Joel Weadge is an Associate Professor in the Biology Department at Wilfrid Laurier University , Waterloo, Ontario. His research focuses on bacterial biofilms, glycobiology, and protein structure-function relationships. Contact: jweadge@wlu.ca , Office: BA425 (Bricker Academic). Education: PhD in Microbiology (University of Guelph, 2006) BSc (Hons) in Microbiology (University of Guelph, 2000) Research Interests center on bacterial biofilms as virulence factors in pathogens like E. coli and Salmonella . Key areas include: Structural and functional characterization of biofilm proteins (cellulose, curli fimbriae) Enzymology of carbohydrate modifications (acetylation, phosphoethanolamine transfer) Developing therapeutics targeting biofilm synthesis Biopolymer applications for medical/industrial use Publications highlight studies on Pseudomonas and Salmonella biofilm mechanisms, glycosyltransferases, and carbohydrate-active enzymes, with methodologies spanning X-ray crystallography to high-throughput biofilm profiling. Labs and Teams: The Weadge Lab investigates biofilm roles in food/water security and oral health, utilizing enzymology, mass spectrometry, and structural biology. Current members include graduate students, technicians, and research assistants.
Mike Kirby is a Professor at the Kahlert School of Computing, University of Utah. He also holds adjunct professorships in the Department of Bioengineering and the Department of Mathematics. His current roles include leadership in scientific computing and informatics initiatives, including former directorships of the Utah Informatics Initiative (2019-2023) and the Multi-Scale Multidisciplinary Modeling of Electronic Materials (MSME) Collaborative Research Alliance (2016-2022). He has extensive experience in strategic research initiatives, including serving as Assistant Vice President for Research (2024-2025). Education: Dr. Kirby earned a PhD in Applied Mathematics (2002) and MS in Computer Science (2001) from Brown University, and a BS in Applied Mathematics and Computer Science from Florida State University (1997). Research Interests: Focus on large-scale scientific computing, physics-informed machine learning, computational science and engineering, high-order numerical methods, and visualization. His work bridges applied mathematics and computer science to address real-world engineering challenges. Publications: Over 150 peer-reviewed articles, including high-impact contributions in journals like Journal of Computational Physics and SIAM Journal on Scientific Computing . Recent work emphasizes machine learning for differential equations, topology optimization under uncertainty, and multi-fidelity modeling. Awards: Recognized for leadership in computational science and informatics, including contributions to University of Utah’s Clery Compliance Program. Advising & Grants: Supervised over 50 graduate students and postdocs. Secured funding from NSF, DOE, and industry partnerships, totaling millions in research grants. Active in interdisciplinary collaborations across engineering, materials science, and medicine. Labs/Teams: Scientific Computing and Imaging (SCI) Institute, Utah Informatics Initiative, and the Center for Multiscale Modeling of Electronic Materials (MSME).
Kenneth Hoehn is an Assistant Professor in the Department of Biomedical Data Science at the Geisel School of Medicine, Dartmouth College. As a computational immunologist with expertise in evolutionary biology, he develops computational evolutionary approaches to trace cellular lineages, particularly B cells, in contexts such as infection, vaccination, cancer, and autoimmune diseases. His research focuses on understanding adaptive immunity in conditions like COVID-19 Food allergies Myasthenia gravis through collaborations with experimental teams. Key projects include: Phylogenetic modeling of B cell responses Evolutionary signatures in immune repertoires Tracking B cell dissemination in autoimmune diseases Epigenetic regulation of memory B cells Recent publications highlight trends in single-cell immunology , phylogenetic inference , and computational tools for analyzing B cell dynamics. His lab at Dartmouth integrates evolutionary genetics with high-resolution immune profiling.
Xiaoyu Cai is an Assistant Professor at the Department of Medicine, Loyola University Chicago, specializing in lung regeneration, aging biology, and stem cell plasticity. Her research focuses on the molecular mechanisms governing alveolar type 2 (AT2) stem cell dynamics during aging and chronic lung diseases. Education: Bachelor of Medicine (Peking University, 2012), Master of Science (Peking University, 2015), PhD in Biology of Aging (USC & Buck Institute, 2021) Key Research Areas: Lung regeneration, inflammation resolution, stem cell aging, 3D organoid cultures Methodologies: Single-cell multiome, mouse genetics, multicellular organoid systems Collaborations: Translational partnerships with clinical teams for bench-to-bedside applications Dr. Cai's recent work explores lineage plasticity in aged lung stem cells, ferroptosis suppression via CRISPR screens, and cellular aging atlases across species. She previously held a postdoctoral position at Genentech Inc. and maintains a professional lab website. Contact: xcai2@luc.edu | Office: CTRE 123
Dana Pe'er is a Professor and Chair of the Computational and Systems Biology Program at the Sloan Kettering Institute (SKI) of Memorial Sloan Kettering Cancer Center. She is also an Investigator of the Howard Hughes Medical Institute and holds the Alan and Sandra Gerry Endowed Chair. Dr. Pe'er leads an interdisciplinary research group that combines advanced genomics approaches with machine learning to address fundamental questions in biomedical science, with particular focus on cancer biology, developmental biology, and immunology. Dr. Pe'er earned her PhD from Hebrew University in Jerusalem, Israel. Her academic journey includes a postdoctoral fellowship with George Church at Harvard Medical School. Before joining Memorial Sloan Kettering Cancer Center in 2016, she held faculty positions at Columbia University. Dr. Pe'er's research focuses on understanding cellular plasticity, the consequences of intra-tumor heterogeneity, cancer evolution and metastasis, and the mechanisms by which regulatory circuits go awry in disease. Her lab combines single-cell and spatial profiling technologies with machine learning approaches to investigate gene regulation, cellular plasticity, and cell-cell communication in the contexts of cancer, immunity, and development. They are particularly interested in how organisms develop from a single cell to generate diverse cell types, how epigenetic control rewires during development, and how cells communicate to execute multicellular responses. Analysis of Dr. Pe'er's recent publications reveals a strong focus on developing computational methods for single-cell and spatial genomics data analysis. Her work spans cancer types including pancreatic, prostate, colorectal, and breast cancer, with emphasis on tumor heterogeneity, metastasis mechanisms, and cellular plasticity. A significant portion of her research involves creating novel algorithms and tools like CellRank, REUNION, and SEACells that enable researchers to extract meaningful biological insights from complex genomic datasets. 2023 Class of 2023 Inductee - American Academy of Cancer Research (AACR) Academy 2023 Innovator Award - International Society for Computational Biology (ISCB) 2021 Fellow - International Society for Computational Biology (ISCB) Howard Hughes Medical Institute Investigator (2021) 2019 Ernst W. Bertner Memorial Award - University of Texas MD Anderson Cancer Center 2016 Lenfest Distinguished Faculty Award - Columbia University 2014 Director's Pioneer Award - National Institutes of Health 2014 Overton Prize - International Society for Computational Biology (ISCB) Dr. Pe'er is known for her dedicated mentorship approach, describing herself as "a mama bear" who cares deeply about her trainees while expecting independence, innovation, and hard work. She mentors numerous PhD students and postdocs in her lab. Her HHMI Investigator award provides approximately $9 million over seven years, enabling ambitious research directions. She also collaborates extensively with the Single-cell Analytics and Innovation Lab (SAIL) at MSK to generate new data from emerging technologies, working closely with wet-lab collaborators at MSK and beyond to apply computational methods to cutting-edge datasets across multiple disease areas. The Pe'er Lab is an interdisciplinary group of computational biologists with diverse backgrounds ranging from pure mathematics to clinical medicine. They work closely with wet-lab collaborators to apply their computational methods to cutting-edge datasets across cancer, immunology, and developmental biology. The lab is described as open, supportive, collaborative, and fun, with access to world-class facilities at the Sloan Kettering Institute. Dr. Pe'er's work continues to push the boundaries of computational biology and cancer research, with the ultimate goal of developing more effective, personalized therapies for cancer patients.
Dr. Igor V. Pivkin is a Full Professor at the Institute of Computing within the Faculty of Informatics at the Università della Svizzera italiana (USI) in Lugano, Switzerland. His academic journey includes degrees from Novosibirsk State University (B.Sc./M.Sc. Mathematics), Brown University (M.Sc. Computer Science and Ph.D. Applied Mathematics), and postdoctoral research at MIT's Department of Materials Science and Engineering. His research focuses on multiscale/multiphysics modeling , numerical methods , and large-scale simulations of biological and physical systems. Key areas include biophysics, cellular/molecular biomechanics, stochastic modeling, and coarse-grained molecular simulations. He leverages high-performance computing (HPC) and particle-based methods to address complex biological phenomena. His work spans diverse applications, from understanding cellular mechanosensitivity and biofilm engineering to modeling cancer cell behavior and red blood cell dynamics in the spleen. His contributions bridge computational science, biotechnology, and biomedical research. He has published extensively in top-tier journals, with recent work advancing automated biofilm analysis, deep learning for microbial classification, and systems biology approaches to metal bioleaching. His lab collaborates on interdisciplinary projects, emphasizing computational innovation for real-world biological challenges.
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.
Anders Krogh is a Professor at the Department of Computer Science, University of Copenhagen, and also holds a position at the Department of Public Health in the Section for Health Data Science and AI. He serves as the head of the Center for Health Data Science (HeaDS) in the Faculty of Health and Medical Sciences. Previously, he was affiliated with the Department of Biology at the University of Copenhagen until 2020. Dr. Krogh earned his PhD in theoretical physics but transitioned into machine learning and bioinformatics during his doctoral studies. His research spans both theoretical foundations and practical applications in these fields. He is particularly renowned for his pioneering work on hidden Markov models for biological sequences, which has had significant impact in computational biology. In recent years, Krogh's research has focused on deep generative models applied to gene expression data and other biomedical applications. His work bridges computer science with healthcare, developing AI-driven approaches for precision medicine, cancer diagnostics, and analysis of complex biological systems. His current research integrates machine learning with quantum computing applications in biomolecular modeling. Analysis of his recent publications reveals a strong trend toward applying artificial intelligence to healthcare challenges, particularly in rare diseases, cancer diagnostics, and personalized medicine. His work increasingly incorporates federated learning approaches to address privacy concerns while enabling collaborative research across institutions. There's also a growing emphasis on quantum computing applications in biomolecular modeling and drug discovery. As head of the Center for Health Data Science, Krogh leads interdisciplinary research efforts that bring together computer scientists, medical researchers, and clinicians. His team develops novel computational frameworks like MOSAIC for multimodal analysis of rare cancers and multiDGD for multi-omics data integration. These tools are designed to translate AI innovations into clinical practice while addressing the unique challenges of medical data.
Dr. Karen Anderson is a Professor at Arizona State University (ASU), affiliated with the School of Life Sciences, the Biodesign Center for Personalized Diagnostics, and the College of Health Solutions. Her research focuses on tumor biology and immune system interactions in cancer, particularly developing biomarkers for early detection of cancers like breast, ovarian, pancreatic, and HPV-related cancers. She employs molecular techniques such as protein arrays, next-gen sequencing, and functional genomics to identify therapeutic targets and vaccine candidates. Education: Ph.D. in Microbiology and Immunology (Duke University), M.D. from Duke University School of Medicine, and B.A. in Chemistry (University of Virginia). Research interests include cancer immunotherapy, autoantibody profiling, and translational applications of proteomics. Key achievements include pioneering autoantibody-based biomarker assays and investigating HPV serology in head and neck cancers. Awards include the Health Care Heroes Award and recognition as one of Arizona's Most Influential Women. Teaching responsibilities include courses on research techniques and honors thesis supervision. Grants span biomarker validation, cancer genomics, and point-of-care diagnostics. Active in professional service, including roles in grant review panels and public health initiatives.
Bertram Müller-Myhsok is a Research Professor and Research Group Leader at the Max Planck Institute of Psychiatry in Munich, Germany. His research focuses on statistical genetics and transcriptomic data analysis in psychiatric disorders, particularly major depression, PTSD, schizophrenia, and their treatment responses. He integrates machine learning with genetic and clinical data to develop predictive models and stratified treatment approaches. Professional activities include leadership roles in the International Max Planck Research School for Translational Psychiatry and collaborations with institutions like the Institut du Cerveau (Paris) and Bernhard Nocht Institute (Hamburg). His work spans genetic epidemiology, psychiatric genomics, and precision medicine, with over 400 publications in high-impact journals. Key research areas include identifying genetic risk factors for mental disorders, developing polygenic scores, and leveraging omics data to uncover disease mechanisms. He leads projects like Psych-STRATA, a Horizon Europe-funded initiative advancing personalized psychiatry through pharmacogenomics.
Dr. Rong Fan is the Harold Hodgkinson Professor of Biomedical Engineering and Professor of Pathology at Yale University. His research focuses on developing and applying single-cell and spatial omics technologies to study immune systems, cancer, and aging. His lab has pioneered technologies like the IsoCode microchip for high-throughput protein profiling, and spatial multi-omics platforms (e.g., DBiT-seq, spatial-ATAC-seq) to analyze tissue complexity at cellular resolution. He co-founded IsoPlexis, Singleron Biotechnologies, and AtlasXomics to commercialize these innovations. Education: PhD in Chemistry from UC Berkeley (2006), B.S. in Applied Chemistry from University of Science and Technology of China (1999). Postdoctoral training at Caltech before joining Yale in 2010. Research interests include CAR-T cell therapy optimization, spatial epigenomics, and multi-omics integration. Key achievements include discovering biomarkers predictive of CAR-T efficacy and defining spatial genomic landscapes in cancer and neuroinflammation. Awards: NSF CAREER Award, Packard Fellowship, election to AIMBE, CASE, and NAI. Serves on advisory boards for Bio-Techne and Yale Ventures. Active in training future scientists via the Yale Biomedical Engineering and Yale School of Medicine programs.
Dr. Channakeshava S. Umeshappa is a faculty member in the Department of Microbiology & Immunology and Department of Pediatrics at Dalhousie University, Canada . He holds a PhD in Immunology from the University of Saskatchewan and completed postdoctoral training at the University of Calgary. Education : DVM (Karnataka Veterinary Animal and Fisheries Sciences University, India), MVSc (Indian Veterinary Research Institute, India), PhD (University of Saskatchewan, Canada) Research Interests : Dr. Umeshappa’s program focuses on immunoregulation in chronic diseases , particularly autoimmunity and cancer. His lab employs genetically modified murine models , omics , synthetic biology , flow cytometry , and imaging to develop immunotherapies. His work emphasizes interdisciplinary collaboration with clinicians and scientists. Article Trends : Recent publications highlight nanomedicine applications in autoimmune liver disease (e.g., peptide-MHC nanomedicines, invariant NKT cell reprogramming) and cancer therapy (e.g., laser-responsive nanoparticles, tumor-to-lymph gels). Studies span immuno-informatics , cell signaling , and clinical outcomes analysis.
Yuyin Zhou is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, Santa Cruz (UCSC), within the Baskin School of Engineering. She previously held a postdoctoral fellowship at Stanford University, collaborating with Prof. Lei Xing and Prof. Matthew Lungren. She earned her Ph.D. in Computer Science from Johns Hopkins University under the supervision of Bloomberg Distinguished Professor Alan Yuille. Her research is centered on advancing biomedical artificial intelligence to match medical experts in decision-making. Key focuses include developing medical multimodal models, building fair and trustworthy real-time learning systems for clinicians and patients, enabling one-shot/few-shot adaptation of foundation models to diverse medical tasks, and generating synthetic data aligned with clinical knowledge. Dr. Zhou’s recent publications span top-tier venues such as Nature Medicine , Medical Image Analysis , ICLR, CVPR, NeurIPS, MICCAI, and ECCV, reflecting a strong trend in foundation models for medical imaging, trustworthy AI, and efficient deployment. Her work bridges computer vision, deep learning, and clinical applications, with notable projects including TransUNet, BioMedGPT, and MicroSegNet. She has been recognized with the Google Research Scholar Award and the Hellman Fellowship . Dr. Zhou actively contributes to the academic community as an Area Chair for CVPR, ICLR, MICCAI, and CHIL. She organizes workshops and tutorials, including the CVPR 2024 Workshop on Foundation Models for Medical Vision and MICCAI 2024’s FOMMIA tutorial. Google Research Scholar Award Hellman Fellowship Dr. Zhou is actively recruiting self-motivated PhD students and interns to work on machine learning, computer vision, and AI for healthcare. She leads a dynamic research group focused on pushing foundation models into real-world clinical settings. Her team has launched public datasets, such as a micro-ultrasound dataset for prostate segmentation, and open-sourced tools to foster community collaboration.
Hector Aguilar-Carreno is a Professor of Virology in the Department of Microbiology and Immunology at Cornell University's College of Veterinary Medicine, where he also serves as Associate Vice Provost in the Office of the Vice President for Research and Innovation. His research focuses on high-mortality paramyxoviruses including Nipah virus (NiV) and Hendra virus (HeV), as well as coronaviruses and other enveloped viruses. Dr. Aguilar-Carreno received his BS in Biochemical Engineering from Instituto Tecnologico de Tepic, Mexico, followed by an MS in Biology from California State University, Los Angeles, and a PhD in Biochemistry and Molecular Biology from the University of Southern California. He completed postdoctoral training in Virology at UCLA under Dr. Benhur Lee before becoming an Assistant Professor at Washington State University's Paul G. Allen School for Global Animal Health. His research spans four main areas: (1) Viral entry mechanisms, where his lab has identified novel domains in viral glycoproteins important for membrane fusion; (2) Viral egress, using multi-omics approaches to study viral assembly and budding; (3) Vaccine development using viral-like particles to generate neutralizing antibodies; and (4) Antiviral discovery targeting enveloped viruses. His lab employs innovative techniques including Flow Virometry and Raman Spectroscopy to study viral entry processes. Analysis of his recent publications reveals a strong focus on paramyxoviruses (particularly Nipah and Hendra viruses), coronavirus research, and the development of broad-spectrum antivirals. His work spans fundamental virology to translational applications, with numerous publications in high-impact journals including Nature, Science, and Cell Reports. President Elect of the American Society of Virology Chair of the American Society of Virology Diversity, Equity, and Inclusion committee Chair of the Cornell CVM Diversity Committee Director of the Cornell Program for Achieving Career Excellence Chair of 16 PhD student thesis committees Dr. Aguilar-Carreno has served on numerous scientific committees including the American Society for Virology Education Committee, the American Society of Microbiology Committee for Minority Education, and as a Standing Member of the VIR-A NIH study section. His leadership extends to chairing the Cornell CVM Diversity Committee and serving on the Cornell presidential postdoctoral fellowship committee, demonstrating significant commitment to diversity and mentorship in science.
Professor Chen Zhengming holds the Richard Peto Chair in Epidemiology at the University of Oxford's Nuffield Department of Population Health. He is also an Honorary Visiting Professor at institutions like Fudan University and Shanghai Institute of Biological Sciences. His research focuses on genetic epidemiology, clinical trials, and public health policy, with significant contributions to global health through large-scale studies like the China Kadoorie Biobank (CKB), a cohort of 512,000 adults. Key achievements include landmark trials demonstrating aspirin's benefits in stroke and dual-antiplatelet therapy in acute MI, influencing international guidelines. His work on cholesterol, tobacco-attributed deaths in China, and genetic studies on alcohol and cardiovascular risk has shaped policy and clinical practices. He leads a team of over 100 researchers and has published over 475 papers, including highly cited works in Lancet , NEJM , and Nature Medicine . Awards: Bayer International Aspirin Award (1997), Wellcome Trust Advisory Board (2022), and numerous international recognitions. Leadership: PI and Director of China Kadoorie Biobank; contributor to global consortia like the International Hundred K+ Cohorts.
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