Dr. Hillel Adesnik is a Professor in the Department of Neuroscience at the University of California, Berkeley, and a leading researcher in the neural basis of sensory perception. His lab focuses on cortical microcircuits, optogenetics, and neural coding, with emphasis on visual processing and memory formation. Key Research Areas: Cortical Microcircuits Optogenetic Tools Gamma Band Rhythms Neural Coding Mechanisms Dr. Adesnik has pioneered high-speed optical methods like 3D-MAP and 3D-SHOT to manipulate neural activity. His work spans cortical dynamics, synaptic plasticity, and cortical layer interactions, with applications in understanding learning algorithms and sensory inference. Selected Trends from Publications: Recent preprints and papers highlight advancements in cortical VIP neuron function, channelrhodopsin structures, and inter-areal computations. His team utilizes two-photon holography, cryo-EM, and computational modeling to decode perception-related neural codes. Scientific Awards: NIH Director's New Innovator Award (2013) Dr. Adesnik's lab collaborates with institutions like NIH and develops tools for awake animal studies. Funding includes grants from the Beckman Young Investigator Program and NIH.
Sharon Rozovsky is a Professor in the Department of Chemistry and Biochemistry at the University of Delaware's College of Arts & Sciences, where she leads research on oxidative stress response mechanisms and protein quality control pathways. Her work bridges biochemistry, chemical biology, and structural biology with direct implications for understanding neurodegenerative diseases and viral pathogenesis. Her academic foundation includes a B.S. from Tel Aviv University (1994) and a Ph.D. from Columbia University (2000), establishing her expertise in protein dynamics and redox biochemistry. These credentials underpin her innovative approaches to studying cellular stress responses. Rozovsky's research program centers on selenoproteins—proteins containing the rare amino acid selenocysteine—and their critical roles in endoplasmic reticulum (ER) stress resolution. She investigates how membrane-bound selenoproteins like Selenoprotein S and K regulate the ER-associated degradation (ERAD) pathway, with recent work revealing their surprising autoproteolytic activity and involvement in SARS-CoV-2 replication. Her lab pioneers chemical tools including expressed protein ligation and advanced 77Se NMR spectroscopy to characterize these systems at molecular resolution. Analysis of her 2021-2025 publications shows dominant themes in selenoprotein structure-function relationships, ER stress mechanisms, and viral interactions, alongside methodological innovations in cryo-EM grid technology and NMR. This body of work demonstrates consistent focus on redox biochemistry with expanding applications in virology and structural biology. No major scientific awards or fellowships were explicitly documented in the available materials, though her research impact is evident through high-impact publications and methodological contributions. She directs the active Rozovsky Research Group, mentoring graduate students and postdoctoral researchers in biochemical and biophysical techniques. Her laboratory operations are supported by competitive funding including an NSF CAREER award (2011) focused on selenoprotein reactivity, reflecting sustained recognition of her innovative research program.
Ying Ge is a Professor at the University of Wisconsin–Madison, jointly appointed in the Department of Cell and Regenerative Biology and the Department of Chemistry. Her research integrates chemistry, biology, and medicine, focusing on advanced mass spectrometry-based proteomic and metabolomic technologies to address cardiovascular diseases. Education: B.S., Peking University (1997) Ph.D., Cornell University (2002) Ying Ge's work centers on developing ultra high-resolution mass spectrometry platforms for top-down proteomics and metabolomics, applied to systems biology studies of heart failure and regenerative medicine. Key projects include myofilament protein modification mapping, stem cell therapy evaluation, and biomarker discovery for cardiac conditions. The 15 most recent articles highlight her lab's methodological innovations (e.g., photocleavable surfactants, native mass spectrometry) and biological discoveries in AMPK structural heterogeneity, RBM20-mediated cardiotoxicity, and sarcomere-metabolism cross-talk during regeneration. These publications span proteomics, metabolomics, structural biology, and clinical applications.
Steven A. Corcelli is a Professor and Interim Dean of the College of Science at the University of Notre Dame, with a research focus on Theoretical Chemistry and Molecular Dynamics Simulations . His work bridges Physical Chemistry and Biochemistry , targeting Energy Applications and Biomolecular Binding Mechanisms . He leads the Computational Molecular Science & Engineering Laboratory (CoMSEL). Ph.D., Chemistry, Yale University (2001) Sc.B., Chemistry, Brown University (1997) Research interests span ionic liquids for Carbon Capture , aqueous electrolytes in battery technologies , and molecular binding processes in immunology and DNA interactions . His group employs GPU-accelerated simulations and weighted ensemble methods to uncover structural and dynamic motifs. Recent publications highlight trends in vibrational spectroscopy , TCR-MHC binding , and CO2 solvation mechanisms . Awards include the Thomas P. Madden Award (2020) , ACS Fellowship (2016) , and NSF CAREER Award (2009) . Staff: Erin Brossard (Ph.D.), Nell Karpinski, Shuang Wu, Noah Vasconez, Kaitlyn Handy, Isabel Thompson
Christian P Petersen, PhD is a Professor in the Department of Cell and Developmental Biology at the Weinberg College of Arts and Sciences , Northwestern University Feinberg School of Medicine. His research focuses on molecular mechanisms underlying regeneration in planarians and other organisms. PhD: MIT (2006) Research Interests: Planarian regeneration and tissue patterning Wnt signaling pathway regulation Stem cell biology in regenerative contexts Neurogenesis and injury response Molecular mechanisms of tissue repair Affiliations: Center for Reproductive Science Robert H. Lurie Comprehensive Cancer Center
Matthew W. Buczynski is an Assistant Professor at the School of Neuroscience , part of the College of Science at Virginia Tech . Holding a Ph.D. in Biochemistry from the University of California San Diego (2008) and postdoctoral training at The Scripps Research Institute (2009-2016), he joined Virginia Tech in August 2016 after completing his postdoctoral fellowship. Education: B.S. in Chemistry, University of Michigan , 2001 Ph.D. in Biochemistry, University of California San Diego , 2008 Postdoctoral Training, The Scripps Research Institute , 2009-2016 Dr. Buczynski’s research program focuses on identifying novel druggable targets for addiction and neurological disorders through mass spectrometry and behavioral pharmacology . His work integrates chemical biology , molecular pharmacology , and in vivo microdialysis to study molecular changes in the brain during chronic drug exposure. Key areas include nicotine dependence , ethanol withdrawal , and cross-talk between pain and addiction mechanisms. His recent publications highlight endocannabinoid system modulation , TRPV1/TRPA1 receptor activation in pain, and diacylglycerol lipase (DAGL) mechanisms in nicotine withdrawal. He employs both self-administration and forced exposure models to validate therapeutic targets. Prospective students can contact him directly through his lab’s website .
Dr. Rebecca Berlow is an Assistant Professor in the Department of Biochemistry and Biophysics at the UNC School of Medicine , University of North Carolina at Chapel Hill. Holding a PhD from Yale University, her research focuses on intrinsically disordered proteins , protein dynamics and allostery , and NMR spectroscopy to study disease-associated macromolecules. PhD – Yale University Affiliation: UNC School of Medicine, University of North Carolina at Chapel Hill Research Interests include understanding how protein conformational changes and dynamic behavior mediate stress response pathways. The lab employs interdisciplinary approaches combining biophysics , structural biology , and complementary biochemical techniques to identify novel therapeutic strategies for diseases linked to dynamic macromolecular dysfunction. Publication Trends across 2007–2024 highlight consistent focus on protein dynamics , allosteric regulation , and biophysical characterization of disordered systems. Key topics include multivalency , redox-dependent structural changes , and therapeutic targeting of dynamic protein interactions. Training & Environment : Lab members engage in collaborative research across biophysical , structural , and chemical disciplines , with emphasis on professional development, conference participation, and inclusive scientific training.
Pamela Ronald is a Distinguished Professor of Plant Pathology at the University of California, Davis, affiliated with the Department of Plant Pathology within the College of Agricultural and Environmental Sciences. Her research focuses on understanding and enhancing crop resilience, particularly in rice, through genetic and molecular mechanisms. Key areas include plant immunity against pathogens, climate adaptation, and sustainable agricultural practices. Education and Background: Details on her academic qualifications are not explicitly mentioned in the provided text, but her career trajectory suggests advanced training in plant genetics and pathology. Research Interests: Ronald’s work centers on engineering disease-resistant crops, studying plant-microbe interactions, and developing climate-resilient varieties. Notably, she has contributed to identifying genes like XA21 that confer resistance to bacterial infections and pioneered methods to reduce methane emissions in rice. Her studies also explore the role of sulfated peptides in pathogen virulence and host defense mechanisms. Publications Trends: Her recent articles emphasize molecular mechanisms of plant immunity, genetic engineering applications, and sustainability challenges. Themes include directed evolution of immune receptors, machine learning in genotype-phenotype prediction, and mitigation of agricultural greenhouse gases. Awards and Recognition: While specific awards are not listed here, her leadership in plant genetics and advocacy for evidence-based biotechnology policies reflect significant recognition in her field. Grants and Advising: Ronald has led projects funded by agencies like the U.S. Department of Energy, focusing on bioenergy crops like switchgrass. She collaborates globally on initiatives such as the Rice Protein Tagging Project and the AI Institute for Next Generation Food Systems. Labs and Teams: She directs the Crop Genetics Innovation Lab at UC Davis, fostering interdisciplinary research in crop improvement and sustainable agriculture.
Dr. Yang Zhang is a Professor at the National University of Singapore (NUS), holding appointments in the Department of Computer Science (School of Computing) and the Department of Biochemistry (Yong Loo Lin School of Medicine). He also leads the Zhang Lab, which focuses on AI-driven computational methods for protein structure prediction and design. Previously, he was a Professor at the University of Michigan. His research integrates artificial intelligence, deep learning, and physics-based models to address challenges in computational biology. Affiliations: School of Computing; Yong Loo Lin School of Medicine; Cancer Science Institute of Singapore Key Roles: Principal Investigator of Zhang Lab; Developer of I-TASSER algorithm Research interests span AI-driven protein design, deep learning for RNA structure prediction, and drug discovery. Projects include the EvoDesign server for protein interaction design and TripletRes for coevolution-based contact prediction. Major contributions include the I-TASSER algorithm, ranked top in CASP experiments for protein structure prediction. Awards: Alfred P. Sloan Award, NSF CAREER Award, and seven-time Highly Cited Researcher (2015–2021).
Ketika Garg is a Postdoctoral Scholar Research Associate in the Division of the Humanities and Social Sciences at the California Institute of Technology (Caltech), with an office in the Broad Center for Biological Sciences. Her research focuses on the interplay between individual and social decisions, using experimental and computational methods to explore how social environments influence decision-making and collective behavior. She investigates contexts ranging from traditional foraging paradigms to modern social media landscapes, developing innovative experimental frameworks to study these dynamics. Her research interests span computational neuroscience, social media analysis, and collective behavior, with a particular emphasis on understanding exploration-exploitation trade-offs in both natural and digital environments. She has contributed to studies on hunter-gatherer foraging networks, online toxicity dynamics, and the evolution of search strategies in collective foraging systems. Her work bridges disciplines such as psychology, ecology, and computer science to address fundamental questions in decision-making and social interaction. Dr. Garg’s publications reflect her interdisciplinary approach, covering topics like synergy in collective problem-solving, the roots of online toxicity, and the application of Lévy walks in virtual foraging experiments. While no formal awards or grants are explicitly listed in the provided materials, her research trajectory demonstrates a commitment to advancing methodologies in computational social science. Contact: kgarg@caltech.edu Office: Broad Center for Biological Sciences (96) Phone: 626-395-1755
Igor Jurisica is a Professor at the University of Toronto and a Senior Scientist at the Krembil Research Institute’s Data Science Discovery Centre for Chronic Diseases. He also serves as Visiting Scientist at IBM CAS, Scientific Director of the World Community Grid, and Chief Scientist at the Creative Destruction Lab (Rotman School of Management). His research focuses on integrative computational biology, data mining, and AI-driven models for cancer mechanisms, drug discovery, and chronic disease management. Key affiliations include the Osteoarthritis Research Program, Schroeder Arthritis Institute, and leadership roles in open science initiatives like the World Community Grid, a global distributed computing platform with 810,000+ volunteers. Jurisica’s work bridges computational tools (e.g., NAViGaTOR visualization platform, MirDIP databases) and clinical applications, emphasizing explainable AI in healthcare. Research interests span proteomics, microRNA regulation, systems vaccinology, and multi-omics integration for disease stratification. Notable contributions include identifying prognostic signatures in cancer and osteoarthritis, machine learning models for drug repurposing, and sportomics analyses of athletic biomarkers. He has been recognized as a Thomson Reuters Highly Cited Researcher (2014-2016) and ranked among the Top 100 AI Leaders in Oncology (2023). His labs develop open-access tools like PathDIP, OsteoDIP, and miRAnno to advance translational research.
Jian Peng is an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. His research focuses on computational biology, machine learning, and their applications to protein structure prediction, drug design, and molecular modeling. He has contributed to advancements in antibody engineering, protein-ligand docking, and generative models for biological systems. Key research areas include: Machine Learning for Molecular Modeling Protein Structure Prediction Antibody and Peptide Design Genomics and Single-Cell Analysis Structure-Based Drug Discovery His work emphasizes integrating deep learning techniques with biological datasets to address challenges in precision medicine, drug development, and systems biology. Notable achievements include developing the FastFold system to accelerate AlphaFold training and pioneering flow-based methods for antibody design. Awards include the Overton Prize (2020), recognizing contributions to computational biology. His research has been published in top journals and conferences, spanning topics from protein mutation prediction to geodesic-based immune complex modeling.
Lara A. Estroff is a Full Professor and the current Chair of the Department of Materials Science and Engineering at Cornell University's College of Engineering. She has been a faculty member since 2005 and served as Director of Graduate Studies from 2015 to 2019. Her academic leadership and research excellence position her at the forefront of bio-inspired materials and biomineralization research. Her educational background includes a B.A. in Chemistry from Swarthmore College (1997) and a Ph.D. in Chemistry from Yale University (2003), followed by an NIH-funded postdoctoral fellowship at Harvard University in the lab of Prof. George M. Whitesides. Dr. Estroff's research centers on the fundamental mechanisms of crystal growth, biomineralization, and pathological mineralization. She investigates how organisms control mineral formation and applies these principles to engineer synthetic materials with complex structures and functionalities. Her work spans biomaterials, tissue engineering, and energy materials—particularly hybrid organic-inorganic perovskites for photovoltaics. She employs advanced characterization techniques and has pioneered in situ methods to monitor crystallization dynamics. Her recent publications reveal a strong trend toward interdisciplinary research, integrating materials science with cancer biology, immunology, and machine learning. The articles emphasize bio-inspired synthesis, mineral-tissue interactions, and the development of functional crystalline materials for medical and energy applications. Faculty Early CAREER Award, National Science Foundation (2009) Fiona Ip Li '78 and Donald Li '75 Excellence in Teaching Award, Cornell College of Engineering (2007) Marilyn Emmons Williams Award, Cornell Undergraduate Research Board (2009) Keynote Speaker, Gordon Research Seminar on Biomineralization (2012) Lawrence Berkeley National Lab Affiliate (2013) Dr. Estroff leads a major DOE-funded project titled “Formulation Engineering of Energy Materials via Multiscale Learning Spirals,” a $3 million, three-year initiative using machine learning to optimize perovskite synthesis for solar cells. She has advised numerous graduate students and postdoctoral researchers, and her lab is known for fostering collaborative, cross-disciplinary research. She has also contributed to educational initiatives at Cornell, particularly in undergraduate research and materials education. Her research group operates at the intersection of chemistry, engineering, and biology, focusing on high-resolution characterization of biominerals, in situ crystal growth studies, and the design of in vitro models for cell-mineral interactions. The lab actively collaborates with institutions including Lawrence Livermore National Laboratory, National Renewable Energy Laboratory, and Johns Hopkins University.
Maria Chikina is an Assistant Professor at the University of Pittsburgh School of Medicine's Department of Computational and Systems Biology. She holds a PhD in Molecular Biology from Princeton University. Her research focuses on developing computational methods to analyze large-scale genomic datasets, bridging statistical rigor with biological insights to overcome experimental biases. Key research areas include latent variable modeling (e.g., PLIER, CellCODE), interpretable neural networks for sequence-to-function modeling, evolutionary rate analysis (RERconverge), and applications in tumor immunology, exercise genomics, and infectious disease (e.g., SARS-CoV-2). Her lab has developed tools like InstaPrism, NIFA, and L0 segmentation for data-driven biological discovery. Her work spans collaborations with institutions like UPMC (on tumor microenvironment) and the Molecular Transducers of Physical Activity Consortium (MoTraPAC). Notable projects include analyzing convergent evolution in marine mammals and subterranean species, and developing epigenetic biomarkers for disease states through the ECHO program. Lab members include PhD students (Rezwan Hosseini, Tugrul Balci) and postdocs (Tina Subic, Anish Sevekari). Past students Wynn Meyer now leads a group at Lehigh University. Her group emphasizes open-source tools (GitHub repository ChikinaLab) and interdisciplinary approaches to systems biology challenges.
Onur Varol is an Assistant Professor at Sabanci University's Computer Science Department and leads the VIRAL Lab, which focuses on computational social science, network science, and machine learning. He has affiliations with the Center of Excellence for Data Analytics. His research spans social bot detection, misinformation analysis, and online behavior modeling.
