Brian A. Primack is a Professor of Public Health with tenure at Oregon State University's College of Public Health and Human Sciences, serving as its dean since 2022. Previously, he was Dean of Education and Health Professions at the University of Arkansas and Dean of the Honors College at the University of Pittsburgh. His research focuses on social media's impact on mental health, including depression, anxiety, and loneliness. He has authored over 300 publications, including his book You Are What You Click , and secured over $10 million in federal research funding. Dr. Primack's research highlights both risks and opportunities of digital media. He emphasizes optimizing social media use through strategies like curating connections and mitigating negativity. His work intersects education, medicine, and public health, addressing disparities in health outcomes, such as those exacerbated during the pandemic. Notable awards include membership in the American Society of Clinical Investigation (2019) and the Next Big Idea Book Award shortlist (2021). His leadership philosophy prioritizes unlocking potential, fostering community trust, and advancing equitable health solutions. He oversees a college with nearly 2,400 students and $18 million in annual research funding, emphasizing community engagement and innovative scholarship.
Professor Klavs F. Jensen is the Warren K. Lewis Professor of Chemical Engineering and Professor of Materials Science and Engineering at MIT. His research focuses on integrating automation, machine learning, and robotics to accelerate materials discovery and pharmaceutical synthesis. He leads the Jensen Research Group, pioneering automated reaction systems with online analytics and optimization algorithms. Education: MS in Chemical Engineering (Technical University of Denmark, 1976); PhD in Chemical Engineering (University of Wisconsin, 1980). Research Interests: Thermochemistry, electrochemistry, photochemistry, Bayesian optimization, high-throughput experimentation, and AI-driven synthesis planning. He collaborates with MIT’s Machine Learning for Pharmaceutical Discovery Consortium to develop algorithms for drug development and process chemistry. Awards: Member of National Academy of Sciences (2017), Member of National Academy of Engineering (2002), Fellow of the American Association for the Advancement of Science (2007), and Fellow of the National Academy of Inventors (2022). Grants & Labs: Editor-in-Chief of Reaction Chemistry and Engineering ; holds 63 US patents and over 490 journal articles. His lab’s innovations include ASKCOS (open-source synthesis planning software) and automated platforms for closed-loop molecular discovery.
Todd A. Alonzo is a Professor of Research in the Department of Preventive Medicine at the University of Southern California . As Group Statistician for the Children's Oncology Group , he focuses on statistical methods for biomarker analysis, medical diagnostic testing, and clinical trial design in pediatric acute myeloid leukemia (AML). Education: B.S. in Statistics, California State Polytechnic University (1994) MS and PhD in Biostatistics, University of Washington (1997, 2000) Research Interests include: Development of statistical frameworks for diagnostic accuracy Genomic and proteomic profiling in AML Pharmacogenomic score systems for chemotherapy response Non-inferiority trial design in low-event-rate settings Health disparities in pediatric oncology Scientific Awards : Fellow, American Statistical Association (2018) Outstanding Teacher Award, International Society for Magnetic Resonance in Medicine (2017) NIH Predoctoral Cardiovascular Biostatistics Training Grant (1995) ENAR Biometrics Society Distinguished Student Paper Award (1999) WNAR Biometrics Society Best Student Oral Presentation (1999) Leadership & Service includes editorial board memberships (Biometrics, Pediatric Blood & Cancer, Biometrical Journal), reviewer for 30+ scientific journals, and roles on multiple Data Safety and Monitoring Boards. He served as President of the International Biometric Society Western Northern America Region (WNAR) in 2009.
Raphael Franzini serves as Associate Professor of Medicinal Chemistry at the University of Utah, actively contributing to the Biological Chemistry PhD Program. His research pioneers innovative chemical approaches for therapeutic development, with dual focus on DNA-encoded library technologies and bioorthogonal drug delivery systems. His educational foundation includes an M.S. from the Swiss Federal Institute of Technology (Lausanne) and a Ph.D. from Stanford University. This training underpins his group's multidisciplinary methodology combining organic synthesis, bioconjugation, computational modeling, and advanced imaging techniques. Dr. Franzini's research program centers on two transformative areas: First, advancing DNA-encoded library screening through computational integration to identify leads for challenging targets like Tankyrase and Sirtuin 6, with recent work addressing false negatives in machine learning prediction. Second, developing novel bioorthogonal release chemistry using isonitrile-tetrazine reactions for spatiotemporally controlled drug activation, validated in zebrafish models. His group emphasizes both technological innovation and therapeutic translation, with chemistry designed to minimize off-target effects in solid tumors. Analysis of his 15 most recent publications reveals escalating integration of computational methods with experimental library screening, alongside refinement of bioorthogonal release kinetics. The work spans chemical biology, medicinal chemistry, and pharmaceutical sciences, with growing emphasis on machine learning for library data interpretation and in vivo validation of drug-release systems. Dr. Franzini maintains an active research laboratory that provides comprehensive training in cutting-edge drug discovery methodologies. His group culture prioritizes both scientific innovation and researcher development, with projects spanning from fundamental reaction kinetics to therapeutic applications. The lab's infrastructure supports organic synthesis, molecular imaging, and computational analysis for advancing precision therapeutics.
Miguel Rodrigues is a Professor of Information Theory and Processing at University College London's Department of Electronic & Electrical Engineering. He leads the Information, Inference and Machine Learning Lab at UCL and serves as the founder and director of the master programme in Integrated Machine Learning Systems. Rodrigues is also the UCL Turing University Lead and a Turing Fellow with the Alan Turing Institute, the UK National Institute of Data Science and Artificial Intelligence. His academic background includes an undergraduate degree in Electrical and Computer Engineering from the Faculty of Engineering of the University of Porto, Portugal, and a PhD in Electronic and Electrical Engineering from University College London. He has held appointments at prestigious institutions worldwide including Cambridge University, Princeton University, Duke University, and the University of Porto. Dr. Rodrigues's research spans information theory, information processing, and machine learning. His work has attracted over £5 million in funding from competitive national and international funding bodies and resulted in more than 250 publications with over 8000 citations in leading journals and conferences, including top AI venues like NeurIPS, ICML, and ICLR. His recent publications demonstrate a strong focus on multimodal learning, machine learning security, climate modeling with satellite data, and applications of AI in healthcare and precision medicine. His work shows increasing interdisciplinary collaboration across fields from climate science to pharmaceutical engineering. IEEE Communications and Information Theory Societies Joint Paper Award 2011 Fellow of the Institute of Electronics and Electrical Engineers (IEEE) Prize for Merit from the University of Porto Prize Engenheiro Cristian Spratley Prize Engenheiro Antonio de Almeida Fellowships from the Portuguese Foundation for Science and Technology Fellowships from the Foundation Calouste Gulbenkian Dr. Rodrigues has served as Editor for IEEE BITS – The Information Theory Magazine and IEEE Transactions on Information Theory, among other editorial roles. He consults widely in machine learning and AI with government institutions, funding agencies, industry, and startups, and sits on committees responsible for AI standardization such as the BSI Art/1 working group. His leadership extends to directing research labs and educational programs focused on advancing machine learning systems. He leads the Information, Inference and Machine Learning Lab at UCL, which focuses on fundamental aspects of information theory and their applications to machine learning and data processing. The lab works on both theoretical foundations and practical implementations of learning systems.
Professor Amy Mullens (University of Southern Queensland) is a leading academic in public health, gender studies, and clinical psychology. Her work focuses on sexual and reproductive health, transgender health equity, and healthcare access for marginalized populations, particularly within correctional systems. Key Affiliations : School of Psychology and Wellbeing, Centre for Health Research, Institute for Resilient Regions. Research Themes : Intersectional health disparities, HIV/STI prevention, gender-affirming healthcare, and mental health interventions. Research Trends : Recent publications emphasize digital health tools for STI/HIV risk prediction, transgender health policy, and qualitative analyses of incarceration experiences. She frequently collaborates on systematic reviews and mixed-methods studies addressing health equity. Advising : Supervises 16+ doctoral and master’s students (2021-2025) on topics spanning trauma, health literacy, and sexual health interventions.
Dr. Xin Zhou is an Oxford-Bristol Myers Squibb Fellow at the Department of Computer Science, University of Oxford. Her research integrates computational modeling, clinical data, and experimental findings to investigate cardiac disease mechanisms and develop human-based simulations for drug evaluation. BSc and MSc in Life Sciences, Beijing Normal University DPhil in Computational Biology, University of Oxford Her work focuses on multi-scale cardiac modeling , particularly in ischemic heart disease and heart failure, exploring ionic currents, tissue conduction, and organ-level dynamics. She develops electromechanical simulations to study cardiac alternans and arrhythmic risks, translating these into clinical applications for patient stratification and pharmaceutical testing. Recent publications emphasize in silico clinical trials , sex-specific cardiometabolic analysis, and Purkinje network modeling. Collaborative efforts with clinicians and pharmaceutical partners highlight her translational approach to regulatory science. Model of the Year 2024, BioModels EPSRC Impact Acceleration Account Microsoft Research Project Award Recognition Award, University of Oxford She supervises PhD and MSc students in computational cardiology, while serving on the editorial board of Frontiers in Physiology . Her current projects involve digital twinning and predictive cardiac safety models to reduce animal testing reliance.
Dr. Mattia Andreoletti is a Lecturer at the Department of Health Sciences and Technology at ETH Zurich, working within the Professorship for Bioethics. His research spans philosophy of medicine and bioethics, with a focus on the ethical dimensions of AI in healthcare, dementia policy, drug regulation, and clinical reasoning. PhD from the European School of Molecular Medicine (SEMM), affiliated with the European Institute of Oncology (IEO, Milan) ORCID: 0000-0003-1880-0770 His work intersects with clinical ethics, particularly examining replicability in scientific research, evidential pluralism in drug regulation, and the ethical landscape of digital biomarkers. He contributes to courses such as Ethics in Drug Development and Ethics Workshop: The Impact of Digital Life on Society . The 15 most recent articles (2025-2023) highlight his engagement with AI ethics, dementia prevention, regulatory science, and clinical reasoning. Topics include ethical frameworks for digital biomarkers, evidential pluralism in drug approval, and philosophical foundations of rehabilitation sciences.
Professor Larry D. Lynd is a prominent researcher at the University of British Columbia's Faculty of Pharmaceutical Sciences, with additional appointments as a Scientist at the Centre for Health Evaluation and Outcome Sciences (CHEOS) at Providence Health Care Research Institute, Director of the Collaboration for Outcomes Research and Evaluation (CORE), Scholar at the Peter Wall Institute of Advanced Studies, and Associate of the UBC School of Population and Public Health. Dr. Lynd completed his PhD in the Department of Health Care and Epidemiology at UBC and a post-doctoral fellowship in health economics at McMaster University. As a pharmacist (BSP) and epidemiologist, he has developed a distinguished career at the intersection of health outcomes research, epidemiology, and health economics, with a particular focus on the application of large administrative health datasets to inform practice and policy. His research spans multiple high-impact areas including rare diseases, multiple sclerosis, respiratory disease, and genomic medicine. Dr. Lynd leads major research initiatives such as the CANadian PROactive Cohort study for People Living with MS, the GenCOUNSEL study evaluating whole genome sequencing for clinical genetic services, and the Early Health Technology Assessment platform for the Nanomedicines Innovation Network. His recent publications demonstrate a strong emphasis on health technology assessment, genomic medicine implementation, multiple sclerosis outcomes research, and addressing unmet needs in clinical genetic services. Dr. Lynd's scientific contributions have been recognized through prestigious awards including the Dr. John McNeil Excellence in Health Research Mentorship Award (2022), Fellowship in the Canadian Academy of Health Sciences (2018), and the UBC Faculty of Pharmaceutical Sciences PharmD Teaching Award (2014-2015). As a mentor, Dr. Lynd has supervised doctoral students including Tamara Mihic (PhD in Pharmaceutical Sciences) and Kennedy Borle (PhD in Interdisciplinary Studies). He has secured substantial research funding, with recent grants totaling over $5 million from organizations including the Canadian Institutes for Health Research, Genome Canada, MS Society of Canada, and Genome British Columbia. Dr. Lynd actively contributes to health policy through leadership roles on committees including as chair of the Health Canada Special Advisory Committee on Non-Prescription Drugs, Special Advisory Committee to the Respiratory and Allergy Therapies Division of Health Canada, BC Ministry of Health Services Expensive Drugs for Rare Diseases Committee, and the BC PharmaNet Data Stewardship Committee.
Jodi Schneider is an Associate Professor at the University of Illinois Urbana-Champaign , with affiliate appointments at the Beckman Institute , Health Care Engineering Systems Center , European Union Center , and Center for Health Informatics . She directs the Information Quality Lab and focuses on the science of science through argumentation and evidence analysis. PhD in Informatics (National University of Ireland, Galway) M.S. in Library and Information Science (UIUC) M.A. in Mathematics (UT-Austin) B.A. in Liberal Arts (St. John's College) Her research examines how scientific controversies persist through citation patterns, the role of knowledge brokers in public policy, and information quality in biomedical contexts. She has developed semantic frameworks for micropublications and knowledge maintenance in digital libraries. Recent publications include citation integrity studies in Scientometrics , retraction indexing in STI Conference , and argumentation mining in Human Language Technologies . Collaborative projects span institutions like Harvard Radcliffe Institute and RWTH Aachen . NSF CAREER Award IMLS Early Career Award Senior Member, Association of Computing Machinery Marie Curie Fellow She advises graduate students in information quality and knowledge representation , with funding from the Alfred P. Sloan Foundation , NIH , and European Commission . Her lab develops tools to combat scientific misinformation and improve public health informatics .
Caroline Samer is an Associate Professor at the University of Geneva (UNIGE) Faculty of Medicine and serves as the Head of the Division of Clinical Pharmacology and Toxicology at the Hôpitaux Universitaires de Genève (HUG) . She also acts as the Delegate to the Dean's Office for Data Issues since July 2023. Medical Degree (2001), PhD in Pharmacogenomics, Postdoctoral Fellowship in Molecular Pharmacology (Sydney) President of the Swiss Society for Clinical Pharmacology and Toxicology (SSPTC) and Swiss Society of Pharmacology and Toxicology (SSPT) Vice-President of Swissethics and the Geneva Research Ethics Committee (CCER) Her research focuses on personalizing drug therapy through pharmacogenomics and precision medicine , emphasizing gene-environment-disease interactions and omic technologies . Key themes include drug interactions , pharmacokinetic modeling , and therapeutic information . Recent publications highlight her work in pharmacogenomics , drug safety , and clinical pharmacology , with a focus on opioids , antiaggregants , and drug metabolism . Her collaborations span oncopediatrics , internal medicine , medical informatics , and pharmaceutical sciences . She leads the Samer-Daali Research Group , which integrates in vitro , in vivo , and in silico models to advance personalized therapy . Her work is supported by institutional affiliations with the Faculty Center of Translational Investigation in Biomarkers and CIOMS .
Prof. Felix Balzer is a Professor for Medical Data Science and Chief Medical Information Officer (CMIO) at Charité - University Medicine Berlin . He serves as Director of the Institute of Medical Informatics, leading digitalization efforts for patient care and overseeing implementation of the hospital's electronic medical record (EMR) systems. Medical Data Science professorship (2021) Director of Institute of Medical Informatics Acting Chief Information Officer (2024-2025) Deputy Chief Medical Officer for Clinical Digitalization (2025) His research focuses on: Digital healthcare transformation Machine learning in critical care Alarm fatigue mitigation Interoperability standards (FHIR, OMOP) Electronic health records (EHR) optimization Patient monitoring systems The 2025-2026 publications reveal expertise in ICU data analysis, predictive modeling for postoperative delirium, and pandemic response technology. His work bridges clinical practice with technical implementation through: Interdisciplinary teams Multi-center trials Real-time clinical data architectures Human factors in healthcare AI
Lars-Olof Johansson is a Senior Lecturer at Halmstad University's School of Information Technology, specializing in Informatics. His research focuses on digital service innovation from a learning perspective, emphasizing collaboration between diverse stakeholders and knowledge exchange in innovation processes. He is actively involved in the LeaDS research program (Learning in a Digitalized Society) and teaches in the bachelor's program 'Digital Business Development' and the master's program 'Digital Learning'. His work bridges educational methodologies and technological innovation, particularly in fostering environments where interdisciplinary learning drives successful digital service creation. Notably recognized as an 'Excellent Teacher in Informatics,' he integrates practical experience with academic rigor, contributing to both scholarly discourse and pedagogical advancements. Key projects include SESMA (2019-2021), exploring sustainable mobility solutions, and ongoing collaborations in boundary practices for ICT innovation. His publications span topics like knowledgeability in digital service innovation, ethics in autonomous systems, and collaborative learning frameworks. His awards highlight his pedagogical impact, while his research addresses systemic challenges in innovation through interdisciplinary approaches.
Dr. Barbara Polivka is the Associate Dean for Research and Professor at the University of Kansas School of Nursing. She holds a BSN and MSN from the University of Cincinnati College of Nursing and Health, and a PhD in Nursing from The Ohio State University. Her research focuses on environmental health (e.g., lead poisoning prevention, asthma triggers) and health services research (e.g., public health nursing standards, nursing workforce challenges). She has secured NIH, NIOSH, and AHRQ funding for projects addressing home safety hazards and asthma management in older adults. Professional Affiliations include the American Academy of Nursing (Fellow), American Public Health Association, and Midwest Nursing Research Society. Key grants include current NIEHS funding for real-time asthma exposure monitoring and prior NIOSH support for virtual home safety training. Awards include the Ruth B. Freeman Award (APHA) and Ohio Healthy Homes Achievement Award. Teaching spans undergraduate through doctoral levels, with emphasis on community/public health nursing. Mentored numerous PhD/DNP students in environmental health and health disparities. Current work explores口罩使用对哮喘患者的影响, pandemic-related disinfectant exposure risks, and medication literacy in aging populations.
Joel Greenhouse is a Professor of Statistics at Carnegie Mellon University (CMU), affiliated with the Department of Statistics & Data Science. He has been on the faculty since 1983 and held leadership roles, including serving as Associate Dean of the College of Humanities and Social Sciences from 1997 to 2002. He also holds an adjunct appointment as Professor of Epidemiology and Psychiatry at the University of Pittsburgh. His expertise spans statistical methodology, clinical trial design, and meta-analysis, with a focus on integrating data from multiple sources to address complex healthcare and public health challenges. Greenhouse earned his Ph.D. in Biostatistics from the University of Michigan and completed a postdoctoral fellowship at CMU. His research emphasizes developing statistical tools for observational studies, clinical trials, and meta-analytic frameworks, particularly in neurology, mental health, and public policy contexts. Notable contributions include analyzing the impact of media on youth suicide rates, improving aphasia classification through automated speech analysis, and evaluating highway safety through driver health data. Education: Ph.D. in Biostatistics, University of Michigan Affiliations: Adjunct Professor at University of Pittsburgh, Member of National Academy of Sciences’ committees Professional Service: Data and safety monitoring boards for NIH/VA studies, co-chair of Federal Motor Carrier Safety Administration review panels His awards include CMU’s Doherty Award for Education, Ryan Teaching Award, and E. Dunlop Smith Award for teaching excellence. His work bridges theoretical statistics with real-world applications, particularly in interdisciplinary collaborations across medicine, psychology, and public policy. Greenhouse’s recent articles highlight trends in leveraging large datasets for clinical insights (e.g., aphasiaBank), re-evaluating environmental and behavioral health associations, and advancing causal inference methods. His interdisciplinary approach ensures statistical rigor addresses societal challenges, from suicide prevention to highway safety.
