Rozenn Dahyot is a Professor of Computer Science at Maynooth University within the Faculty of Science & Engineering. She previously held roles as Assistant and Associate Professor in Statistics at Trinity College Dublin (2008-2021) and Lecturer in Computer Science (2005-2008). Her research interests bridge Digital Signal Processing, Computer Vision, Machine Learning, and Statistical Analysis. She organized the European Signal Processing Conference (EUSIPCO2021) in Dublin and served as President of the Irish Pattern Recognition and Classification Society (IPRCS) from 2014-2020. Her work spans topics like semantic scene understanding, CNN compression, and medical image segmentation. Key contributions include advancements in graph-based image analysis, reinforcement learning optimization, and AI-driven systems for disaster management. Dahyot is a member of IEEE, ACM, and EURASIP, contributing to both academic and industrial collaborations.
Professor Marek Sanak serves as Full Professor at the Department of Internal Medicine, Jagiellonian University Medical College in Cracow, Poland. He concurrently holds leadership positions as Acting Director of the Department of Forensic Medicine, Head of the Division of Molecular Biology and Clinical Genetics, and Vice-Rector for Research and International Cooperation since 2016. His academic foundation includes: MD from Jagiellonian University Medical College Specialization in Pediatrics and Genetics PhD from Jagiellonian University Research appointments at Harvard University, University of Paris VI, and University of Zurich Professor Sanak's research integrates clinical genetics with molecular immunology, focusing on asthma pathogenesis, lipid mediators of inflammation, and genetic diagnostics. His laboratory employs advanced techniques including deep DNA/RNA sequencing to identify biomarkers and elucidate disease mechanisms. The work bridges fundamental molecular discoveries with clinical applications in respiratory diseases, allergic disorders, and forensic medicine, demonstrating particular expertise in aspirin-exacerbated respiratory disease and epigenetic regulation of inflammatory pathways. Analysis of his recent publications reveals a strategic evolution from classical asthma research toward molecular genetics and viral pathogenesis. His 2017-2021 work increasingly incorporates epigenetic approaches (DNA methylation, microRNA profiling) while expanding into SARS-CoV-2 research during the pandemic. The publications demonstrate interdisciplinary integration across immunology, respiratory medicine, and molecular diagnostics, with consistent focus on translational applications. His distinguished career has been recognized through numerous honors: The Lancet Investigators Award on Asthma (1997) Polish Ministry of Health Individual Prize (1999) Jagiellonian Laurel (2012) Pro Arte Docendi Award (2014/15) Gold Medal for Long Service (2019) Top 2% of world scientists ranking (Elsevier 2022) As Vice-Rector for Research, Professor Sanak has significantly expanded international collaborations with King's College London, University of Southampton, and University of Zurich. His leadership has secured substantial funding for molecular diagnostics and inflammatory disease research while mentoring numerous early-career researchers. He delivers invited lectures globally for organizations including the American Thoracic Society and European Academy of Allergy and Clinical Immunology. Professor Sanak directs integrated research units across the Division of Molecular Biology and Clinical Genetics, Division of Biochemical and Molecular Diagnostics at University Hospital Cracow, and the Department of Forensic Medicine. These teams combine clinical service with basic research to advance genetic diagnostics and understand disease mechanisms, maintaining forensic genetics expertise developed over 20 years of practice.
Prof. Dr. Raphael Sznitman serves as Director of the ARTORG Center for Biomedical Engineering Research and Head of the Artificial Intelligence in Medical Imaging group at the University of Bern, Switzerland, holding a Full Professor position in AI for Medical Imaging since 2015. Education: PhD in Computer Science, Johns Hopkins University (2011) MSc in Computer Science, Johns Hopkins University (2009) BSc in Cognitive Systems, University of British Columbia (2007) Research Interests: Sznitman's work centers on computational vision , probabilistic methods , and statistical learning applied to medical imaging challenges. His group develops AI algorithms for ophthalmic diagnostics, surgical robotics, and medical image analysis, with emphasis on OCT, surgical phase recognition, and domain adaptation techniques. Key application areas include retinal disease detection and cataract surgery automation. Publication Trends: His 2021-2025 publications reveal concentrated efforts in deep learning for medical imaging , particularly in ophthalmology (OCT analysis) and surgical video understanding. Emerging themes include LLM applications for clinical monitoring, unsupervised out-of-distribution detection for surgical safety, and physics-informed AI for multimodal medical data fusion. Research Leadership: As ARTORG Center Director, Sznitman oversees interdisciplinary research bridging computer science and clinical medicine. His group collaborates extensively with Bern University Hospital clinicians on translational projects, securing funding for AI-driven diagnostic tools and surgical assistance systems. Current initiatives focus on real-time intraoperative guidance and spaceflight ophthalmology applications. Laboratory: The Artificial Intelligence in Medical Imaging group operates within ARTORG's dedicated facilities, maintaining partnerships with surgical robotics labs and ophthalmology departments for clinical validation of AI systems. Their work integrates multimodal data streams including OCT, VR perimetry, and surgical video feeds.
Preet Singh is a Professor and Associate Chair for Graduate Studies in the School of Materials Science and Engineering at Georgia Tech, with affiliations to the College of Engineering. His research focuses on corrosion science, electrochemistry, and environmental degradation of materials, particularly metals and alloys. Prior to joining Georgia Tech in 2003, he was a faculty member at the Institute of Paper Science and Technology (IPST), where he investigated corrosion issues in the pulp and paper industry. Professor Singh's work explores fundamental mechanisms of material degradation in industrial environments, aiming to develop mitigation strategies against environment-induced failures. Key research areas include corrosion fatigue, hydrogen embrittlement, stress corrosion cracking, and oxidation behavior. His group employs experimental approaches to study material reliability under varying chemical and mechanical conditions. Recent publications demonstrate interdisciplinary collaboration across oncology, agriculture, and energy systems, reflecting broad applications of materials science principles. Research trends show increased focus on biomedical materials and sustainable technologies alongside core corrosion studies. Professor Singh advises graduate students including Abdullah Alzubail, Yousif Al Rabie, Sai Shreeya, Yara, and Sean Li. He directs the Corrosion and Materials Reliability Laboratory (CMCRL), which partners with industry to solve practical engineering challenges related to material performance.
Dr. Ian Wilson is a researcher at Newcastle University with a focus on medical genetics, nephrology, and genomic analysis. His work spans genetic determinants of kidney diseases, mitochondrial disorders, and biomarker development. Notable contributions include studies on uromodulin genetics in African populations, copy-number variations in rare diseases, and kidney ciliopathies. He has collaborated extensively on projects involving genome sequencing, mitochondrial replacement therapy, and muscular dystrophy biomarkers. Wilson's research integrates computational tools like machine learning for predictive modeling in urolithiasis and employs advanced imaging techniques for disease progression monitoring. Key areas: Genetic epidemiology, renal genomics, mitochondrial DNA analysis Focus on translational applications: Biomarker development for kidney stones and muscular dystrophies Interdisciplinary collaborations in ophthalmology and orthopedics His publications reflect a commitment to advancing diagnostic accuracy and understanding complex genetic disorders through multi-omics approaches.
Professor Maryse Bailly is a Professor of Cell Biology at the UCL Institute of Ophthalmology, University College London, where she has been employed since December 2000, progressing from Lecturer to Reader/Associate Professor and finally to Professor in October 2020. Her research focuses on understanding fibroblast behavior in the context of ocular diseases, scarring, and fibrosis, with particular emphasis on cytoskeletal dynamics and mechanotransduction pathways. Education: Doctor of Philosophy, Universite Claude Bernard (Lyon 1), 1992 Diplome Universitaire de Technologie, Universite Claude Bernard (Lyon 1), 1983 Professor Bailly's research program investigates how fibroblasts sense and respond to mechanical and chemical stimuli in their environment, with applications to multiple ocular pathologies including trachoma, thyroid eye disease, glaucoma scarring, and myopia. Her laboratory has developed innovative in vitro and ex vivo models that allow the study of tissue contraction mechanisms within pseudo-physiological 3D environments, leading to the identification of novel therapeutic targets such as the Rac1 small GTPase and the MRTF/SRF pathway. She has established significant collaborations with clinicians at Moorfields Eye Hospital, particularly with Dr. Annegret Dahlmann-Noor on pediatric eye growth and myopia research. Analysis of Professor Bailly's publication record reveals a consistent focus on fibroblast mechanobiology with increasing emphasis on pediatric ocular development in recent years. Her work bridges fundamental cell biology with translational applications, particularly in understanding the biomechanical properties of fibroblasts in myopia development and post-surgical scarring. The research demonstrates strong interdisciplinary connections between ophthalmology, cell biology, and tissue engineering. Teaching: CELL0016 - Actin cytoskeleton and Intermediate Filaments CELL0017 - Fibrosis and mechanotransduction CELL0009 - Models organisms and techniques MECH0031 MSc Biomaterials & Tissue Engineering - Modeling tissue contraction and fibrosis
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.
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.
Dale L. Boger is a Professor of Chemistry at The Scripps Research Institute (TSRI), where he leads the Boger Group specializing in synthetic organic and medicinal chemistry. His academic roles include serving as co-Chair (2017-2018) and Chairman (2013-2017) of the Chemistry Department. Boger earned his B.S. from the University of Kansas (1975) and Ph.D. from Harvard University (1980). His research focuses on total synthesis of natural products, development of synthetic methodologies, and antibiotic design, particularly addressing antibiotic resistance via glycopeptide analogs like vancomycin. Key honors include the Paul Janssen Prize (2002), RSC Robert Robinson Award (2017), and election to the National Academy of Sciences (2014). His work spans collaborations in bioorganic chemistry, molecular modeling, and drug design. The Boger Group’s lab includes numerous students and postdocs, advancing projects such as maxamycins and guanidine-modified vancomycins. Funding includes NIH grants and industry partnerships, highlighting his contributions to both academic and applied research. Research highlights include groundbreaking studies on vancomycin analogs with dual mechanisms of action to combat resistance, as well as contributions to TLR agonists and neurovascular drug delivery. His legacy includes over 300 publications and impactful patents in antibiotic design and synthetic organic chemistry.
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.
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.
Istvan Albert is a Research Professor of Bioinformatics at Pennsylvania State University , affiliated with the Department of Biochemistry and Molecular Biology . He leads the Bioinformatics Consulting Center and teaches BMMB 852: Applied Bioinformatics . Research Interests: Specializing in bioinformatics, large-scale biological data analysis, microarray and sequence analysis, scientific programming, algorithm development, and database-driven web development. His work spans gene ontology visualization , RNA-Seq analysis , and coronavirus research . Software Development: Created GeneScape for gene function visualization and bio for bioinformatics workflows. Maintains the Biostar Handbook series and the Biostars Q&A Forum , a leading bioinformatics resource.
Prof. Dr. Kathrin Schumann is an Assistant Professor at the Technical University of Munich (TUM), leading the 'Engineering Immune Cells for Therapy' group within the TUM School of Medicine and Health. Her research focuses on CRISPR-based engineering of human immune cells to develop novel therapies for autoimmune and tumor diseases. She holds a doctorate from the Max Planck Institute of Biochemistry and has conducted postdoctoral research at the University of California, San Francisco, under Professors Alex Marson and Jeffrey Bluestone. Dr. Schumann’s academic career includes a Presidential Postdoc Fellowship at Novartis (Basel) and a tenure-track appointment at TUM since 2018. Her work emphasizes genomic editing of T cells to study gene function and improve cell therapy safety. Key research themes include CRISPR-mediated gene silencing, T cell receptor engineering, and HIV-host interaction studies. Education: Bachelor/Master in Biochemistry, University of Tübingen PhD, Max Planck Institute of Biochemistry (Martinsried) Postdoc, University of California, San Francisco (UCSF) Her research has yielded breakthroughs in CRISPR applications for T cell therapy, including PD-1 disruption to enhance anti-tumor efficacy and targeted editing of T cell receptors. Awards include a DFG research grant (2016). Notable achievements include the development of CRISPR ribonucleoprotein platforms for primary T cells and insights into metabolic checkpoints in T cell exhaustion. Her lab collaborates globally to translate CRISPR-based discoveries into clinical therapies.
Dr. Teresa Puthussery is an Associate Professor in the School of Optometry & Vision Science at the University of California, Berkeley. Her research focuses on retinal neurobiology and neurophysiology, investigating how visual signals are encoded in healthy retinas and disrupted during degeneration. She uses advanced techniques like patch-clamp electrophysiology, immunohistochemistry, and microscopy to study retinal circuits, neurotransmitter receptors, and ion channels. Dr. Puthussery teaches courses on vision science anatomy, physiology, and problem-based learning, including VISION SCIENCE 206B/C and 260C. Her research explores questions such as how retinal neurons extract motion/spatial details, how photoreceptor mutations cause degeneration, and how inner retinal circuits adapt post-photoreceptor loss. Recent work includes studies on ON-type direction-selective ganglion cells, optogenetic therapy for vision restoration, and calcium dynamics in foveal ganglion cells post-degeneration. She collaborates on projects involving primate and rodent models, contributing to understanding retinal disease mechanisms and therapeutic targets. Dr. Puthussery’s lab (retinalab.berkeley.edu) emphasizes translational research, bridging basic science and clinical applications. Her work has been published in journals like Nature and Cell Reports , with a focus on retinal degeneration, synaptic plasticity, and optogenetic interventions. She actively participates in training future vision scientists through Berkeley’s Optometry program and oversees GSI affairs as a faculty advisor.
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.
