Turkey Research Encouragement Award (2017), Science Heroes Association Young Scientist of the Year Award (2017), METU Parlar Foundation Research Incentive Award (2019), and TUSEB Research Encouragement Award (2021).

Zoie Wilkins-Wong

PhD
Adjunct Associate Professor, The Kirby Institute, University of New South Wales, Sydney, Australia
Adjunct Senior Lecturer, Biomedical Informatics and Digital Health, School of Medical Sciences, The University of Sydney, Sydney, Australia
Honorary Associate Professor, School of Public Health, The University of Hong Kong, Hong Kong, China

Dr. Zoie Wilkins-Wong is a distinguished researcher, educator, and consultant with global expertise in digital health, data science analytics, and AI technology innovation. Her research program aims to harness digitalized data to enhance human-computer synergism and improve population health outcomes. She believes that leveraging AI and information technologies through visionary project leadership can drive transformative advancements. Through more than a decade of academic experience and industrial consultancy, she has attained significant recognition in digital innovations, particularly in the health sector. Having served as the lead consultant for a UNICEF-funded project, she applied informatics best practices, stakeholder engagement, and conflict-sensitive approaches to assess the digital transformation landscape for a supported country in the region.

Achim Riedle

MBA
Head of Business Development IPS CMF, KLS Martin Group, Tuttlingen, Germany

Achim Riedle has been with KLS Martin for over 10 years, where he focuses on patient-specific solutions in the CMF field. He began as a specialist in the IPS CaseDesigner software in 2017, and since then, the team has grown to four members. Mr. Riedle now leads a team of IPS experts who are dedicated to assisting local representatives, partners, and surgeons with cutting-edge technology.

The team prioritizes serving everyone involved to ensure the best possible treatment outcomes. They also aim to introduce innovative solutions, including new indications, products, and digital applications for planning, designing, and simulating. Their efforts are particularly focused on AI-supported software solutions to enhance these treatment outcomes.

Arun Jayarame Gowda

MBBS
Senior Principal, Head of AIML Middle-East, IQVIA, Bangalore, Karnataka, India

Dr. Arun Gowda is a trained physician with 20 years of experience in various health sectors, including clinical practice, research, consulting, patient education, behavior change, analytics, real-world evidence, and technology.

Currently, he works at IQVIA, focusing on health and healthcare access through real-world insights and stakeholder dialogues in dynamic, high-growth economies. At IQVIA, Dr. Gowda leads AIML-related projects in the Middle East and participates in healthcare stakeholder engagement activities aimed at developing consensus statements and generating real-world evidence.

Previously, Dr. Gowda worked with Nokia, where he led the Health and Wellness vertical of Nokia Life, a mobile information service centered on behavior change and wellness messaging across Africa, the Middle East, and Asia.

Dr. Gowda began his career as an emergency physician and medical officer in hospitals, managing in-patients in wards, the ICU, and post-operative care. He has authored approximately 30 scientific publications and delivered presentations at various conferences.

Gijs Luijten

MSc
Institute for Artificial Intelligence in Medicine (IKIM), Essen University Hospital (AöR), Essen, North Rhine-Westphalia, Germany
Center for Virtual and Extended Reality in Medicine (ZvRM), University Hospital Essen, North Rhine-Westphalia, Essen, Germany
Institute of Computer Graphics and Vision (ICG), Graz University of Technology, Graz, Styria, Austria

Gijs Luijten holds a Master's in Technical Medicine, specializing in medical imaging and intervention, from the Technical University of Twente. He focused on augmented reality (AR) applications for oral-maxillo-facial (OMF) and free flap surgery.

At the Institute for Artificial Intelligence in Medicine (IKIM), he conducts research with the University Hospital Essen (UKE). The research aims to improve (surgical) diagnosis and intervention using state-of-the-art 3D technologies, particularly Virtual and Augmented Reality (VR/AR). As a visiting scientist, he collaborated closely with the Technical University of Graz (Institute for Computer Graphics and Vision) and the Medical University of Graz. This collaboration aimed to investigate the effectiveness and usability of AR tools in real clinical settings and to explore interesting combinations of machine learning (ML) and AR.

Recently, Mr. Luijten has explored diminishing reality in synthetic data of surgeries and created an extensive database and API for 3D medical shapes and forms in machine learning, eye tracking to improve diagnosis, and more. Currently, he is co-managing the XR-Lab at IKIM while working on a combination of ultrasound, machine learning, and augmented reality. He is working on a combination of ultrasound, machine learning, and augmented reality. Mr. Luijten has a strong desire for continuous learning and improvement in related fields such as machine learning, workflow planning, modeling, and programming. His work aims to empower researchers, improve patient care, and inspire clinicians, patients, and companies to push the boundaries of current possibilities. His publications display a diverse range of collaborations, highlighting his commitment to advancing the possibilities within his field.

Hassan Rivaz

PhD, SMIEEE
Full Professor, Research Chair in Medical Imaging with Deep Learning, Concordia University, Montreal, QC, Canada

Dr. Hassan Rivaz completed his Bachelor of Science in 2003 at Sharif University of Technology, followed by a Master of Science in 2005 at the University of British Columbia (UBC). He earned his PhD in 2011 from Johns Hopkins University and subsequently completed a post-doctoral fellowship funded by NSERC at the Montreal Neurological Institute.

In 2014, Dr. Rivaz was appointed as an Assistant Professor in the Department of Electrical and Computer Engineering at Concordia University. He was promoted to Associate Professor in 2019 and to Professor in 2024. Dr. Rivaz held the Concordia University Research Chair in Medical Image Analysis from 2018 to 2023 and currently holds the Research Chair in Medical Imaging with Deep Learning from 2023 to 2028.

He is the Director of the IMPACT Lab, which focuses on Image Processing and Characterization of Tissue. In 2022, he was recognized as a Rising Star in Quebec Bio-imaging. Additionally, he has served as an Associate Editor for the IEEE Transactions on Medical Imaging since 2017 and for IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control since 2018. He was also an Associate Editor for IEEE Open Journal of Biomedical Engineering from 2021 to 2024.

Dr. Rivaz has been a member of the Organizing Committee for several conferences, including IEEE EMBC 2020 in Montreal, Canada, and IEEE ISBI 2021 in Nice, France. He has also served as an Area Chair for MICCAI for seven years, from 2017 to 2024. His research interests include machine learning and deep learning in medical imaging, ultrasound imaging, quantitative ultrasound, elastography, and beamforming.

İlkay Ulusoy

PhD
Professor and Chair, Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey

Dr. İlkay Ulusoy earned her B.Sc. degree from the Department of Electrical and Electronics Engineering at Middle East Technical University (METU). She then obtained her M.S. degree in Biomedical Engineering from The Ohio State University and her PhD from the Department of Electrical and Electronics Engineering at METU.

Dr. Ulusoy has worked at the Computer Science Department at the University of York, UK, and at Microsoft Research in Cambridge, UK. Since 2003, she has been a faculty member in the Department of Electrical and Electronics Engineering at METU, becoming a Professor in 2018 and Chair of the department in 2019. Her main research interests include machine learning, probabilistic modeling, and neuroscience.

Kevser Banu Köse

PhD
Assistant Professor, Biomedical Engineering Department, Istanbul Medipol University, Turkey

Dr. Kevser Banu Köse is an Assistant Professor at Medipol University, specializing in cardiovascular. Her research focuses on artificial intelligence-driven risk modeling, computational hemodynamics simulations, medical image processing, and three-dimensional modeling applications in cardiovascular surgery, particularly in congenital heart disease and coronary artery bypass grafting surgery. She has experience in computational modeling, fluid dynamics, and AI-powered decision support systems, aiming to improve surgical planning and patient-specific treatment strategies. As a mentor for the EIC Accelerator program, Dr. Köse actively supports innovative startups and research projects in the healthcare domain. Additionally, she serves as a lead auditor and consultant in the vascular medical device industry, ensuring regulatory compliance and guiding medical technology development.

Dr. Köse has contributed to multiple projects, working closely with clinicians, biomedical engineers, and AI researchers to advance personalized medicine. She also plays a role in fostering interdisciplinary partnerships for start-ups, bridging the gap between engineering, medicine, and data science to support innovative healthcare solutions.

Kun Qian

PhD
Full Professor, School of Medical Technology, Beijing Institute of Technology, Beijing, China

Prof. Kun Qian received his doctoral degree for his study on automatic general audio signal classification in 2018 in electrical engineering and information technology from Technische Universität München (TUM), Germany. He is committed to researching machine learning/deep learning in medical health, audio-intelligent sensing, and intelligent Internet of Things. His research interests include Computer Audition (CA), Affective Computing, and Brain Sciences. From 2021, he has been appointed (Full) Professor at the Beijing Institute of Technology (BIT), China. He won the Beijing Science and Technology Award (Second Prize for Scientific and Technological Progress) in 2023, Invention Entrepreneurship and Innovation Award in 2023, and the Excellent Achievement Award of Zhejiang Lab in 2020. He is a Senior Member of the IEEE. He was recognized as one of Forbes China's 100 Outstanding Overseas Returnees in 2023 and an MIT Technology Review (China) & DeepTech's Intelligent Computing Innovators 2023 of China. Prof. Qian is an Associate Editor for the IEEE Transactions on Affective Computing, Frontiers in Digital Health, and BIO Integration. He co-authored more than 170 publications in peer-reviewed journals and conference proceedings that received more than 3.1k citations (h-index 33).

Maurizio S. Tonetti

DMD, PhD, MMSc, FRCS(Eng), FRCPS
Chair Professor, and Director, Institute for Integrated Oral, Craniofacial and Sensory Research, Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

With a distinguished academic and clinical career, Prof. Dr. Maurizio Tonetti holds a DMD from Genova, Italy, a PhD from Berne, Switzerland, and an MMSc from Harvard, US. He is also a Fellow of the Royal College of Surgeons of England and the Royal College of Physicians and Surgeons. Currently, he is Chair Professor and founding Dean/Director of the Integrated Institute for Oral, Craniofacial, and Sensory Health Research, Ninth People’s Hospital, Faculty of Medicine, Shanghai Jiao Tong University. He is also the Executive Director of the European Research Group on Periodontology and Editor Emeritus of the Journal of Clinical Periodontology. He is a former tenured professor and head of periodontology and implant dentistry, University of Hong Kong, University of Connecticut Health Science Center, University College London.

Dr. Tonetti’s clinical practice is limited to periodontology and implant surgery with emphasis on regeneration, minimally invasive surgery, and microsurgery. He is a strategic clinical scientist focusing on periodontal health. With an h-factor of 116, his scientific work has been cited more than 61,000 times and featured in many global press and television news outlets. He has been engaged worldwide in the planning and delivery of advanced educational programs in periodontology and implant dentistry. 

Raafat George Saadé

PhD
Chair Full Professor, School of Management, Beijing Institute of Technology, Beijing, China

After his PhD from Concordia University, Dr. Raafat George Saadé was awarded a post-doctoral fellowship from the Natural Sciences and Engineering Research Council of Canada, which he completed at McGill University, Montreal, Canada. After 22 years of service, in 2021, Dr. Saadé, a full professor (and Chair of the Department of Supply Chain and Business Technology Management), joined the Beijing Institute of Technology (BIT), Beijing, China, at the rank of Chair Full Professor.

Dr. Saadé has extensive consulting experience on international projects from the Canadian International Development Agency (CIDA), the International Civil Aviation Organization (ICAO), and the private sector in the fields of medical engineering and information technologies (clinical research organizations information systems; artificial neural networks in breast cancer; evidence-based expert system on fracture risk in osteoporosis and osteoporosis decision support system; intelligent interpretation system of medical devices; reverse engineering and manufacturing of ultrasound diagnosis device for osteoporosis, intelligent system for chronic disease management, etc...).

Dr. Saadé is multi-disciplinary and has published in top-ranked journals in different areas: information & management, expert systems and applications, computers and human behavior, computers and education, internet of things, sustainability, administrative sciences, decision sciences, Journal of Organizational Change Management, and IEEE. He founded the International Network for Digital Innovation Research and Education (INDIRE). Dr. Saadé’s newly established research interests include the internet of intelligence of things in education and medicine, climate change, blockchain applications, affective computing, and the application of AI in medical practice.

Shrooq A. Alsenan

PhD
Assistant Professor and Director of the Artificial Intelligence Center, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, KSA
Research Affiliate, Massachusetts Institute of Technology, Cambridge, MA, US

Dr. Shrooq Alsenan is an Assistant Professor and the Director of the College of Computer and Information Sciences (CCIS) AI Center at Princess Nourah Bint Abdulrahman University. She holds a PhD in Information Systems Sciences from King Saud University specializing in artificial intelligence applications in healthcare, medicine, and drug discovery. Her research was awarded "1st place distinguished PhD dissertation" in the Annual Awards Ceremony for Excellence in Scientific Research at King Saud University 2022. She was also the recipient of the healthcare innovation research chair grant at KSU.

In 2022/2023, Dr. Shrooq received two fellowship grants to assume the role of a postdoctoral at the Massachusetts Institute of Technology (MIT). She worked in the Computer Science & Artificial Intelligence Lab (CSAIL) and Jameel Clinic AI & Healthcare Center at MIT. Her research interests revolve around AI adoption in healthcare, the transformation of the traditional drug discovery pipeline with AI and machine learning, and early disease detection and prevention.

Sozo Inoue

PhD
Professor and Director, Care XDX Center, Kyushu Institute of Technology, Kitakyushu, Fukuoka, Japan

Dr. Sozo Inoue is a full professor at the National Kyushu Institute of Technology in Japan and serves as the Chief Technical Officer of AUTOCARE LLC. His research focuses on human activity recognition using smartphones and the healthcare applications of web, pervasive, and ubiquitous systems. Currently, he is developing activity recognition and health forecasting applications for nursing care and medicine, which are implemented in hospitals and over 50 nursing facilities using smartphones and IoT technologies.

Dr. Inoue earned his PhD in Engineering from Kyushu University in 2003. After completing his degree, he took on the role of assistant professor at the Faculty of Information Science and Electrical Engineering at Kyushu University. In 2006, he transitioned to the Research Department at the Kyushu University Library. Since 2009, he has held the position of associate professor in the Faculty of Engineering at Kyushu Institute of Technology. In 2018, he moved to the Graduate School of Life Science and Systems Engineering at the same institute and was promoted to full professor in 2020. In 2022, he became the head of the Care XDX Center at Kyushu Institute of Technology.

Throughout his career, Dr. Inoue has also been a guest professor at Kyushu University, a visiting professor at the Karlsruhe Institute of Technology in Germany in 2014, and a guest professor at the University of Los Andes in Colombia in 2019. He served as a technical advisor for Team AIBOD Co. Ltd. from 2017 to 2019 and worked as a guest researcher at the RIKEN Center for Advanced Intelligence Project (AIP) during the same period. From 2020 to 2021, he held the position of director and is currently a senior member of the Information Processing Society of Japan (IPSJ) and a member of the IEEE Computer Society and the Association for Computing Machinery (ACM).

Ahmad Abdel-Hafez

PhD
Assistant Professor, Data Science & Artificial Intelligence, College of Computing and Information Technology, University of Doha for Science and Technology, Doha, Qatar

Dr. Ahmad Abdel-Hafez is an Assistant Professor and data scientist specializing in Machine Learning (ML), Artificial Intelligence (AI), and applied data science. His expertise lies in using ML algorithms to address complex data science challenges in healthcare systems, finance, education, and industry. Dr. Abdel-Hafez has a proven track record of applying data-driven insights to enhance clinical decision-making and operational efficiency, particularly in healthcare settings. Before joining the University of Doha for Science and Technology (UDST), Dr. Abdel-Hafez worked as a data scientist consultant and expert at Queensland Health, Australia, where he collaborated with multidisciplinary teams on impactful projects from inception to deployment.

Dr. Abdel-Hafez has led and contributed to successful grant applications exceeding $1.4M, where he played a central role in the data analytics and data science components of these projects. He has worked on high-impact healthcare solutions, including personalized dosing systems and automated triaging of outpatient referrals, demonstrating his commitment to driving positive change in healthcare. Dr. Abdel-Hafez is passionate about mentoring the next generation of researchers, having co-supervised several PhD students to graduation at the University of Queensland (UQ) School of Pharmacy, Queensland University of Technology (QUT) School of Public Health & Social Work, and the School of Computer Science at QUT. Through his work, he continues to bridge the gap between technology and healthcare, fostering interdisciplinary collaborations with clinicians, researchers, and institutes to advance the role of AI in improving healthcare outcomes.

Ammira Akil

PhD
Principal Investigator – Associate Level Executive, Precision Genomics and Translational Omics Lab, Sidra Medicine, Doha, Qatar

Dena Al-Thani

PhD
Associate Professor, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar

Dr. Dena Al-Thani is currently an Associate Professor, the co-founder of the A-sense Centre of Excellence, and the Head of the Information Communication and Technology Division at the College of Science and Engineering at Hamad Bin Khalifa University. She was awarded her MSc in Software Engineering and PhD in Computer Science from the Queen Mary University of London. Her research areas of interest include accessibility, inclusive design, human-AI interaction, and eHealth. Dr. Al-Thani is now actively publishing her work in high-ranked journals and presenting her work at international conferences. She is keen to see the impact on the world of her research on inclusion, and, to that end, she is a member of the World Health Organization (WHO) technical advisory group on assistive technology and the Arab ICT Accessibility Expert Group, an initiative by Mada.

Erchin Serpedin

PhD
Professor and Chair, Electrical and Computer Engineering Program, Texas A&M University at Qatar, Doha, Qatar

Dr. Erchin Serpedin (Fellow, IEEE) is currently a Professor and Chair of the Electrical and Computer Engineering Program at Texas A&M University at Qatar and a tenured Professor with the Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, US. He authored four research monographs, one textbook, 17 book chapters, 220 journal papers, and 320 conference papers. He has served as associate editor for a dozen top journals such as IEEE Transactions on Information Theory, IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, IEEE Transactions on Signal Processing, IEEE Signal Processing Letters, Signal Processing (Elsevier), EURASIP Journal on Advances in Signal Processing, IEEE Communications Letters, IEEE Signal Processing Magazine, and EURASIP Journal on Bioinformatics and Systems Biology. He served as technical co-chair of 7 major symposia and conferences. His research interests include signal processing, machine learning, artificial intelligence, cyber security, smart grids, bioinformatics, and biomedical engineering.

Hasan Kurban

PhD
Assistant Professor, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar
Adjunct Associate Professor of Computer Science and Data Science, Indiana University Bloomington, Bloomington, IN, US
Adjunct Assistant Professor of Electrical and Computer Engineering, Texas A&M University at Qatar, Doha, Qatar

Dr. Hasan Kurban is an Assistant Professor at the College of Science and Engineering at Hamad Bin Khalifa University, with additional roles as Adjunct Associate Professor of Computer Science and Data Science at Indiana University Bloomington and Adjunct Assistant Professor of Electrical and Computer Engineering at Texas A&M University at Qatar. He also serves as an Editor for Nature Scientific Reports.

He earned his PhD in Computer Science with a minor in Statistics from Indiana University, Bloomington, US in 2017. His research spans Artificial Intelligence (AI), deep learning, software engineering, graph theory, and large-scale data analytics, with applications in diverse fields including computational materials science, biology, sports analytics, education, public transportation, finance, and medicine. Dr. Kurban has gained practical experience through his involvement in AI start-ups in the US, where he focused on developing AI-driven solutions with an emphasis on ethical and human-centered approaches, aimed at improving efficiency and productivity in various sectors.

Kholoud Abdulla

BPharm, MSc, PhD
Acting Assistant Professor, Pharmaceutical Sciences Department, College of Pharmacy, QU Health, Qatar University, Doha, Qatar

Dr. Kholoud Abdulla is a pioneering expert in the fields of clinical pharmacy and pharmacogenomics, recognized as the first Qatari specialist in this domain. She earned her Bachelor's degree in Pharmacy from Jordan University in 2006 and later, pursued advanced studies, obtaining a Master's degree in Clinical Pharmacy from Queen’s University Belfast, UK, in 2014. In 2021, she completed her PhD in Genomic and Precision Medicine, focusing on pharmacogenomics. Currently serving as an Acting Assistant Professor at the College of Pharmacy, Qatar University, she leads pioneering research in Qatar focusing on optimizing psychiatric drug therapy through machine learning and pharmaco-omics.

Dr. Abdulla has secured multiple research grants, including funding from Qatar’s Path Towards Precision Medicine initiative, to advance personalized medicine applications in mental health and chronic diseases. She has played a pivotal role in integrating pharmacogenomics into clinical practice and is actively implementing AI-driven decision-support tools in Qatar’s healthcare system. Additionally, she has received several prestigious awards, including first place at the GCC Rowad Hackathon for her innovation in pharmacogenomics-driven health tech. Her research is centered on transitioning conventional treatment from a traditional trial-and-error approach to a precision medicine framework, incorporating AI-driven decision-making into real-world clinical settings.

Marwa Qaraqe

PhD
Associate Professor, Co-founder of the Autism Sensing Cener of Excellence, College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar

Dr. Marwa Qaraqe is an Associate Professor in the Division of Information and Communication Technology at the College of Science and Engineering at Hamad Bin Khalifa University. She is also the co-founder of the Autism Sensing Center of Excellence within the College of Science and Engineering at HBKU. Dr. Qaraqe earned her Bachelor's Degree in Electrical Engineering from Texas A&M University at Qatar in 2010, followed by a MSc and PhD in Electrical Engineering from Texas A&M University in College Station, Texas, in 2012 and 2016, respectively.

Her research focuses on wireless communication, signal processing, and machine learning, with multidisciplinary applications spanning security, the Internet of Things (IoT), and health. Dr. Qaraqe has a particular interest in physical layer security, reconfigurable intelligent surfaces, and machine learning techniques for enhancing wireless communication, security, and health. Passionate about predictive health analytics and personalized learning, she actively explores innovative approaches to managing health disorders through AI-driven solutions. In addition, she is deeply dedicated to research that leverages AI, sensing technology, and computer vision for the non-subjective assessment of behavior in children with autism, aiming to improve intervention strategies, outcomes, and learning.

Mohamad Saad

PhD
Senior Research Scientist, Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar

Dr. Mohamad Saad is a Senior Research Scientist at Qatar Computing Research Institute, Hamad Bin Khalifa University. His research focuses on developing and applying new statistical and artificial intelligence methods to unravel new risk factors for complex diseases. Dr. Saad is working on building polygenic risk scores and artificial intelligence models for better risk prediction of diseases with a focus on clinical implementation in the MENA region. He is also interested in artificial intelligence approaches to integrate multi-omics data for chronic diseases, including coronary heart disease and type 2 diabetes. Dr. Saad has many peer-reviewed articles in top-tier journals, including Nature Genetics, The Lancet, The Lancet Oncology, Immunity, Circulation: Genomics and Precision Medicine, and Genome Research.

Mohamed Elshrif

PhD
Software Engineer, Qatar Center for Artificial Intelligence, Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar

Dr. Mohamed Elshrif is currently a Software Engineer in the Qatar Center for Artificial Intelligence at the Qatar Computing Research Institute, Hamad Bin Khalifa University. He earned his PhD from the Rochester Institute of Technology in New York, US. Dr. Elshrif completed his Bachelor and Master of Science degrees in Computer Engineering at Tripoli University in Libya and Cairo University in Egypt, respectively. He also holds a Master of Business Administration from the Arab Academy for Banking and Financial Sciences in Egypt.

After completing his Bachelor's degree, he worked as an engineer and network administrator. He then served as a research assistant and data analytics engineer at the Rochester Institute of Technology. Following that, he was a visiting scholar at Qatar University before joining the Qatar Computing Research Institute as a Postdoctoral Research Associate. His research interests include machine learning, deep learning, data analytics, computational genetics, and the development of software platforms and applications for high-performance computing in biological contexts.

Muhamad Sadek Almiski

MD, FRCPC
Senior Hematopathologist, Pathology and Laboratory Medicine, Sidra Medicine, Doha, Qatar
Clinical Associate Professor, College of Medicine, Qatar University, Doha, Qatar

Muhamad Sadek Almiski graduated from the School of Medicine at Damascus University in Syria. He then completed his residency and fellowship training in Pathology at the American University of Beirut in Lebanon, Wayne State University, and the University of Texas Southwestern Medical Center in the US.

Dr. Almiski practiced as a Hematopathologist for thirteen years at Shared Health Manitoba, the University of Manitoba, and Canadian Blood Services. He also worked briefly in various Canadian institutions, including St. John Eastern Health, Vancouver General Hospital, Saskatoon Royal University Hospital, and Kelowna General Hospital. In 2023, he joined Sidra Medicine as a Senior Hematopathologist and became a Clinical Associate Professor at Qatar University.

He holds the title of Fellow of The Royal College of Physicians of Canada (FRCPC) and is a Diplomate of the American Board of Pathology (DABP) in Anatomic & Clinical Pathology, Hematology, and Cytopathology. In addition to artificial intelligence, his areas of interest include education, transfusion medicine, and hematopathology. Dr. Almiski has received several awards in Research and Pathology Informatics from the College of American Pathologists and the Digital Pathology Association.

He has collaborated with Dr. Mark M. Tuthill, Division Head of Pathology Informatics at Henry Ford Health, and Dr. Ulysses G.J. Balis, Director of the Division of Informatics in the Department of Pathology at the University of Michigan.

Muhammad E. H. Chowdhury

PhD, SMIEEE
Assistant Professor and Program Coordinator, Department of Electrical Engineering, Qatar University, Doha, Qatar

Dr. Muhammad E. H. Chowdhury received his PhD from the University of Nottingham, UK, in 2014. He subsequently worked as a Postdoctoral Research Fellow at the Sir Peter Mansfield Imaging Centre, University of Nottingham. Currently, he serves as an Assistant Professor and Program Coordinator in the Department of Electrical Engineering at Qatar University. Dr. Chowdhury is a prolific researcher with several patents, three edited books, over 250 peer-reviewed journal articles, more than 30 conference papers, and multiple book chapters. His research interests span biomedical instrumentation, signal processing, wearable sensors, medical image analysis, machine learning, computer vision, embedded system design, and simultaneous EEG/fMRI.

He is actively involved in leading several research projects funded by the Qatar Research, Development, and Innovation Council (QRDI) and internal grants from Qatar University, along with academic collaborations with Hamad Bin Khalifa University and Hamad Medical Corporation (HMC). As a Senior Member of IEEE, Dr. Chowdhury also serves as an Associate Editor for Computers and Electrical Engineering and IEEE Access, as well as a Topic Editor and Review Editor for Frontiers in Neuroscience. Dr. Chowdhury has been recognized with several prestigious awards, including the COVID-19 Dataset Award, the AHS Award from HMC, and the National AI Competition award for his contributions to the fight against COVID-19. His team earned a gold medal at the 13th International Invention Fair in the Middle East (IIFME). Additionally, he has been listed among the Top 2% of scientists in the world by Stanford University.

Sabri Boughorbel

PhD
Lead Scientist, Qatar Computer Research Institute, Hamad Bin Khalifa University, Doha, Qatar

Dr. Sabri Boughorbel serves as a Lead Scientist at Qatar Computing Research Institute (QCRI) within Hamad Bin Khalifa University (HBKU). His research focuses on artificial intelligence applications in healthcare, particularly on large language models. He currently leads the pre-training initiatives for the Fanar project while pursuing research in multimodal LLMs. Before joining QCRI, Dr. Boughorbel held the position of Staff Scientist at Sidra Research, where he led the Machine Learning for Health group. During his tenure, he secured multiple research grants for developing AI models focused on clinical applications utilizing electronic health records. His industry experience includes working as a Senior Scientist at Philips Research Laboratories in the Netherlands. Dr. Boughorbel holds a PhD from Paris-Saclay University, bringing a combination of academic and industrial expertise to his current role

Serkan Kiranyaz

PhD
Professor, Department of Electrical Engineering, College of Engineering, Qatar University, Doha, Qatar

Prof. Serkan Kiranyaz received his BS and MS degrees in the Electrical and Electronics Department at Bilkent University, Ankara, Turkey, in 1994 and 1996, respectively. He received his PhD degree in 2005 and his Docency in 2007 from the Tampere University of Technology, Institute of Signal Processing respectively. He worked as a Professor in the Signal Processing Department at the same university from 2009 to 2015. He currently works as a Professor at Qatar University.

Prof. Kiranyaz has noteworthy expertise and background in various signal processing domains. He published three books, 13 book chapters, 10 patents/applications, more than 150 journal articles in several IEEE Transactions and other high-impact journals, and more than 120 papers in international conferences. He served as PI and LPI in several national and international projects. His principal research field is machine learning and signal processing. He is rigorously aiming to reinvent the ways in novel signal processing paradigms, enriching them with new approaches, especially in machine intelligence, and revolutionizing the means of “learn-to-process” signals. He made significant contributions to bio-signal analysis, particularly EEG and ECG analysis and processing, classification and segmentation, computer vision with applications to recognition, classification, multimedia retrieval, evolving systems and evolutionary machine learning, swarm intelligence, and evolutionary optimization.

Prof. Kiranyaz’s contributions to AI and computer vision resulted in state-of-the-art algorithms in various domains, especially biomedical signal analysis and generation. In 2019, he won the Research Excellence Award and Merit Award of Qatar University. With his two teams, he won the second and third places in the Qatar National AI competition in 2021. He won the “1st Place Prize in the 2019 IEEE Engineering in Medicine and Biology Prize Paper Award”. For five consecutive years, he was ranked among the 100,000 top scientists Worldwide. He in particular aims at investigating scientific questions and inventing cutting-edge solutions in “personalized biomedicine” which is one of the most dynamic areas where science combines with technology to produce efficient signal and information processing systems meeting the high expectations of the users.

Shimaa Mohammed Sherif

PhD
Post Doctoral Fellow, Pediatric Cancer Omics Lab, Translational Research Department, Sidra Medicine, Doha, Qatar

Dr. Shimaa Sherif is a postdoctoral researcher in the Pediatric Cancer Omics Lab at Sidra Medicine. She earned her PhD in Genomics and Precision Medicine from Hamad Bin Khalifa University, Qatar in 2022. Her PhD research focused on immune profiling of pediatric and adult tumors using gene expression analysis. Currently, she specializes in the bioinformatics analysis of pediatric solid tumors and leukemias, working with whole genome, whole exome, RNA sequencing, DNA methylation, and single-cell transcriptomic data.

As the lead scientist for the Sidra Medicine Pediatric Cancer Biobank, Dr. Sherif performs bioinformatics analysis of clinical samples from pediatric cancer patients, providing critical molecular insights to pathologists and oncologists. She coordinates molecular tumor board (MTB) meetings, facilitating discussions on genomic findings of expedited cases to support clinical decision-making. Before transitioning into research, she worked as a pharmacist in Egypt and Qatar for several years, gaining experience in clinical practice and patient care. Beyond her research, she has supervised Master's and PhD students, mentoring them in bioinformatics and cancer genomics.

Dr. Sherif is also an active reviewer for several peer-reviewed journals, including Frontiers and the Journal for ImmunoTherapy of Cancer (JITC). She holds a Bachelor’s degree in Pharmaceutical Sciences and a Master’s degree in Human Genetics from Alexandria University, Egypt. Her Master's research explored multidrug resistance (MDR) gene polymorphisms and their impact on tyrosine kinase inhibitor response in chronic myeloid leukemia (CML) patients.

Sirajeddin Belkhair

MD, MHSc, FRCSC
Chairman of Neurosurgery Department, Director of Neurosurgery Residency Program, Hamad Medical Corporation, Doha, Qatar

Dr. Sirajeddin Belkhair has served as the Chair of the Neurosurgery Department and the Director of the Neurosurgery Residency Program at Hamad Medical Corporation (HMC) since January 2019. He has also held the position of Chair of the Qatari National Advisory Committee for Neurological Tumors since September 2019. He joined HMC in July 2018 as a Senior Consultant in the Neurosurgery Department. Prior to this, he practiced in the United States as an Assistant Professor in the Neurosurgery Department at Saint Louis University Hospital in Missouri, as well as at hospitals affiliated with Michigan State University in Michigan. He completed his neurosurgery residency training at Dalhousie University in Halifax, Canada. Additionally, Dr. Belkhair completed two clinical fellowships at the University of Toronto, Canada: one in open cerebrovascular neurosurgery and the other in complex spine surgery. This extensive training in North America has equipped him to perform complex cerebrovascular and spine surgeries, significantly enhancing the neurosurgical care offered to patients at HMC.

Dr. Belkhair also holds a Master's degree in Clinical Epidemiology from the University of British Columbia in Vancouver, Canada. He has published more than thirty articles in peer-reviewed journals and textbooks. In addition to his clinical work, he plays a crucial role in advancing research at the Neurosurgery Department at HMC and is the primary author of several research projects, including a randomized controlled trial currently being conducted by him and his team.

Susu Zughaier

MSc, PhD
Infectious Diseases Research Network Chair, Associate Professor of Microbiology, College of Medicine, Qatar University, Doha, Qatar

Dr. Susu Zughaier is an Associate Professor of Microbiology and Immunology and the Chair of the Infectious Diseases Research Network at Qatar University College of Medicine. She has trained as a clinical microbiologist at University College London and was awarded MSc and PhD in Microbiology and Immunology from Cardiff University, UK. She completed her postdoctoral training at Harvard Medical School in Boston, US, and was Assistant Professor of Microbiology and Immunology, at Emory University School of Medicine in Atlanta, US.

Dr. Zughaier’s  research interests are focused on antimicrobial resistance, host-pathogen interactions, nanovaccine development, nanotechnology for the rapid detection of bacterial infections, and artificial intelligence for medical applications. Her translational research is focused on vitamin D immune modulatory effects and related translational studies. Dr. Zughaier published over 100 scientific research papers with an h-index of 37 and was awarded four patents on her discoveries. She has been listed among the top 2% of highly cited authors with impact in their field in 2020 and 2024. She is an active member of various international societies and serves as Associate Editor, Editorial board member, and ad-hoc reviewer for multiple international journals.

Tariq Abbas

MD, PhD
Attending Physician, Urology Division, Sidra Medicine, Doha, Qatar

Dr. Tariq Abbas completed a world-class highly competitive fellowship program in Pediatric Urology in Birmingham, United Kingdom, and a fellowship in Pediatric Urology at Sidra Medicine Hospital, Doha, Qatar. He later finished a PhD in the Department of Health Science and Technology, Aalborg University, Aalborg, Denmark, titled “Development of a Tissue Engineered Urethral Substitute for the Treatment of Severe Hypospadias.” He serves as an Editorial Board Member for many reputed journals and a member of the European Society of Pediatric Surgery (ESPU), and the Society of Academic Surgery and Research (SARS). He is currently a consultant pediatric urologist in Sidra. He has published extensively on pediatric surgery and urology with over 150 peer-reviewed articles and 70 international and local presentations. He conducts several ongoing research projects focusing exclusively on child health with a special interest in artificial intelligence pediatric urology and currently serves on the advisory committee of the international AI-PEDURO Repository.

Tariq Abu Saqri

MSc
Senior Architect - Software, IMT Planning and Governance, Sidra Medicine, Doha, Qatar

Tariq Abu Saqri serves as a Senior Architect - Software at Sidra Medicine. He has over 19 years of experience in information management systems and applications, artificial intelligence (AI) development and governance, data management and governance, and enterprise architecture. Throughout his career, he has demonstrated a strong ability to merge advanced computational techniques with real-world applications, leading initiatives that have significantly impacted various industries, including healthcare, clinical research, information technology, and banking.

Mr. Abu Saqri’s academic journey began with a Bachelor's degree in Management Information Systems, which laid a strong foundation for addressing the gaps between business processes, technology architecture, and frameworks. Building on this foundation, he pursued a Master's degree in Data Science and Artificial Intelligence from the University of Liverpool, equipping him with expertise in data analysis, machine learning, and artificial intelligence skills that are increasingly vital across domains.

In his professional role, Mr. Abu Saqri has led the development and deployment of AI, deep learning, and machine learning applications, workflows, projects, and research initiatives. He has designed and implemented high-performance databases and systems to support efficient data management and analysis for large-scale projects. Additionally, he has successfully implemented high-computational AI infrastructure and clusters integrated with GPUs, enhancing computational capacity for research and clinical applications.

Mr. Abu Saqri’s recent role as an Enterprise Architect involved leading technology implementation, AI governance and initiatives, and data governance. He aligned cutting-edge AI and data strategies with organizational goals, ensuring impactful business outcomes. His technical expertise encompasses programming languages mainly Python, SQL, and PL-SQL, proficiency in machine learning frameworks, and experience with data visualization tools.

With a strong aptitude for interdisciplinary collaboration and problem-solving, Mr. Abu Saqri is committed to leveraging his knowledge to make meaningful contributions to Computer Science and Engineering. He is particularly interested in exploring the application of AI and machine learning in healthcare data systems and enhancing collaboration between clinicians and researchers.

Yosra Mekki

College of Medicine, Qatar University, Doha, Qatar
Communications Fellow, npj Digital Medicine

Yosra Mekki is an award-winning extended reality (XR) developer and aspiring sports medicine physician in Qatar, focusing on clinician-engineer collaboration and athlete health. She is the inaugural Nature Digital Medicine communications fellow, hosting their podcast, and leads Qatar's national AI and XR healthcare network. Her work includes developing educational VR applications addressing antibiotic resistance and AI algorithms for COVID-19 pre-screening. Ms. Mekki has lectured internationally, including at the International Olympic Committee flagship conference, led an international AI journal club, and taught a medical AI elective at Qatar University. Some of her collaborations include projects with Aspetar, the Football Association, and the Mayo Clinic on initiatives related to digitizing athlete health, AI, and aerospace medicine. She also completed a fellowship at Mayo Clinic's STR-X program, focusing on athlete health and aerospace medicine, was a visiting student at King's College London at the Quinn NASA Lab, and serves as research lead at the Clinician Engineer's Hub based at Cambridge.

Ms. Mekki is set to complete her MD this April and plans to pursue a dual track in healthcare innovation, specializing in sports medicine and hand. She is affiliated with the College of Medicine, Qatar University, Doha, Qatar, and is an Ambassador for Google's Tech Makers. She serves on the Editorial Board of NPJ Digital Medicine and is a Reviewer for The British Journal of Sports Medicine (BJSM) and Springer Nature. She has co-authored numerous book chapters and articles in the medical AI and XR space, serves on several scientific committees and strategic boards, and has chaired international workshops and organized entrepreneurial challenges.

Ahmad Abdel-Hafez

PhD
Assistant Professor, Data Science & Artificial Intelligence, College of Computing and Information Technology, University of Doha for Science and Technology, Doha, Qatar

Dr. Ahmad Abdel-Hafez is an Assistant Professor and data scientist specializing in Machine Learning (ML), Artificial Intelligence (AI), and applied data science. His expertise lies in using ML algorithms to address complex data science challenges in healthcare systems, finance, education, and industry. Dr. Abdel-Hafez has a proven track record of applying data-driven insights to enhance clinical decision-making and operational efficiency, particularly in healthcare settings. Before joining the University of Doha for Science and Technology (UDST), Dr. Abdel-Hafez worked as a data scientist consultant and expert at Queensland Health, Australia, where he collaborated with multidisciplinary teams on impactful projects from inception to deployment.

Dr. Abdel-Hafez has led and contributed to successful grant applications exceeding $1.4M, where he played a central role in the data analytics and data science components of these projects. He has worked on high-impact healthcare solutions, including personalized dosing systems and automated triaging of outpatient referrals, demonstrating his commitment to driving positive change in healthcare. Dr. Abdel-Hafez is passionate about mentoring the next generation of researchers, having co-supervised several PhD students to graduation at the University of Queensland (UQ) School of Pharmacy, Queensland University of Technology (QUT) School of Public Health & Social Work, and the School of Computer Science at QUT. Through his work, he continues to bridge the gap between technology and healthcare, fostering interdisciplinary collaborations with clinicians, researchers, and institutes to advance the role of AI in improving healthcare outcomes.

Moshiur Farazi

PhD
Assistant Professor, Data Science & Artificial Intelligence, College of Computing and Information Technology, University of Doha for Science and Technology, Doha, Qatar

Dr. Moshiur Farazi is a distinguished researcher and educator with over a decade of experience in industrial innovation and biomedical engineering. He earned his PhD in Computer Vision and Machine Learning from the Australian National University, following a Master’s in Biomedical Engineering from the University of British Columbia in Canada. His academic journey laid a solid foundation for his work at the intersection of artificial intelligence, medical imaging, and real-world applications.

Dr. Farazi’s work spans several countries, including Australia, Canada, the United States, and the Netherlands. In Canada, he developed 3D biomechanical models and interactive training platforms to support diagnostic imaging and clinical decision-making. His projects in the US and the Netherlands have focused on applying AI techniques to streamline imaging workflows and enhance diagnostic accuracy. At Data61–CSIRO in Australia, he led initiatives that integrated cloud-based AI solutions with practical applications, working closely with government agencies and industry partners to translate research into usable tools. Currently serving as an Assistant Professor at the University of Doha for Science and Technology in Qatar, Dr. Farazi leverages his deep expertise in AI, machine learning, and medical imaging to drive practical innovation. In his role, he focuses on collaborative research initiatives that bridge academic theory with real-world applications, leading to tangible, meaningful, and measurable outcomes.

Oussama Djedidi

PhD
Assistant Professor, Data Science & Artificial Intelligence, College of Computing and Information Technology, University of Doha for Science and Technology, Doha, Qatar

Dr. Oussama Djedidi is an Assistant Professor at the University of Doha for Science and Technology. He holds a PhD in Computer Engineering and Automation and works as a Senior Data Scientist, specializing in the semiconductor, sensor, and glass industries. With a strong background in research and development, he focuses on AI-driven process control and virtual metrology. Dr. Djedidi's contributions have advanced data-driven models for process automation, real-time control algorithms in glass manufacturing, and sensor-based pollution detection. His research emphasizes applied machine learning, control engineering, and advanced modeling in smart systems.