Geir Selbæk is a Professor II at the University of Oslo in the Department of Geriatric Medicine . His research focuses on dementia , neurodegenerative diseases , and aging-related mental health , with extensive work on the HUNT study —a large Norwegian population-based cohort. He investigates risk factors like depression , loneliness , metabolic health , and social determinants to understand dementia progression. Key research areas: Dementia epidemiology, geriatric mental health, neurodegenerative disease, aging, cognitive impairment Recent publications analyze AI in diagnostics, genetic risk scores, social media's role in pandemic isolation, and metabolic markers Collaborations Selbæk collaborates with international teams across Alzheimer's & Dementia , Nature Genetics , PLOS ONE , and other high-impact journals. His work integrates epidemiological data , neuropsychological testing , and molecular biology to address dementia prevention and care.
Professor Stuart L. Graham is a Professor of Ophthalmology at Macquarie Medical School and Head of Ophthalmology and Visual Science at Macquarie University Faculty of Medicine. He also serves as a Visiting Professor at the Save Sight Institute, University of Sydney. With expertise in glaucoma subspecialty and electrophysiology, his research focuses on optic nerve damage mechanisms, vascular and molecular factors, neurodegenerative pathways, and neuroprotective therapies for glaucoma and multiple sclerosis. He holds a MBBS, MS, PhD, and FRANZCO. His research projects include studies on retinoid agonists for glaucoma, early diagnosis of Alzheimer's via retinal screening, and retinal vascular changes in sleep apnea. He has received prestigious awards such as the FARVO (2023), Gillies Medal (2017), and RANZCO Distinguished Service Award (2015). With 384 research outputs and 64 active projects, his work spans clinical trials, drug development, and collaborative studies. His team explores novel therapies and imaging techniques to address vision loss and neurodegenerative diseases.
Kushal Dey serves as an Assistant Professor in the Computational and Systems Biology Program at Memorial Sloan Kettering Cancer Center (MSKCC), part of the Graduate School of Medical Sciences in partnership with Weill Cornell Medicine. His research integrates statistical and machine learning approaches with genomic data to understand the regulatory architecture of complex diseases. Dr. Dey's research focuses on developing computational methods that integrate human disease genetics with functional genomics data. His work spans immune-related diseases including Alzheimer's and inflammatory bowel disease, as well as heritable cancers like breast and prostate cancer. His lab develops models to prioritize variants, genes, and cell states for disease using genetic, genomic, and perturbation data, with emphasis on causal directed graphs and benchmarking pipelines informed by disease genetics. His recent publications highlight expertise in GWAS, colocalization, spatial transcriptomics, Perturb-seq, and RNA+ATAC multiome analysis. His work frequently appears in top journals like Nature Genetics, with a focus on single-cell multi-omics approaches to understand disease mechanisms at cellular resolution. Scientific Awards: Josie Robertson Investigator (2023–2028) K99/R00 Pathway to Independence Award (NIH/NHGRI) (2022–2026) NIH/NHGRI Early Stage Investigator R01 (2025-2030) NCI P30 CCSG supplement – 'LLMs in cancer research' (2023-2024) Catalog Working Group Co-chair + Disease Focus Group Lead: IGVF consortium (2023-) Dr. Dey mentors several graduate students through the Weill Cornell Graduate School (WGS), including Thahmina Ali, Pretty Garcia, Karthik Guruvayurappan, Louis Liu, Sarthak Tiwari, Berk Turhan, and Harry Zhang. His lab has received multiple grants including the AWS IMAGINE Grant Children's Health Innovation Award 2024-2025 (as Project Co-lead) and PSRP Developmental Funds Awards (2025: Co-lead). The lab actively collaborates with consortia including ENCODE, ADSP, MorPhiC, and IGVF, maintaining strong ties with Columbia University, Stanford University, and Harvard T.H.Chan School of Public Health. The Kushal Dey Lab is part of the vibrant Tri-Institutional Research campus adjacent to Rockefeller University and Weill Cornell Medical College, offering a collaborative environment focused on computational genomics and disease mechanisms.
Samuli Ripatti is a Professor of Biometry at the Faculty of Medicine, University of Helsinki, and Director of the Institute for Molecular Medicine Finland (FIMM). He chairs the Research Council Finland’s Centre of Excellence in Complex Disease Genetics and the EU H2020-funded Intervene Consortium. His research focuses on genetic variation in the Finnish population, particularly its effects on cardiometabolic diseases and cancers, with a strong emphasis on polygenic risk scores for disease prevention and early detection. His work spans Genetic risk prediction models Lipidomic and metabolomic profiling Gene-environment interactions Translational genomics Recent research highlights include 1099 plasma metabolite-disease causal analysis Genetic determinants of weight loss interventions Cardiovascular risk stratification tools Leukocyte lipid metabolism pathways He actively supervises doctoral programs in Integrative Life Science, Social Sciences, Clinical Research, and Population Health, and collaborates with the Broad Institute of MIT and Harvard.
Marylyn D Ritchie, PhD, is the Edward Rose, M.D. and Elizabeth Kirk Rose, M.D. Professor at the Perelman School of Medicine, University of Pennsylvania. She concurrently serves as Director of the Institute for Biomedical Informatics, Vice President for Research Informatics for the University of Pennsylvania Health System, Director of the Division of Informatics in the Department of Biostatistics, Epidemiology, and Informatics, and Vice Dean of Artificial Intelligence and Computing. Education: BS in Biology, University of Pittsburgh at Johnstown, 1999 MS in Applied Statistics, Vanderbilt University, 2002 PhD in Statistical Genetics, Vanderbilt University, 2004 Research Interests Dr Ritchie’s work integrates computational genomics , bioinformatics , pharmacogenomics , and systems genomics to advance precision medicine. She develops statistical and machine-learning approaches to dissect epistasis , genetic epidemiology , and evolutionary computation in large-scale biobanks, with a special focus on cardiovascular disease and Alzheimer’s disease . Her group is also pioneering translational informatics methods that incorporate social determinants of health and fairness metrics into AI-driven clinical decision support. Publication Trends In 2025 alone, Dr Ritchie co-authored more than fifteen high-impact studies spanning vision-language models for 3D CT , multi-omics Alzheimer’s risk prediction , fairness in neuroimaging AI , ancestry-specific pharmacogenomics , and cloud-based polygenic risk score platforms . The collective work highlights a shift from single-omics discovery to integrative, equitable, and clinically actionable models across diverse ancestries. Awards & Honors While specific named awards were not detailed in the text, Dr Ritchie’s endowed professorship and multi-institutional leadership roles signify sustained recognition. Grants & Advising Dr Ritchie leads large NIH, foundation, and industry-funded initiatives that support interdisciplinary teams of postdocs, graduate students, and data scientists. Her lab actively mentors trainees from UPenn’s Cell and Molecular Biology and Genomics and Computational Biology graduate groups. Laboratories & Teams She directs the Ritchie Lab (ritchielab.org), which develops open-source visualization tools such as PhenoGram , PheWAS-View , and Synthesis-View for genome-wide and phenome-wide data exploration. The lab operates within the Institute for Biomedical Informatics and collaborates closely with the Penn Medicine BioBank and multiple clinical departments to translate big-data discoveries into precision medicine workflows.
Ardo van den Hout is a Professor of Statistics at the Department of Statistical Science, University College London. He holds a PhD in Social Statistics from Utrecht University (2004) and has previously worked at the MRC Biostatistics Unit in Cambridge. His research focuses on advanced statistical methodologies including longitudinal data analysis, survival analysis, multi-state models, and applications in aging research and public health. He has authored influential works such as Multi-state Survival Models for Interval-censored Data (2017). Research Interests Development and application of multi-state models for complex health data Survival analysis techniques for interval-censored and longitudinal datasets Methodological advancements in cognitive decline and disease progression modeling Integration of socio-economic factors in health expectancy analysis Key Contributions Pioneered penalized likelihood approaches for multi-state models Developed frameworks for estimating life expectancies in health and disease Advanced methods for handling missing/misclassified data in longitudinal studies Awards Recipient of the Gopal Kanji Prize 2012 for outstanding contributions to statistics Professional Activities Maintains an active research program with collaborations across biostatistics, epidemiology, and health economics. Supervises doctoral students focusing on statistical methodologies with real-world health applications. His work frequently addresses critical questions in aging populations, cancer research, and public health policy.
Ismene Petrakis is a Professor of Psychiatry at Yale School of Medicine and Director of the Mental Health Service Line at VA Connecticut Healthcare System since 2010. She also leads the ACGME-accredited Addiction Psychiatry Residency program at Yale and serves as Principal Investigator for NIAAA- and NIDA-funded training grants . Her clinical and research focus bridges alcohol dependence , comorbid psychiatric disorders , and veterans' health . Research Pillars : Pharmacotherapies for dually diagnosed patients Neurobiological mechanisms of alcoholism PTSD-alcohol comorbidity Genetic risk in substance use Methodological Expertise : Multicenter clinical trials Neurotransmitter system analysis Population-based epidemiology Translational neuroscience Key Publications (2024-2025) : Investigations into GLP1R gene expression in kidney disease Dexmedetomidine for comorbid alcohol-PTSD Cognitive training combinations for alcohol use disorder PTSD treatment effects on neurobiological markers Chronic pain-alcohol use syndemic Collaborative Networks : Yale-Drug use, Addiction, and HIV prevention Research Scholars Neuroscience Research Training Program Collaboration with Department of Anesthesiology
Dr. Megan Skelton is a Research Fellow at King’s College London’s Social, Genetic and Developmental Psychiatry Centre (SGDP), affiliated with the Institute of Psychiatry, Psychology and Neuroscience. She holds a PhD in Psychology from King’s College London, funded by the NIHR Maudsley Biomedical Research Centre. Her research focuses on leveraging genetic data and longitudinal medical records to study anxiety, depression, and treatment responses, particularly via genome-wide association studies (GWAS), polygenic scoring, and structural equation modeling. Current projects in Prof. Thalia Eley’s EDIT Lab involve prediction modeling, GWAS meta-analyses, and medical record linkage. Education: BSc Psychology (First Class, University of Leeds), MSc Genes, Environment and Development in Psychology (Distinction, King’s College London). Research experience includes roles at the University of Leeds (2011–2017) and King’s College London (2017–present). Awards include the British Psychological Society Undergraduate Award (2014) and Wellcome Trust Biomedical Vacation Scholarship (2013). Key research themes include anxiety/depression comorbidity, treatment efficacy measurement, and understanding genetic influences on mental health outcomes. Her work contributes to UN Sustainable Development Goal 3 (Good Health & Wellbeing) through advancements in personalized mental health care.
Tania Fernández Villa is an Associate Professor in the Department of Biomedical Sciences at the Faculty of Veterinary Medicine, University of León. Her primary academic affiliation centers on preventive medicine and public health research within the GIIGAS (Interactions Gene-Environment-Health) research group. Her research spans nutritional epidemiology, gender studies in food systems, substance use disorders, and chronic disease prevention. Key focus areas include alcohol consumption patterns among university students (via the UniHcos cohort), sarcopenia in metabolic syndrome, breast cancer risk factors, and pandemic impacts on health behaviors. Her work integrates longitudinal cohort analysis, systematic reviews, and psychometric validation studies. Recent publications demonstrate strong trends in gender-disaggregated health research, pandemic-related behavioral shifts, and methodological innovations in dietary assessment. Her 2024-2025 output shows increasing emphasis on environmental sustainability of diets and multi-cancer risk prediction models. She serves on the editorial board of the Spanish Journal of Human Nutrition and Dietetics, contributing to strategic planning (2020-2026) and open science initiatives. Her PhD from Universidad de Granada focused on ICT usage patterns among university students. Current projects include the UniHcos longitudinal study tracking health behaviors in Spanish university students, with particular attention to alcohol use, sleep patterns, and nutritional status. Her research group actively investigates gene-environment interactions in public health contexts.
Pekka Martikainen is a leading researcher in population health and demography, affiliated with the Population Research Unit at the Faculty of Social Sciences, University of Helsinki . He is also actively involved with the MaxHel Center and the Laboratory of Population Health , contributing to major research initiatives such as the Monitoring Mortality Inequalities Consortium and studies on immigrant-native health disparities. His research focuses on social and economic determinants of health and mortality over the life course, using extensive Finnish register data. Key interests include fertility and family dynamics , health inequalities , migration and health , early-life determinants of health, and behavioral factors influencing mortality. His work often explores intergenerational linkages and the role of socioeconomic status in shaping health outcomes. The most recent publications reflect a strong emphasis on mental health , genetic and social interactions , educational and occupational influences on health , and disparities in cancer and reproductive health . Studies frequently employ longitudinal, register-based designs across Nordic and European populations, highlighting cross-national comparative insights. Behavioral Determinants of Health and Mortality Costs and Gains of Postponing Parenthood Immigrant-Native Health Disparities Over the Life Course Linked Lives: Family and Socioeconomic Attainment Medically Assisted Reproduction Mortality Disparities at Subnational Level His research has been published in top journals including The Lancet , Demography , Social Science and Medicine , and European Journal of Epidemiology . He collaborates extensively with researchers at the Max Planck Institute for Demographic Research and leads or contributes to multiple large-scale projects analyzing health and demographic trends in Finland and beyond. Martikainen’s work informs public health policy and contributes to understanding how social structures and individual behaviors interact to shape population health and longevity. He plays a central role in advancing register-based demographic research in Europe.
Donghao Lu is a Professor at Karolinska Institutet's Institute of Environmental Medicine, where he leads the Epidemiology of Women's Mental Health Lab. His research program focuses on psychiatric epidemiology with specialization in women's reproductive mental health, using large-scale population cohorts to investigate biological mechanisms and health outcomes. Primary research domains include: Risk factors and health consequences of perinatal depression and premenstrual disorders Bidirectional relationships between autoimmune diseases and mood disorders Gender disparities in mental health presentation and outcomes Cardiometabolic comorbidities in reproductive psychiatric conditions His recent publications (2023-2025) demonstrate strong methodological consistency, predominantly using Scandinavian national registries for longitudinal cohort designs. Research themes show progression toward understanding systemic health impacts of reproductive mood disorders, particularly cardiovascular risks and mortality. Over 90% of recent work incorporates population-level data analysis with sample sizes exceeding 10,000 participants. Laboratory focus includes integrating epidemiological methods with biomarker research to bridge obstetrics/gynecology and psychiatry. Current projects investigate inflammatory pathways in perinatal depression and genetic determinants of premenstrual disorder trajectories. The team maintains international collaborations across Scandinavia, China, and North America.
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.
George Hripcsak is the Vivian Beaumont Allen Professor of Biomedical Informatics and Director of Medical Informatics Services at New York-Presbyterian Hospital, Columbia University. He holds affiliations with the Vagelos College of Physicians and Surgeons and the Data Science Institute (DSI). His expertise spans clinical informatics, electronic health records (EHRs), and medical knowledge representation standards. Hripcsak earned degrees in chemistry, medicine, and biostatistics, and is a board-certified internist. Research focuses on leveraging EHR data for clinical research and patient safety through data mining and causal inference techniques. Notable contributions include the Arden Syntax (a national standard for medical knowledge representation) and leadership in the Observational Health Data Sciences and Informatics (OHDSI) network. He chairs the AMIA Standards Committee and has advised federal health informatics policies under HIPAA. His academic awards include Fellowships in the American College of Medical Informatics (1995) and New York Academy of Medicine. Current projects emphasize federated learning, genomic risk prediction, and large-scale real-world evidence analysis through initiatives like LEGEND-T2DM and All of Us Research Program. Educations: MD, Biostatistics, Chemistry Labs/Teams: OHDSI, DSI, Medical Informatics Services Grants & Funding: Not explicitly listed in provided texts
Bao-Zhu Yang is a Researcher at Yale School of Medicine , specializing in the Department of Psychiatry . With a PhD from University at Albany (2001), his work focuses on genetic mechanisms underlying psychiatric disorders. Positions: Research Scientist in Psychiatry Labs: Gelernter Lab, Division of Human Genetics His research explores gene-environment interactions , admixture mapping , and comorbid substance use-depression using linkage/association methods. Supported by NIH K01 funding, he investigates genetic bases for conditions including childhood depression , alcoholism , and PTSD . Recent publications highlight: Microbiome studies in methamphetamine use disorder (2023-2025) Genetic polymorphism analyses in NGF and GABAergic pathways (2020-2024) Network approaches to nicotine-alcohol comorbidity (2019) Epigenetic research on child maltreatment effects (2020) Scientific Recognition: Young Investigator Award (2011) from NARSAD Brain and Behavior Research Foundation Active grant support includes NIH K01 career development award for gene-mapping in comorbid disorders. Collaborates with leading researchers including Joel Gelernter and Hongyu Zhao across 30+ joint publications. His work spans 15+ years with recent focus on integrative -omics approaches to addiction psychiatry. Based at 300 George St, New Haven, CT , Yang's laboratory work involves genetic epidemiology , transcriptomic integration , and neurogenetic mapping of substance use disorders.
Lucila Ohno-Machado, MD, PhD, MBA, is the Waldemar von Zedtwitz Professor of Medicine and Biomedical Informatics and Data Science at Yale University. She serves as Deputy Dean for Biomedical Informatics and Chair of the Department of Biomedical Informatics and Data Science at the Yale School of Medicine. Her leadership roles include overseeing informatics infrastructure for Yale’s academic health system and fostering interdisciplinary collaboration across departments such as Medicine and the Halicioğlu Data Science Institute (previously at UCSD). Ohno-Machado holds an MD from the University of São Paulo (Brazil), an MBA from Fundação Getúlio Vargas (Brazil), and a PhD in Medical Information Sciences and Computer Science from Stanford University. She has held faculty positions at Harvard Medical School, MIT’s Health Sciences and Technology Division, and the UCSD Health Department of Biomedical Informatics, where she pioneered federated learning and privacy-preserving AI methodologies. Her research focuses on predictive analytics, federated learning, quantum computing in healthcare, and blockchain applications to enhance data security. She emphasizes addressing algorithmic bias and promoting health equity through data-driven solutions. Recent work includes developing frameworks for medical device safety evaluation and guiding principles to mitigate disparities in algorithmic healthcare applications. Key achievements include the Inaugural Helen M. Ranney Award (2024), election to the National Academy of Medicine (2024), and the William W. Stead Award (2019). She has led NIH-funded informatics centers and contributed to the first large-scale clinical data-sharing initiative across five UC medical systems. Her grants span AHRQ, PCORI, NSF, and blockchain-related initiatives through the IT/NIST Challenge Award. Ohno-Machado advises on translational research strategies and mentors teams in YBIC (Yale Biomedical Informatics & Computing). Her lab collaborates globally, leveraging federated models and AI to advance personalized medicine while prioritizing patient privacy. She also chairs the OHER Awards for Yale Research Excellence, promoting interdisciplinary health equity research.
