William Balch, PhD, is a Professor in the Department of Molecular and Cellular Biology at Scripps Research. His research focuses on linking genetic variation in human populations to protein function using machine learning tools like Gaussian Process (GP) modeling. He pioneered concepts in proteostasis and spatial covariance, exploring how genetic and environmental factors influence protein folding and disease. Education: Ph.D. in Microbiology from University of Illinois (1979) Research interests include inherited diseases (e.g., CFTR, AATD, NPC1), aging-related proteostasis collapse, and host-pathogen interactions in SARS-CoV-2. His lab develops computational platforms to model protein design and discover therapeutic interventions. Key projects involve GP-based analysis of genetic diversity, small molecule therapeutics targeting chaperone systems, and understanding viral evolution via spatial covariance. His work bridges genomics and phenomics to address disease mechanisms at atomic resolution. Grants and collaborations focus on protein-folding correction, with applications in precision medicine and climate change mitigation through RuBisCo optimization in plants.
Dr. Lin Su is a Lecturer in Engineering Biology at Queen Mary University of London, leading the Biohybrids group. His research focuses on biohybrid systems in synthetic biology, particularly electron transfer mechanisms between microorganisms and materials, with applications in bioelectrical systems and artificial photosynthesis. Dr. Su holds a PhD in Biomedical Engineering from Southeast University (2021), with postdoctoral research at the University of Cambridge (2021–present). His work includes collaborations with Lawrence Berkeley National Lab and Rice University (2016–2021). He is a Leverhulme Early Career Fellow (2022–2025) and an Isaac Newton Trust Grant recipient. He also serves as a Fellow at Lucy Cavendish College, Cambridge. Research interests span synthetic biology, microbial-material interfaces, and energy-related bioengineering. His lab develops novel platforms integrating living and non-living components for sustainable technologies. Awards: Leverhulme Early Career Fellowship Isaac Newton Trust Grant Fellow of Lucy Cavendish College Grants: Collaborative funding via Leverhulme Trust and Isaac Newton Trust. Labs/Teams: Director of the Biohybrids Group (https://biohybrids.group/), focusing on interdisciplinary engineering-biology research.
Knut Håkon Hole is an Associate Professor at the University of Oslo's Department of Radiology and Nuclear Medicine. His research focuses on diagnostic imaging applications in oncology, particularly in prostate and rectal cancers. He specializes in MRI, PET, and radiogenomics techniques to assess tumor biology, treatment response, and recurrence. Expertise: Prostate cancer imaging, neoadjuvant therapy response, tumor hypoxia, and imaging biomarkers Key affiliations: Oslo University Hospital (Rikshospitalet), Radium Hospital Research interests include: Developing MRI and PET protocols for cancer staging and recurrence detection Integrating imaging with genomic data (radiogenomics) Optimizing therapeutic approaches using imaging biomarkers Recent work highlights: Prostate cancer radiogenomics and hypoxia biomarkers (2024) MRI/PET comparisons for tumor localization (2021-2023) Neoadjuvant therapy response assessment in rectal and breast cancers (2020-2023) Publications span over 50 peer-reviewed articles with a focus on translational imaging research. Collaborates extensively with oncology and urology teams.
Michael Krauthammer is a Professor of Medical Informatics and Chair of the Department of Quantitative Biomedicine at the University of Zurich, affiliated with the University Hospital of Zurich. His lab focuses on Clinical Data Science and Translational Bioinformatics, leveraging AI and machine learning to address healthcare challenges. Key areas include cancer genomics, federated learning, and automated medical imaging analysis. Education and affiliations: Krauthammer leads an interdisciplinary team supported by major funding agencies. His research spans bioinformatics, clinical decision support systems, and multimodal data integration. Notable projects include AI-assisted diagnosis in rheumatology and prime editing efficiency prediction. Recent work emphasizes longitudinal cfDNA analysis, drug interaction modeling, and personalized oncology. The lab collaborates across disciplines, with projects funded by Swiss and international grants. Students and postdocs work on topics like machine learning for radiology reports, longitudinal disease trajectories, and protein design. Key projects include the NTCIR-18 RadNLP challenge, prime editing prediction models (Nature Biotechnology 2024), and vision transformers for capillaroscopy analysis. The lab advocates for reproducible data science and ethical AI in healthcare.
Eduardo N. Chini, M.D., Ph.D., is a Professor at Mayo Clinic with primary and joint appointments in the Department of Anesthesiology and Perioperative Medicine and the Department of Cancer Biology. He is based in Rochester, Minnesota, and leads a research program focused on NAD metabolism, aging, and their roles in diseases such as cancer, obesity, and kidney disease. Education: BS in Biology, Centro Educacional de Niteroi-RJ MD, Universidade do Rio de Janeiro PhD in Biological Chemistry, Universidade do Rio de Janeiro Fellow, Department of Physiology and Biophysics, Mayo Clinic Resident in Anesthesiology, Mayo Clinic College of Medicine Research Interests: Eduardo N. Chini's research investigates the central role of nicotinamide adenine dinucleotide (NAD) in cellular metabolism, aging, and disease. His lab has made foundational discoveries in NAD catabolism, identifying CD38 as the primary enzyme regulating NAD levels in mammals. His work explores SIRT1 regulation via CD38 and DBC1, NAD metabolism in cancer, and its implications in polycystic kidney disease. He is particularly interested in how NAD signaling influences aging, metabolic syndrome, and organ dysfunction. Recent Research Trends: His recent publications (2023–2025) reveal a strong focus on the role of CD38 in aging, immune function, and tissue metabolism. Key themes include NAD+ depletion triggering inflammatory responses, CD38 inhibition as a therapeutic strategy for cardiotoxicity and metabolic aging, and the interplay between senescence, stem cell function, and mitochondrial health. His work increasingly integrates translational models with molecular mechanisms in aging and cancer. Scientific Awards: Florida Investigator of the Year, Mayo Clinic (2024) Glenn/AFAR Breakthroughs in Gerontology Award (2007) Edward C. Kendall Award, Mayo Clinic Alumni Association (2002) Directors Award for Aging Research, Kogod Center on Aging (2018) Distinguished Scientist Seminar Series, Georgetown Medical School (2022) Grants and Leadership: Dr. Chini is a co-Principal Investigator on multiple NIH-funded grants, including projects on CD38 in scleroderma, CLL, and male reproductive aging. He is Co-Director of the Mayo Clinic Mitochondrial Care Center and Associate Director of the Robert and Arlene Kogod Center on Aging. He has served on numerous national review panels and advisory councils, including the NIH Hepatobiliary Pathophysiology Study Section and AFAR's National Scientific Advisory Council. Labs and Teams: Dr. Chini leads a research laboratory at Mayo Clinic focused on NAD metabolism and aging. His team collaborates extensively with experts in cancer biology, mitochondrial medicine, and aging research. He is affiliated with the Mayo Clinic Comprehensive Cancer Center, the Kogod Center on Aging, and the Robert M. and Billie Kelley Pirnie Translational PKD Center.
Prof. Dr. Jörg Hackermüller is a computational biologist with expertise in Omics data integration Toxicology Environmental risk assessment Non-coding RNA biology . He serves as Head of the Department of Computational Biology and Chemistry at the Helmholtz Centre for Environmental Research (UFZ) since 2024 and holds a Professorship at the Faculty of Mathematics and Computer Science at Leipzig University since 2021. His research focuses on Developing AI methods for chemical toxicity prediction Multi-omics integration for mechanistic toxicology Data standardization in environmental monitoring Non-coding RNAs as biomarkers in disease and toxicity and has produced 15+ recent publications spanning tools like multiGSEA and deepFPlearn+ . He collaborates with teams across UFZ Leipzig University Novartis Fraunhofer Institute and leads projects like InCeTo and SafePol , integrating exposome research with systems biology.
Adrien Depeursinge is a Professor at HES-SO Valais-Wallis - Haute Ecole de Gestion, affiliated with the School of Economics and Services and the Management Information Systems department. His research focuses on radiomics, personalized medicine via image-based analysis, and clinical workflow optimization. He leads the development of the QuantImage platform, a physician-centered web-based tool for radiomics research, and contributes to radiomics standardization efforts through initiatives like the Image Biomarker Standardization Initiative (IBSI). His work emphasizes machine learning applications in healthcare, including tumor segmentation, biomarker extraction, and improving diagnostic accuracy through computational models. Key research themes include: 1) Radiomics – developing quantitative imaging features for cancer diagnosis/prognosis; 2) Medical Imaging Analysis – advancing texture-based models, multi-modal fusion, and automated lesion detection; 3) Physician-AI Collaboration – designing user-centric tools for clinical integration. His contributions span neuro-oncology (brain metastases), head-and-neck cancer, and multiple sclerosis imaging. Publications emphasize methodological advancements (e.g., kernel optimization in CNNs, steerable detectors) and clinical validation (e.g., reproducibility of radiomics features across imaging protocols). He collaborates with institutions like the University Hospital of Lausanne (CHUV) and international teams on projects like the HECKTOR challenge for PET/CT tumor segmentation. His work bridges technical innovation with clinical impact, aiming to translate radiomics into actionable clinical tools. QuantImage v2, his flagship tool, enables no-code development of machine learning models using clinical imaging data. Research also includes phantom-based validation of radiomics features and addressing challenges in feature stability across imaging modalities. Current projects explore improving contour quality for radiomics studies and optimizing AI explainability in medical decision-making.
Dr. Deborah Goberdhan is an Associate Professor at the University of Oxford , affiliated with the Department of Physiology, Anatomy and Genetics (DPAG) . She leads an independent research group investigating amino acid sensing , mTORC1 signaling , and exosome-mediated communication in cancer progression using both human cancer cells and Drosophila models . She serves on the Cancer Research UK Oxford Centre Research Committee , teaches Medical and Biomedical Sciences undergraduates , and acts as Academic Public Engagement Lead for her department. Her research focuses on cell growth regulation through Proton-assisted Amino acid Transporters (PATs) , which function as 'transceptors' modulating mTORC1 activity . This work has expanded to examine exosome heterogeneity and therapeutic delivery mechanisms with support from BBSRC and Cancer Research UK . She co-founded Oxosome , the Oxford extracellular vesicle interest group , to foster interdisciplinary collaboration. Key research areas include Cancer cell communication via exosomes Amino acid signaling in tumor progression Drosophila as cancer model system Clinical collaborations with Prof Adrian L Harris , Prof Freddie C Hamdy , and Prof Clare Verrill Recent publications highlight her group's contributions to exosome biogenesis (2023), brain-targeted siRNA delivery (2021), and nutrient stress responses in cancer (2020). She actively promotes scientific communication through ISEV social media initiatives.
Michael DiGiovanna is a Professor of Internal Medicine and Pharmacology at Yale School of Medicine, specializing in Medical Oncology with a focus on breast cancer. He holds clinical leadership roles including Chair of the Breast Cancer Tumor Board and educational leadership as Co-Director of the Pre-Clerkship Curriculum and Thread Leader in Pharmacology. MD and PhD from Yale University (1990) Residency and Fellowship at Yale School of Medicine Board Certified in Medical Oncology (ABIM) His research investigates signal transduction mechanisms in breast cancer, particularly HER2/EGFR/ER/IGF-I receptor interactions and their implications for targeted therapies. Clinical work spans pharmacology, oncology, and translational research with frequent co-authorship alongside Lajos Pusztai and Donald Lannin. Scientific Awards: American Cancer Society Research Scholar Grant Women's Health Investigator Award Swebilius Translational Cancer Research Award Alvan R. Feinstein Award Contact: Email: michael.digiovanna@yale.edu Office: 203.785.2876 Clinical: 203.200.2328
Professor Jonna Kuntsi is a leading researcher in developmental disorders and neuropsychiatry at King's College London's Institute of Psychiatry, Psychology & Neuroscience, where she holds a professorship in the Social, Genetic & Developmental Psychiatry Centre. With extensive training including BSc, MSc, and PhD from University College London and clinical experience at Great Ormond Street Hospital for Children, she has established herself as a prominent figure in ADHD research globally. Her research primarily focuses on attention deficit hyperactivity disorder (ADHD) and related conditions, with particular expertise in neurodevelopmental disorders, remote measurement technology applications, developmental trajectories, preterm birth associations, and the effects of physical activity on cognition and ADHD symptoms. Professor Kuntsi has pioneered the ADHD Remote Technology (ART) research programme, securing substantial funding including £4 million from the UK Medical Research Council and European Commission for innovative projects like ART-transition and ART-CARMA. Her publication record demonstrates consistent high-impact research across multiple domains of ADHD investigation, with recent work emphasizing digital phenotyping, remote monitoring technologies, and the developmental aspects of ADHD across the lifespan. This research portfolio shows a clear trajectory toward increasingly sophisticated technological approaches to understanding and managing ADHD. Co-Chair of EUNETHYDIS - the European Network for ADHD Member of the European ADHD Guideline Group (EAGG) Principal Investigator in International Multi-centre Persistent ADHD Collaboration (IMpACT) Steering committee member of ECNP ADHD across the Lifespan Network Steering committee member of ECNP Digital Health Applied to Clinical Research Network Professor Kuntsi actively collaborates with patient support organizations including ADHD Europe and the UK ADHD Information and Support Service (ADDISS), and with technology companies like Empatica and The Hyve. She serves as Chair of the PhD Subcommittee across Departments of Social, Genetic & Developmental Psychiatry and Biostatistics & Health Informatics, demonstrating her commitment to mentoring the next generation of researchers while leading multiple international research networks that advance both scientific understanding and clinical practice in ADHD.
Fabian Spill is a Professor of Applied Mathematics, specializing in interdisciplinary research that bridges mathematical modeling with biomedical applications. His work spans cancer biology, metabolic pathways, and data-driven optimization for sustainable systems. Research Focus: Mathematical modeling of cancer spheroids, immune-inflammatory dynamics, and epigenetic age regression. Collaborations: Engages in cross-disciplinary projects with institutions like the Medical Research Council and Innovate UK. Projects: Leads initiatives in systems-mechanobiology, stem cell behavior prediction, and energy-efficient building design. Recent publications highlight his contributions to hybrid computational models for collagen stiffening in tumors, lactate signaling in inflammation, and interpretable machine learning frameworks for age estimation. His research aligns with UN Sustainable Development Goals, particularly those addressing health and sustainable cities.
Paavo Alku is a Professor of Speech Communication Technology at Aalto University's Department of Information and Communications Engineering. With academic credentials from Helsinki University of Technology (M.Sc. 1986, Lic.Tech. 1988, Dr.Sc.Tech. 1992), he has held academic positions at Asian Institute of Technology (1993) and University of Turku (1994-1999). Current research focuses on speech production analysis, parametric speech synthesis, and speech-based biomarkers for health monitoring Actively develops machine learning models for voice disorder detection and Parkinson's disease classification Principal investigator for projects including SymptoSonic (2024-2025) and HEART (2020-2024) His recent publications emphasize: Wavelet scattering for neurological speech analysis Fisher vector representations in voice disorder classification Machine learning approaches to vocal intensity categorization Respiratory aerosol emission during speech production Formant tracking through hybrid neural network/LP methods Awarded: IEEE Fellow (2020) Academy Professor (2015-2019) Multiple best student paper awards at ICASSP and Interspeech
Koushik Maharatna is a Professor in the Digital Health and Biomedical Engineering department at the University of Southampton. His research spans biomedical signal processing, digital health, and embedded systems, with a focus on neurological and cardiovascular disorders. Active in EU Horizon Europe and FP7 projects Member of the Institute for Life Sciences and Centre for Internet of Things and Pervasive Systems Specializes in EEG analysis, arrhythmia detection, and autism spectrum disorder diagnostics His recent publications highlight applications of phase-space reconstruction, machine learning, and wavelet transforms in medical diagnostics. Collaborations include researchers across Europe and Malaysia, with emphasis on interdisciplinary digital health solutions. Current research projects funded by UKRI, EPSRC, and European Union grants include PUREMIND and ETHEREAL, focusing on mental health prevention and energy-harvesting electronics. He supervises PhD students in Human Development & Health and Electronics & Electrical Engineering.
Dr Bastien Lechat is a Research Fellow at Flinders Health and Medical Research Institute (FHMRI): Sleep Health, within the College of Medicine and Public Health at Flinders University. He is also a Full Member of the College of Science and Engineering and the Medical Device Research Institute. As an NHMRC Emerging Leadership Fellow, he leads innovative research at the intersection of sleep medicine, artificial intelligence, and wearable technology. Education: PhD in Sleep Health, Adelaide Institute for Sleep Health, Flinders University (2018–2021) Bachelor of Engineering in Engineering Science/Acoustics, Université du Maine, France (2014–2017) Dr Lechat’s research focuses on understanding the physiological mechanisms and consequences of obstructive sleep apnea (OSA), particularly night-to-night variability and patient subtypes. He develops AI-driven tools for efficient and accurate diagnosis using wearables and signal processing. His work aims to create a scalable, low-cost model of care for sleep-disordered breathing, addressing global diagnostic gaps. His recent publications reveal a strong trend in digital health innovation, with a focus on machine learning for OSA detection, circadian rhythm modeling, cardiovascular risk prediction, and climate impacts on sleep. His research has been published in top journals including Nature Communications , Journal of Sleep Research , and Sleep Medicine , demonstrating interdisciplinary reach. Scientific Awards and Recognition: NHMRC Emerging Leadership Fellow (2023) Helen Bearpark Memorial Scholarship (2022) Emerging Research Leader Award, Flinders University (2021) Multiple early-career awards from Sleep Down Under, Australasian Sleep Association, and Adelaide Sleep Retreat Ranked in the top 5% of international authors in sleep apnea by Expertscape Dr Lechat has secured over $2.5 million in competitive research funding and actively supervises and mentors junior researchers. He serves on the program committee of the American Thoracic Society meetings and contributes to clinical guidelines. He collaborates globally with industry and academic partners to translate research into clinical practice. Laboratories and Research Teams: He co-leads the 'Novel use of digital innovations & technology development' theme at FHMRI: Sleep Health, working closely with Professor Danny Eckert. His team integrates expertise in biomedical engineering, data science, and clinical sleep physiology to advance digital sleep medicine.
Mei Hong is the David A. Leighty Professor of Chemistry at the Massachusetts Institute of Technology (MIT), where she leads the Hong group. Her research focuses on developing and applying high-resolution solid-state NMR spectroscopy to study the structure and dynamics of biological macromolecules, particularly membrane proteins, amyloid proteins, and plant cell walls. Her work integrates advanced NMR techniques with biophysical and biochemical studies to elucidate mechanisms underlying ion transport, protein misfolding in neurodegenerative diseases, and plant cell wall architecture. Her research interests span viral ion channels (e.g., influenza M2, SARS-CoV-2 E protein), amyloid proteins (e.g., tau in Alzheimer’s disease), and plant cell wall polysaccharides. She pioneered techniques like 19F-based NMR distance measurements and multidimensional correlation NMR to study structural and dynamic heterogeneity in biomolecules. Her lab’s contributions include defining the structure of the SARS-CoV-2 envelope protein, elucidating tau fibril conformations, and revealing the single-network model of plant primary cell walls. Collaborations with medicinal chemists, electrophysiologists, and molecular dynamics experts enhance her interdisciplinary approach.
