Dr. Gayathri Pandey is an Assistant Professor in the Department of Psychiatry & Behavioral Sciences at SUNY Downstate Health Sciences University. She specializes in social neuroscience, focusing on the interplay between social relationships, brain function, and mental health across the lifespan, with a particular emphasis on alcohol use disorders and resilience mechanisms. NIH-sponsored TRANSPORT fellowship recipient First PRODiG faculty in Psychiatry & Behavioral Sciences K01 award from NIA/NIAAA Co-investigator on multiple R01 and U01 grants Her research integrates biopsychosocial approaches to examine familial risk factors, neurocognitive biomarkers, and social-environmental influences on mental health. She has received recognition for her work on parent-child bonding's protective role in neurocognitive health among high-risk offspring, featured in Psychology Today , Neuroscience News , and the Thriving Minds podcast. Dr. Pandey's interdisciplinary training spans clinical psychology, neuroscience & education, and social & personality psychology. She employs advanced neuroimaging techniques, polygenic risk scores, and machine learning to analyze developmental trajectories of resilience and risk in substance use disorders. Principal Investigator for K01-AA030610 (2024-2029): Interplay of parenting, genetics, and brain function in alcohol use disorder Co-Investigator for COGA (Collaborative Study on the Genetics of Alcoholism) and other NIH-funded projects
Ariful Azad serves as an Associate Professor in the Department of Computer Science & Engineering at Texas A&M University, where he leads research at the intersection of high-performance computing and graph analytics. His work focuses on developing scalable algorithms for graph machine learning with applications in bioinformatics and security informatics. Educational Background: Ph.D. in Computer Science, Purdue University (2014) B.S. in Computer Science and Engineering, Bangladesh University of Engineering and Technology (2006) Research Focus: Dr. Azad specializes in high-performance graph algorithms , particularly for distributed-memory systems. His pioneering work includes the Combinatorial BLAS library and novel approaches for graph neural networks (GNNs), with emphasis on explainability through Shapley values and optimization of sparse matrix operations. His bioinformatics research tackles large-scale metagenomics challenges through projects like Exabiome. Publication Trends: Recent publications (2023-2025) reveal three dominant themes: (1) Scalable GNN explanation frameworks using distributed Shapley values, (2) High-performance sparse linear algebra for graph embeddings and knowledge graphs, and (3) Bioinformatics applications in metagenomics and network alignment. His work consistently bridges theoretical algorithm development with practical implementations for exascale systems. Scientific Recognition: NSF CAREER Award (2024) for foundational contributions to scalable graph algorithms Indiana University Trustee's Teaching Award (2024) U.S. Department of Energy Early Career Award (2021) Research Leadership: As principal investigator for multiple federal grants, Dr. Azad directs projects advancing graph analytics at extreme scales. His work on Weapons of Mass Destruction knowledge graphs demonstrates applied security research, while Exabiome represents significant contributions to computational biology. He actively develops open-source tools like PLANETALIGN for network analysis benchmarking, fostering reproducibility in computational science.
Robert Plomin is MRC Research Professor in Behavioural Genetics at the Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London. He helped launch the Social, Genetic and Developmental Psychiatry Research Centre in 1994 and established the Twins Early Development Study (TEDS) in 1995, which has followed 10,000 pairs of UK twins for over 25 years. With more than 800 publications and numerous books including "Blueprint: How DNA Makes Us Who We Are," he is a leading figure in behavioral genetics. Professor Plomin earned his PhD from the University of Texas at Austin and his BA from DePaul University. His academic journey includes positions at the University of Colorado and Pennsylvania State University before joining King's College London. Plomin's research focuses on using quantitative genetic and genomic approaches to understand how genetic and environmental factors shape behavioral development. His work particularly examines cognitive development and educational achievement, investigating how DNA influences individual differences in learning abilities and disabilities. Through large-scale twin studies like TEDS, he has made significant contributions to understanding the heritability of psychological traits and the role of nonshared environmental influences. His recent publications reveal a strong emphasis on genome-wide association studies, examining connections between genetics and various psychological outcomes including mental health, educational achievement, language development, and psychopathology. His work increasingly integrates molecular genetic techniques with traditional behavioral genetics approaches, demonstrating how DNA can predict behavioral outcomes from childhood through adulthood. Professor Plomin has received numerous prestigious honors including: Lifetime Achievement Award from the British Psychological Society (2020) Youngest President of the international Behavior Genetics Association Lifetime research achievement awards from multiple major associations in his field Fellowship in the American Academy of Arts and Sciences Fellowship in the British Academy Fellowship in the American Academy of Political and Social Science Fellowship in the Academy of Medical Sciences (UK) As principal investigator of the Twins Early Development Study (TEDS), Plomin has secured continuous funding for 25 years through Medical Research Council programme grants. TEDS has grown from studying infant twins to following participants into early adulthood, providing unprecedented longitudinal data on genetic and environmental influences. He has mentored numerous researchers through this project and has collaborated extensively with institutions worldwide, significantly advancing the field of behavioral genetics. The Social, Genetic and Developmental Psychiatry Centre at King's College London, where Plomin is based, serves as a hub for integrating genetic and environmental research approaches. TEDS remains his flagship project, but his influence extends through collaborations on international consortia studying everything from dyslexia to mental health outcomes. His current work focuses on applying polygenic scoring methods to predict behavioral outcomes and understanding the mechanisms through which genes influence development.
Jonas L. Juul is an Assistant Professor in the Computer Science Department at the IT University of Copenhagen . With a background in network science and complex systems, he employs statistical methods, mathematical modeling, and computer simulations to study social networks, spreading processes, and human behavior. Focus areas include: information diffusion in social networks Disease spread mitigation in human populations Interdisciplinary collaboration with medical doctors, economists, and computer scientists Recent research highlights include improving statistical models for pandemic forecasting through the InForM project funded by the Novo Nordisk Foundation , and groundbreaking work on contact tracing optimization and information cascade dynamics. Notable recognitions: 2025 H.C. Ørsted Research Talent Prize 2024 Novo Nordisk Foundation Data Science Emerging Investigator Grant 2025 Young Academy membership He has contributed to mathematical modeling efforts during Denmark's COVID-19 reopening in 2020 and maintains active collaborations with institutions including Cornell University , Technical University of Denmark , and Niels Bohr Institute .
Professor Thalia Eley is Professor of Developmental Behavioural Genetics at King's College London's Institute of Psychiatry, Psychology & Neuroscience. She serves as Head of the Social, Genetic & Developmental Psychiatry Centre and leads the Emotional Development, Intervention and Treatment (EDIT) Lab. Professor Eley is also Director of the Twins Early Development Study (TEDS), the largest longitudinal twin birth cohort in the UK, and co-leads the Genetic Links to Anxiety and Depression (GLAD) Study. Professor Eley's educational background includes: Bachelor of Arts in Social and Political Sciences with a focus on psychology from Trinity College Cambridge PhD in the role of genetic and environmental influences on depression and anxiety in young people from the Institute of Child Health, University College London Professor Eley's research focuses on understanding the interplay between genetic and environmental factors in the development and treatment of anxiety and depression, particularly in youth. She is transforming efforts toward personalized medicine through 'therapygenetics,' studying genetic effects on psychological treatment response. Her work creatively combines longitudinal, genetic, experimental, and clinical approaches to explore mechanisms underlying mental health disorders. A key aspect of her research examines why anxiety and depression tend to run in families and whether this is due to shared environments or genetic factors. Professor Eley's recent publications demonstrate a strong focus on integrating genetic approaches with clinical psychology to understand mental health conditions. Her work spans anxiety disorders, depression, eating disorders, and neurodevelopmental conditions, with particular emphasis on how genetic factors influence treatment response. She has been instrumental in large-scale studies like the GLAD Study, which is the largest single study of anxiety and depression ever undertaken, and TEDS, which has followed twins from birth into early adulthood. Professor Eley has received numerous prestigious awards for her contributions to the field: Fellow of the British Academy (2025) Fellow of the Academy of Medical Sciences (2021) James Shields Lifetime Achievement Award from the International Society for Twin Studies (2017) King's Graduate School IoPPN Supervisory Excellence Award (2017) King's University Research Project of the year for the GLAD Study (2019) Lilly-Molecular Psychiatry Award (2004) Spearman Medal from the British Psychological Society (2002) Professor Eley is passionate about mentoring early career researchers and has chaired the Research and Innovation Committee for over five years, developing initiatives to support this group. Her research has been supported by substantial grants including MRC funding for TEDS, Wellcome Trust funding for anxiety treatment prediction research, and MRC/ESRC funding for the UK Longitudinal Linkage Collaboration. She actively promotes diversity in scientific research both in terms of researchers and study participants. Professor Eley leads the Emotional Development, Intervention and Treatment (EDIT) Lab, which consists of postdoctoral researchers, PhD students, and undergraduate and master's students. The lab is based at the Social, Genetic & Developmental Psychiatry Centre at King's College London. She also co-leads the GLAD Study, which recruits participants through media and social media, and has developed digital tools like the FLARe (Fear Learning and Anxiety Response) app for remote fear conditioning experiments.
Dr. Eran Halperin is a Professor at the University of California, Los Angeles, affiliated with the School of Engineering (Computer Science Department) and the School of Medicine (Human Genetics, Computational Medicine, Anesthesiology). His research bridges computational biology, genomics, and machine learning, with a focus on developing statistical methods to analyze big medical data for disease prediction and treatment. Developed open-source software tools like FEAST, ReFACTor, and Bisque Recipients of prestigious awards including Rothschild Fellowship and ISCB Fellow (2021) Research Interests: Computational Genomics: Applying machine learning to genomic data (methylation, RNA expression) for disease understanding. Machine Learning in Medicine: Creating deep learning architectures for ophthalmology, anesthesiology, and acute care applications. Medical Data Science: Integrating electronic health records with genomic datasets for predictive modeling. Scientific Recognition: Rothschild Fellowship Technion-Juludan Research Prize Krill Prize in Science Elected ISCB Fellow (2021) Dr. Halperin's lab collaborates across disciplines, utilizing software platforms such as GLINT (methylation analysis) and MTV-LMM (microbiome prediction). His work has received funding from NIH, NSF, and international foundations.
Dr. Lauren E. Gillespie is an Assistant Professor in the Department of Geospatial Data Sciences at the University of Michigan, specializing in AI-integrated approaches for large-scale ecosystem monitoring. With a background in computer science and biology, her research focuses on developing foundation models to analyze noisy environmental data from remote sensing and citizen science platforms, aiming to enhance ecological forecasting under rapid climate change. PhD : Computer Science, Stanford University BS : Computer Science & Chemistry, Southwestern University Her work bridges machine learning , global ecology , and remote sensing , with recent publications on biodiversity mapping using deep learning, domain adaptation in citizen science datasets, and genetic diversity loss in the Anthropocene. She actively explores ethical frameworks for scalable environmental AI applications. Key scientific awards include the Best Paper Award at AAAI 2025, Fulbright Program support (2024), and NSF Graduate Research Fellowship (2019). Her projects have received grants such as the Climate Change AI Innovation Grant for ForestBench (2022) and the Ethics, Society and Technology Hub grant for Scenes from the Anthropocene (2022).
Peng Liu is a Professor at Iowa State University, specializing in statistical modeling and computational methods for microbiome and RNA-sequencing data analysis. His work spans plant genomics, stress response studies, and bioinformatics tool development. Developed software tools like C-REx and RiboZIP for genomic data analysis Key research areas: microbiome dynamics, differential translation, plant-pathogen interactions Collaborates with agricultural scientists to address drought tolerance and nutrient stress in crops His recent publications focus on advanced statistical approaches (e.g., hurdle Poisson models, variational inference) applied to multi-omics studies in sorghum and maize systems. He has contributed to understanding gene expression heterosis, ER stress responses, and microbiome impacts on plant resilience through peer-reviewed studies in journals like Bioinformatics, ISME J, and BMC Genomics.
Dr. Nicholas Matzke is a Senior Lecturer at the School of Biological Sciences , University of Auckland, New Zealand. His research revolutionizes biogeography by integrating extinction, fossils, organismal traits, and paleogeography into computationally efficient frameworks. Education: PhD in Integrative Biology (2013), University of California, Berkeley MA in Geography (2003), University of California, Santa Barbara Double BSc in Biology and Chemistry (1998), Valparaiso University Dr. Matzke's research spans three major domains: phylogenetic biogeography (developing methods to model trait-dependent dispersal), bacterial flagellum evolution (collaborating on experimental and bioinformatic analyses), and macroevolutionary modeling (integrating fossils and morphological data). His work on the FBD-MSC model and trait-dependent dispersal has transformed divergence time estimation and biogeographical inference. Recent publications show consistent focus on: Integrating molecular and fossil data in phylogenies Quantifying trait-dispersal interactions in rails and crocodiles Modeling historical biogeography using BioGeoBEARS Reconstructing evolutionary timelines with Bayesian methods His 2021 work on Caninae phylogeny demonstrates the power of combined MSC-FBD approaches, while 2019 studies on crocodilian range expansion revealed unexpected trait-dispersal correlations. Scientific Recognition: 2015-2018: Discovery Early Career Researcher Award (DECRA) Fellow at Australian National University 2017: Associate Fellow of The Higher Education Academy As an accredited PhD supervisor with active Marsden Grant projects, Dr. Matzke trains students in phylogenetics, computational modeling, and paleogeographic reconstruction. His lab combines custom software development with empirical studies across diverse taxa, from Rana frogs to Crocodylus crocodiles.
Sergio Baranzini is a Professor in the Department of Neurology at the University of California, San Francisco (UCSF) School of Medicine and a member of the UCSF Weill Institute for Neurosciences. With a distinguished career spanning over two decades at UCSF, Dr. Baranzini has established himself as a leading researcher in multiple sclerosis (MS) and neuroimmunology. Dr. Baranzini earned his BS/MS and PhD in Biochemistry/Biotechnology and Human Molecular Genetics from the University of Buenos Aires, Argentina, completing his PhD with honors in 1997. He then pursued postdoctoral training in neurogenetics at UCSF before joining the faculty in 2003. His research focuses on the genetic, genomic, and immunological aspects of multiple sclerosis, with particular emphasis on the gut-brain axis and microbiome's role in neuroinflammation. Dr. Baranzini's research employs a multidisciplinary approach integrating wet lab techniques (including DNA microarrays, proteomics, and laser capture microdissection) with dry lab analytical approaches (bioinformatics, complexity theory, and mathematical modeling). His work has revealed critical insights into MS pathogenesis, particularly how gut microbiota influences disease development and progression. Recent groundbreaking studies have demonstrated how specific gut bacteria from MS patients can trigger MS-like disease in animal models and how microbial metabolites affect remyelination processes. His laboratory has secured significant funding through multiple NIH grants, including as Principal Investigator on projects examining the genetic basis of MS progression and post-GWAS approaches to identify cell-specific genetic pathways underlying MS risk. As evidenced by his extensive publication record in top-tier journals including Science, Nature, and PNAS, Dr. Baranzini's work represents some of the most innovative research in neuroimmunology and MS pathogenesis. National Multiple Sclerosis Society (US) Advanced Postdoctoral Fellowship (2001) National Multiple Sclerosis Society (US) Harry Weaver Neuroscience Scholar Award (2009-2014) Department of Neurology UCSF Endowed Chair in Neurology (2010) National Multiple Sclerosis Society Stephen C. Reingold Award (2015) Department of Neurology UCSF Distinguished Professorship in Neurology I (2019) Department of Neurology UCSF Neurology Research Incentive Program 2 (N-RIP2) (2023) Barancik Prize for Innovation in Multiple Sclerosis Research (2024) Dr. Baranzini serves as an ad-hoc reviewer for numerous specialized journals and is an elected member of the American Neurological Association. His laboratory (iMSMS) actively collaborates with interdisciplinary teams worldwide to integrate knowledge across research domains through systems biology approaches. His current NIH-funded research explores automated evidential support from raw data for relay agents in biomedical knowledge graph queries and investigates the genetic basis of progression in multiple sclerosis.
Maria Brbic is an Assistant Professor of Computer Science at EPFL, previously a postdoctoral researcher at Stanford University under Jure Leskovec. Her research focuses on developing machine learning methods for biological and biomedical applications, particularly representation learning of high-dimensional datasets, open-world semi-supervised learning, and single-cell genomics. Her work includes the STELLAR method for spatial cell type discovery (Nature Methods 2022), the ORCA framework for open-world learning (ICLR 2022), and contributions to the Fly Cell Atlas (Science 2022). She is involved in the Chan Zuckerberg Biohub and Neuro-omics projects. She received the University of Zagreb's best thesis award, was recognized as a MIT Rising Star in EECS, and won the Basel Computational Biology Conference best poster award. Her research bridges computer science with cutting-edge biomedical discovery.
Paula Mouser is a Professor in the Department of Civil and Environmental Engineering at the University of New Hampshire. Her research focuses on microbial ecology in extreme environments, particularly in hydraulically fractured shale wells, and the biodegradation of industrial contaminants in water systems. Ph.D., University of Vermont M.S., University of Vermont B.S., Utah State University Mouser's work spans environmental microbiology, toxicology, and engineering, with key contributions to understanding: Microbial adaptation in shale gas wells Biodegradation of surfactants and PFAS Antibiotic resistance gene dynamics Uranium attenuation in contaminated aquifers SARS-CoV-2 wastewater surveillance Her recent publications (2024-2011) reveal trends in environmental impacts of hydraulic fracturing, wastewater treatment challenges, and microbial community responses to industrial contaminants.
Yanlei Diao is a Professor of Computer Science at École Polytechnique (France) with a joint appointment at the University of Massachusetts Amherst. She received her PhD from UC Berkeley in 2005. Her research focuses on scalable data systems, particularly in big data analytics, cloud computing optimization, and real-time stream processing. Research Interests: Her work spans cloud infrastructure optimization (UDAO project), explainable anomaly detection in data streams (EXAD), interactive data exploration (AIDEme), genomic data analysis (GESALL), and uncertain data management (CLARO). She leads the CEDAR team at Inria/LIX focusing on cloud-scale data exploration. Awards & Honors: ERC Consolidator Grant (2017-2023) CRA-W Borg Early Career Award (2013) NSF CAREER Award (2008) Keynote speaker at ACM DEBS 2021 and SWIFT 2023 AI Forum Best Paper Award at SIGMOD 2011 ACM SIGMOD Dissertation Honorable Mention (2005) Advising & Leadership: Mentored over 20 PhD students and postdocs, currently supervising 7 researchers. Served as PVLDB PC Co-Chair (2025-2026) and ACM SIGMOD Editor-in-Chief (2014-2019). Leads multiple projects with industry partners including Alibaba Cloud.
Ulrich Klostermeier is a researcher at the Institute of Clinical Chemistry and Laboratory Medicine, University Medical Center Hamburg-Eppendorf (UKE). His scientific work spans hemostasis, thrombosis research, and molecular mechanisms of coagulation disorders. Hematology Clinical Chemistry Stem Cell Research Translational Medicine His research focuses on thrombophilia , venous thromboembolism , and genetic regulation in both pediatric and adult populations. Key projects include investigations into protein C/S deficiencies , NOD2 interactions , and hemostatic biomarkers . Recent publications demonstrate expertise in translational thrombosis research , with significant contributions to understanding prothrombotic polymorphisms and stem cell applications in cardiac regeneration. Collaborative work includes international cohort studies and multicenter clinical research. Methodologically, he employs transcriptional profiling , mutation analysis , and animal models for studying blood coagulation dynamics. His scientific work has been published in journals covering hematology, molecular biology, and clinical chemistry. Key research trends: Thrombosis risk stratification Genetic basis of coagulation disorders Comparative pediatric/adult hemostasis Translational approaches to cardiac repair Computational transcriptional analysis Developmental biology applications
