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Sohmyung Ha is an Associate Professor of Electrical Engineering and Bioengineering at NYU Abu Dhabi and holds a Global Network position at NYU Tandon School of Engineering. He leads the Integrated BioElectronics Laboratory, focusing on advancing silicon integrated technologies for biomedical applications such as implantable devices and wearable sensors. His expertise spans biomedical circuits, neural interfaces, and wireless power systems. Education: MS (2004, KAIST), PhD (2016, UC San Diego) with a Best Thesis Award. Prior industry experience includes analog circuit design at Samsung Electronics (2006-2010). Academic affiliations include NYU Abu Dhabi, NYU Tandon, and global collaborations. Research interests include high-performance biomedical sensors, neural prosthetics, and energy-efficient bioelectronic systems. Notable achievements include a Best Paper Award (ISCAS 2024) and innovations in impedance spectroscopy and neural interface ICs. Current projects emphasize closed-loop neural interfaces, subcutaneous glucose monitoring, and retinal prostheses. His lab develops miniaturized, power-autonomous systems for healthcare applications.

• Biomedical Engineering
• Neural Engineering
• Wearable Sensors
• +3 more

Jeffrey Glassberg, MD, is a Professor in both the Department of Emergency Medicine and the Division of Hematology and Medical Oncology at the Icahn School of Medicine at Mount Sinai. His clinical and research focus centers on hematology and emergency medicine, with particular attention to sickle cell disease and its complications. Education MD, Washington University Internship and Residency in Emergency Medicine, Bellevue Hospital Center Research Focus Dr. Glassberg's work explores the intersection of emergency care and hematological disorders, particularly sickle cell disease. His research includes epidemiological studies of ICU utilization and advanced imaging techniques to assess retinal blood flow abnormalities in sickle cell patients. Publications Recent work published in Chest and Ophthalmic Surgery Lasers and Imaging Retina focuses on clinical outcomes and vascular complications in sickle cell disease. Contact Information Phone: 212-824-8074 Address: One Gustave L. Levy Place, Box 1620, New York, NY 10029

• Emergency Medicine
• Hematology
• Medical Oncology
• +1 more

Xenophon Papademetris is a Professor of Biomedical Informatics & Data Science and Radiology & Biomedical Imaging at Yale School of Medicine. He serves as Associate Director of Biomedical Imaging Data Sciences at Yale Biomedical Imaging Institute and directs the Medical Software and Medical Artificial Intelligence Certificate Program. PhD in Electrical and Information Sciences from Yale University (2000) BA from Cambridge University (1994) Postdoctoral Fellowship at Yale University (2002) His research focuses on medical image analysis, machine learning, and biomedical software development. He has developed tools like BioImage Suite Web and contributed to standards committees at the Association for the Advancement of Medical Instrumentation (AAMI). His work spans modalities including MRI, CT, PET, and optical imaging. Recent publications emphasize neuroimaging analysis, explainable AI in healthcare, and multimodal data integration across species. He leads NIH-funded research under the BRAIN Initiative (R24 MH114805) and has authored a textbook on Medical Software published by Cambridge University Press. IEEE Senior Member Yale Brown-Coxe Postdoctoral Fellowship Harding Bliss Prize for Excellence in Engineering He directs the BioImage Suite Project, creating web-based image analysis tools using JavaScript and WebAssembly. His teaching includes both academic courses and a Coursera program on Medical Software with over 14,000 enrollments.

• Medical Image Analysis
• Machine Learning
• Biomedical Software Development
• +7 more

Dr. Tan Viet Tuyen Nguyen is a New Frontiers Fellow (Lecturer) in AI at the University of Southampton, specializing in Human-Centered Artificial Intelligence and Social Human-Robot Interaction. His research focuses on multimodal learning for robots to adapt their behavior to human social needs, with applications in healthcare, education, and service environments. Prior to this role, he was a Research Associate at King’s College London and a Research Assistant on the EU-funded CARESSES project, developing culturally-aware assistive robots for elderly support. Education: PhD in Information Science (Robotics) from Japan Advanced Institute of Science and Technology. He has organized conferences such as the IEEE RO-MAN 2022 special session on nonverbal communication and served as a reviewer for top-tier robotics and AI conferences. Research Interests include: Human-Robot Collaboration, Multimodal Perception, Generative AI for Social Interaction, and Context-Aware Robot Behavior Generation. His work has been recognized with awards including the Best Paper Award at ROMAN 2022 and the Prospective Research Award at ICServ 2023. Teaching Responsibilities include courses on Biologically Inspired Robotics, High-Level Programming, and MSc/Undergraduate project supervision. He currently oversees two PhD students and collaborates on projects like 'Exploring the impact of AI-driven writing of engagement in climate change' and 'Bridging Generations and Cultures through Generative AI.' Labs/Teams: Member of the Agents, Interaction and Complexity Centre and the Centre for Robotics Research at Southampton.

• Human-centered Artificial Intelligence
• Social Human-Robot Interaction
• Multimodal Perception and Interaction
• +5 more

Professor Athina E Markaki serves as Professor of Materials & Biomedical Engineering in the Department of Engineering at the University of Cambridge, leading research in advanced biomaterials and tissue engineering solutions for regenerative medicine with emphasis on vascularization and tubular scaffold development for human conduit replacement. Her academic credentials include a Diploma in Metallurgical Engineering (8.6/10) from the National Technical University of Athens and a PhD in Materials Science from the University of Cambridge. Markaki's research program centers on vascularisation techniques for clinically relevant tissue dimensions and tubular scaffolds to replace diseased or damaged human conduits, integrating biomaterials science with regenerative medicine principles. Key applications span liver tissue engineering, neural crest-derived stem cell differentiation, and vascular graft development, with strong translational focus on orthopaedic and cardiovascular medical devices. Analysis of her recent publications reveals dominant trends in biomimetic scaffold design, particularly collagen-based tubular structures and hydrogel systems for vascularized tissue constructs. Her work demonstrates interdisciplinary convergence of AI-driven retinal assessment, glioblastoma modeling, and self-healing cementitious materials, with consistent emphasis on clinically applicable regenerative solutions for liver, bone, and neural tissues. Her distinguished scientific contributions are recognized by major awards: Rosetrees Trust 2017 Interdisciplinary Award European Research Council (ERC) Starting Grant (2010) Advanced EPSRC Fellowship (2005) De Montfort Award at SET for Britain National Event (2004) Young Scientist Prize 2003 (5th Euromech Solid Mechanics Conference) Multiple academic excellence awards from Greek foundations Markaki directs a well-funded research program including ERC and EPSRC grants, mentoring graduate students in tissue engineering while teaching core engineering curricula covering plastic deformation, fracture mechanics, and medical materials design. Her group maintains strong industry and clinical partnerships to advance regenerative technologies. Her laboratory, accessible via http://www-memti.eng.cam.ac.uk/, specializes in vascularized tissue constructs and tubular scaffolds using laser-based manufacturing, biomimetic design, and hydrogel engineering to address critical challenges in tissue replacement and disease modeling.

• Tissue Engineering
• Biomaterials
• Regenerative Medicine
• +3 more

Dr. Anagha Vaze is a Clinical Lecturer affiliated with the University of Sydney's Faculty of Medicine and Health (FMH) and the Save Sight Institute. Her expertise lies in ophthalmology, with a focus on retinal disorders, diabetic eye diseases, and clinical research. She has contributed to studies on VEGF inhibitors, corticosteroid delivery platforms for macular edema, and the application of genomics in retinal diagnostics. Research Interests: Retinal degeneration and vascular abnormalities Management strategies for diabetic retinopathy and macular telangiectasia Clinical outcomes of anti-VEGF therapies Infectious diseases in immunocompromised patients (e.g., heart transplant recipients) Her publications (2014–2022) emphasize observational studies, drug delivery innovations, and case reports on rare infections. Key contributions include assessing treatment discontinuation protocols for neovascular AMD and exploring photobiomodulation for diabetic macular edema. While no scientific awards or grants are explicitly listed, her work reflects active engagement in clinical research and patient care. She is part of the Save Sight Institute, a prominent research center within the FMH, focusing on vision science and ophthalmic advancements.

• Ophthalmology
• Retinal Disorders
• Diabetic Retinopathy
• +3 more

Mahmoud El-Sakka is an Associate Professor at the Department of Computer Science, University of Western Ontario since 1999. Previously, he was a faculty member at the University of Waterloo (1997–1999). He holds a B.Sc. and M.Sc. from Alexandria University (Egypt) and a Ph.D. in Systems Design Engineering from the University of Waterloo. His research focuses on medical imaging, image processing, and computer-aided diagnostics. He has served as Chair of the graduate program (2002–2007) and undergraduate program (2017–present) in Computer Science at Western Ontario. El-Sakka is a Senior Member of the IEEE and a licensed Professional Engineer in Ontario. His work spans grants from NSERC, internal university funding, and industry collaborations. Major research areas include image compression, segmentation, and medical applications like vascular analysis and echocardiography. He has led over 20 funded projects since 1999, emphasizing interdisciplinary approaches in healthcare technology. Academic contributions include advisory roles in summer programs, thesis evaluations, and conference participation. His service includes roles as Pro-Chancellor at convocations and involvement in equipment purchasing committees. Collaborations include consulting with NCR Canada and VRP Web Technology.

• Image Compression
• Medical Imaging
• Image Segmentation
• +5 more

Weiyu Xu is a Professor at the University of Iowa, affiliated with both the Department of Electrical and Computer Engineering and the Department of Applied Mathematical and Computational Sciences. He joined the College of Engineering in 2012 and leads the Intelligent Information Processing Lab (IIPL). Ph.D., Electrical Engineering, California Institute of Technology, 2009 M.S., Electrical Engineering, California Institute of Technology, 2006 M.S., Electronic Engineering, Tsinghua University, 2005 B.E., Information Engineering, Beijing University of Posts and Telecommunications, 2002 His research focuses on compressive sensing, information theory, signal processing, network optimization, and deep learning applications in medical imaging and cybersecurity. He has made significant contributions to adversarial attack robustness, distributed optimization algorithms, and medical imaging techniques for OCT segmentation and brachytherapy. Recent publications highlight trends in Adversarial machine learning Medical imaging algorithms Compressed sensing for diagnostics Optimization in wireless communication He has also contributed to federated learning over tree networks and theoretical guarantees for sparse signal recovery. Weiyu Xu's lab, IIPL, integrates deep learning with classical optimization and signal processing. His work bridges foundational theories (e.g., information-theoretic robustness) with real-world applications in healthcare (e.g., cancer treatment planning) and communication systems (e.g., MIMO channel estimation).

• Compressive sensing
• Information and coding theory
• Signal processing
• +12 more

Joel Zylberberg is an Adjunct Assistant Professor at the University of California, Los Angeles (UCLA), affiliated with the Department of Ophthalmology within the School of Medicine . His research bridges Computational Neuroscience , Neural Networks , and Machine Learning , focusing on how neural activity and biological mechanisms inform artificial intelligence and visual cortex dynamics . Joel's work explores retinal computation , population coding , and neural adaptation , often analyzing mouse visual cortex and neurophysiological data . His recent publications highlight trends in dynamic retinal processes , stimulus-driven network topology , and brain-inspired machine learning , emphasizing the interplay between biophysics and computational modeling . Collaborators include Greg Field (UCLA), Richard Born (Harvard), and Michael DeWeese (UC Berkeley), with affiliations spanning institutions like University of Washington and University of California, San Diego (UCSD). His work appears in journals such as Nature Neuroscience , Neuron , and PLOS Computational Biology .

• Computational Neuroscience
• Neural Networks
• Retinal Computation
• +7 more

Yu-Chong Tai is the Anna L. Rosen Professor of Electrical Engineering and Medical Engineering at the California Institute of Technology. He holds the Cherng Leadership Chair (2017–22) and has served as Executive Officer (2005–2008, 2013–22). His research focuses on applying MEMS/NEMS technologies to medical applications, including medical implants, microfluidics, and lab-on-a-chip systems. Tai leads the Caltech MEMS Laboratory, an 8,000-square-foot facility with clean-room and biological labs dedicated to biomedical device development. Education: B.S., National Taiwan University (1981); M.S., University of California (1986); Ph.D., 1989. Academic progression: Assistant Professor (1989–95) → Associate Professor (1995–2000) → Professor (2000–13) → Rosen Professor (2013–present). Research interests span medical devices, Bio-MEMS, microfluidics, drug delivery, and implantable systems like retinal prosthetics and spinal stimulators. His group collaborates with UCSF, USC, UCLA, and industry partners to advance neural implants and micro-scale medical technologies. Key awards: Member of the National Academy of Engineering, Elected to the National Academy of Inventors Notable projects include HPLC-on-a-chip, wireless drug delivery systems, and oxygen-permeable implant coatings. Tai teaches courses on medical device design and micro/nano technology, fostering interdisciplinary innovation.

• Medical Devices
• MEMS (Microelectromechanical Systems)
• Bio-MEMS
• +7 more

Albert M. Lai, PhD, is a Professor of Medicine and Computer Science & Engineering at Washington University in St. Louis, serving as Chief Research Information Officer (CRIO) for the School of Medicine and Deputy Director of the Institute for Informatics, Data Science and Biostatistics (I²DB). He leads WashU Medicine's data warehousing and informatics services, driving innovation in clinical research infrastructure. His expertise spans biomedical informatics, natural language processing (NLP), and telemedicine. Dr. Lai is also Deputy Faculty Lead for WashU’s Digital Transformation initiative, focusing on secure AI integration with sensitive healthcare data. He holds affiliations with the Institute for Public Health, Siteman Cancer Center, and the Center for Applied Health Informatics (CAHI). Research Interests: Dr. Lai develops informatics infrastructure to support clinical trial prescreening, leveraging NLP and machine learning for phenotype extraction from EHR data. He also explores telemedicine, mobile health applications, and EHR-driven cardiovascular health interventions for cancer survivors. His recent work addresses AI ethics in healthcare, including responsible data sharing and bias mitigation in generative AI models. Key Contributions: Over 77 peer-reviewed publications across clinical informatics, AI in healthcare, and pandemic response strategies. His projects include EHR-based cardiovascular health tools, SARS-CoV-2 surveillance in schools, and machine learning models for predicting transplant outcomes. Active mentorship of PhD/MSTP students in translational informatics and data science. Labs/Teams: Leads the Informatics Services Core and collaborates with the CRITICAL consortium for intensive care analytics. Engages in multi-institutional initiatives like the Greater Plains Collaborative for cancer data integration.

• Biomedical Informatics
• Clinical Research Informatics
• Consumer Health Informatics
• +5 more

Lama Séoud is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. She holds a Ph.D. in biomedical engineering from Polytechnique Montréal and has postdoctoral experience in industry and research at the National Research Council of Canada. Her research focuses on computer vision and computational medical imaging, with applications in healthcare, robotics, and industrial settings. She collaborates closely with clinicians, industrial partners, and artists to develop solutions for human motion analysis, medical image processing, and 3D imaging techniques. Educations: Ph.D. in Biomedical Engineering, Polytechnique Montréal (2012) M.Sc.A. in Biomedical Engineering, Polytechnique Montréal Diploma in Biomedical Engineering, École Supérieure d’Ingénieurs de Beyrouth (Lebanon) Research Interests: 3D imaging and analysis, human motion analysis, medical image computing, computer vision, machine learning. Her work integrates deep learning with 3D data acquisition and analysis, addressing challenges in healthcare (e.g., scoliosis, breast asymmetry) and industrial human-robot interaction. Key Collaborations: Centre de recherche du CHU Sainte Justine, Regroupement de recherche en intelligence artificielle appliquée aux enfants gravement malades, Institut Transmedtech, and Institut de génie biomédical. Teaching: INF8725 (Digital Signal and Image Processing), INF8801A (Multimedia Applications), GBM6700E (3D Reconstruction from Medical Images). Grants & Support: Received funding from the Quebec Research Fund for AI and health innovation projects. Labs & Teams: Active in multidisciplinary teams focusing on biomedical imaging, robotics, and AI for clinical applications.

• Medical Imaging
• Computer Vision
• Machine Learning
• +3 more

Truong Q. Nguyen is a Professor in the Electrical and Computer Engineering (ECE) Department at the University of California San Diego (UCSD), affiliated with the Jacobs School of Engineering. He holds positions at the Center for Wireless Communications and the California Institute for Telecommunications and Information Technology. His research focuses on image/video processing, wavelets, 3D video technology, and applications in healthcare and robotics. He has authored influential textbooks like Wavelets & Filter Banks and pioneered low-power video processing algorithms for mobile devices. Nguyen earned his B.S., M.S., and Ph.D. in Electrical Engineering from the California Institute of Technology (1985–1989). He held roles at MIT Lincoln Laboratory and Boston University before joining UCSD in 1998. His honors include the IEEE Signal Processing Paper Award (1992), NSF Career Award (1995), IEEE Fellow (2005), and UCSD’s Distinguished Teaching Award (2019). His research interests span 3D video processing, machine learning for health monitoring, and biomedical imaging. Notable contributions include wavelet-based compression techniques and AI-driven medical image analysis. He leads the UCSD Video Processing Lab, exploring computer vision, robotics, and generative AI applications. Nguyen is committed to educational innovation, co-creating programs like the Hands-on Curriculum, Summer Research Internship Program (SRIP), and Project-in-a-Box (PIB) for K-12 students. Nguyen’s work bridges academia and industry, with patents in wavelet design and signal analysis. Recent projects include NSF-funded initiatives to develop inclusive engineering curricula and collaborate on graduate pathways programs through the Inclusive Engineering Consortium (IEC).

• Image/Video Processing
• 3D Video Technology
• Wavelets and Filter Banks
• +5 more

Guojun Chen is an Assistant Professor at the Department of Biomedical Engineering and a member of the Rosalind & Morris Goodman Cancer Institute (GCI) at McGill University . His research focuses on engineering intelligent biomaterials for precision medicine , with emphasis on non-viral genome editing , cold atmospheric plasma (CAP) therapy , and biomaterials-mediated immunotherapy . The lab operates in a multidisciplinary environment , integrating principles from materials science , chemistry , biology , and health sciences . Education : Ph.D. from University of Wisconsin-Madison (2017), Postdoc at UCLA (2020) Research Themes : Genome Editing Delivery : Designing non-viral vectors for efficient CRISPR/Cas9 delivery in vivo. CAP-mediated Immunotherapy : Developing portable cold plasma devices to synergize with immune checkpoint blockade and study CAP’s immunological mechanisms. Biomaterials-based Immunotherapy : Reprogramming tumor microenvironments using bioresponsive materials to enhance immune responses. Publication Trends : Recent work spans responsive nanomaterials , genomic editing systems , and plasma oncology , with a focus on cancer immunotherapy , diabetes diagnostics , and bioinspired medical devices . Scientific Awards : Canada Research Chair (2024, 2025) McGill's President's Prize for Emerging Researchers (2025) FRQS Chercheurs-boursiers (2022) Chinese Association for Biomaterials Young Investigator Award (2022) NSERC Discovery Grant (2021) Advising & Grants : Supervises 14 current graduate and undergraduate students. Secured $5M+ in funding from CIHR , NSERC , CCS , and CFI , including multi-institutional collaborations with Dr. Morag Park , Dr. Réjean Lapointe , and Dr. Ian Watson .

• Biomaterials
• Nanomedicine
• Tissue Engineering
• +5 more

J. Christopher Love is the Raymond A. (1921) and Helen E. St. Laurent Professor of Chemical Engineering at MIT, with affiliations to the Koch Institute for Integrative Cancer Research, Broad Institute, and Ragon Institute. He earned a BS in Chemistry from the University of Virginia and a PhD in Physical Chemistry from Harvard University under George Whitesides, followed by postdoctoral work under Hidde Ploegh at Harvard Medical School. His research focuses on single-cell analysis, precision medicine, and biomanufacturing. The Love Lab develops technologies for drug discovery, vaccine development, and equitable biologic medicine production. Notable successes include pioneering single-cell analysis platforms, advancing metastatic cancer diagnostics via liquid biopsies, and engineering yeast-based vaccine manufacturing. Recent articles highlight innovations in liquid biopsy sensitivity, AI-driven ECG diagnostics, and CAR T-cell therapies. Awards include the Keck Young Scholar (2009), Dana Scholar (2009), and Camille Dreyfus Teacher-Scholar. He co-founded OneCyte, HoneyComb, and Sunflower Therapeutics, and advises multiple biotech companies. His lab emphasizes translational research, integrating chemical and biological engineering principles to address global healthcare challenges. Current work explores manufacturability-by-design for vaccines, tumor immunology, and mucosal vaccine delivery systems.

• Nano-based drugs
• Precision medicine
• Immunology
• +3 more