Heng Huang is the Brendan Iribe Endowed Professor in the Department of Computer Science and the Department of Electrical and Computer Engineering at the University of Maryland, College Park . He earned his Ph.D. in Computer Science from Dartmouth College and holds prior degrees from Shanghai Jiao Tong University. His research focuses on advancing the foundations and applications of artificial intelligence, particularly in machine learning, data mining, natural language processing, computer vision, and biomedical informatics . His work integrates large-scale optimization, fairness, and robustness in deep learning systems. Heng Huang’s recent publications demonstrate a strong trend in large language models, federated learning, model watermarking, continual learning, and medical image analysis . His work appears consistently in top venues like NeurIPS, ICML, CVPR, ICLR, and MICCAI, reflecting a broad impact across theoretical and applied AI. He actively mentors students and postdocs, seeking highly motivated researchers in machine learning and related domains. His work has significant implications for healthcare, privacy, and trustworthy AI.
Didier Trono is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he leads the Laboratory of Virology and Genetics (LVG) within the School of Life Sciences. Formerly, from 2004 to 2012, he served as the founding dean of EPFL's Faculty of Life Sciences, orchestrating its development and growth during this formative period. Trono received his medical education at the University of Geneva, followed by clinical training in pathology, internal medicine, and infectious diseases in Geneva and at Massachusetts General Hospital in Boston. His scientific career began at the Whitehead Institute of MIT, and in 1990 he was recruited by the Salk Institute of San Diego to launch an AIDS research center. After seven years in the United States, he returned to Europe and eventually joined EPFL. Dr. Trono's research has evolved significantly over his career. Initially focusing on virus-host interactions, he studied pathogens like HIV and Hepatitis B virus, creating HIV-derived genetic transfer tools that are now successfully used in gene therapy. For approximately the last fifteen years, his research has centered on epigenetics, particularly exploring the impact of retroelements and their control mechanisms on development and physiology of higher organisms, including humans. His laboratory investigates how transposable elements and KRAB zinc finger proteins regulate gene expression, with important implications for understanding cancer biology and developing new diagnostic and therapeutic approaches. Analysis of his recent publications (2022-2024) reveals a strong focus on transposable elements, KRAB zinc finger proteins, and their roles in gene regulation and cancer. His work combines molecular biology, genomics, and bioinformatics approaches to understand how these ancient viral remnants have been co-opted by the host genome to regulate development and cellular functions. The research spans basic molecular mechanisms to potential clinical applications in cancer diagnosis and therapy, with some recent work also addressing SARS-CoV-2 and immune responses. Throughout his career, Professor Trono has mentored numerous PhD students, including Bojkowska Karolina, Brandão Sanches Vong Martins Filipe Amândio, Bulliard Yannick, Coluccio Andrea, Corsinotti Andrea, Coudray Alexandre, De Tribolet-Hardy Jonas Caspar, and Dorschel Iris Arianna. His laboratory has received significant funding to support research at the intersection of virology, genetics, and epigenetics, contributing to EPFL's reputation as a leading institution in life sciences research. The Trono Laboratory continues to be at the forefront of research on retroelements and their regulatory mechanisms, maintaining a vibrant research environment that bridges fundamental biological questions with potential medical applications, particularly in cancer research and precision medicine.
Romain Lopez is an Assistant Professor of Computer Science and Biology at New York University, with a joint appointment in the Courant Institute of Mathematical Sciences and the Department of Biology. He will be joining NYU in September 2025, bringing expertise at the intersection of machine learning and computational biology. Prior to joining NYU, he was a Postdoctoral Fellow at Genentech and Stanford Medicine from 2021 to 2025, working with Jonathan Pritchard and Aviv Regev. Dr. Lopez received his educational training at prestigious institutions: PhD in Computer Science (2021) from the University of California, Berkeley, advised by Mike Jordan and Nir Yosef M.S. in Applied Mathematics (2016) from École polytechnique, Palaiseau, France Dr. Lopez's research focuses on developing machine learning methods to understand biological systems at the cellular level. His work bridges computational techniques with biological applications, particularly in single-cell and spatial omics analysis. He pioneered probabilistic approaches for single-cell analysis with scVI and co-developed scvi-tools, now widely adopted tools in the field. His research spans deep generative models, causal inference, perturbation modeling, and representation learning for biological data. His publication record demonstrates a consistent trajectory of innovation in computational biology, with recent work focusing on spatial biology, disentangled representations of cellular perturbations, and causal modeling of cellular responses. He has made significant contributions to the field of single-cell analysis, developing methods that help scientists interpret complex cellular data and predict how cells respond to various perturbations. Dr. Lopez has received numerous honors and awards for his research: Best Paper Award from the ICML Workshop on AI for Science (2024) Best Paper Award Honorable Mention from the AAAI Conference on Artificial Intelligence (2021) Best Student Poster Award from the ICML Workshop on Computational Biology (2019) UC Berkeley EECS Departmental Graduate Fellowship (2016) Carnot Foundation Fellowship (2016) Monahan Foundation Fellowship (2016) French National Defence Medal, Bronze Echelon (2014) At NYU, Dr. Lopez will lead the Biological Machine Learning group, which develops probabilistic machine learning methods to uncover biological mechanisms governing cellular behavior and disease. His lab focuses on creating tools that transform complex cellular data into biological insights, with applications in understanding cancer, immune responses, and fundamental cellular processes. His work has significant implications for precision medicine and drug discovery.
Richard M. Murray is the Thomas E. and Doris Everhart Professor of Control and Dynamical Systems and Bioengineering at the California Institute of Technology (Caltech). He holds a B.S. from Caltech (1985), M.S. from UC Berkeley (1988), and Ph.D. from UC Berkeley (1990). He has served in academic roles from Assistant Professor (1991–1997) to his current endowed professorship. He chaired the Engineering and Applied Science division (2000–2005) and Biology and Biological Engineering (2020–2024). His research focuses on feedback control in biological and autonomous systems, synthetic cells, and networked control systems. Collaborators include experts in robotics, synthetic biology, and systems biology. Key awards include the IEEE Control Systems Award and election to the National Academy of Engineering. His educational contributions span courses on control systems, robotics, and bioengineering. Current research projects include the Developer Cell initiative (Sloan Foundation), layered testing for autonomous systems (AFOSR), and microbiome-based environmental solutions (CHARMME, ARO). He advises numerous graduate students and postdocs, with notable alumni in academia and industry. Labs include facilities in Keck and Steele laboratories at Caltech. His work bridges control theory, synthetic biology, and autonomous systems to address societal challenges like environmental monitoring and safe autonomy.
Daniel Goldman is a Professor at the School of Physics within the College of Sciences at Georgia Institute of Technology. He directs the Complex Rheology And Biomechanics (CRAB) Lab and leads interdisciplinary research bridging physics, biology, and robotics. His work focuses on locomotion principles in organisms and robots interacting with complex media like granular materials. Research areas include robophysics, biomechanics, and nonequilibrium systems Co-founder of startup Ground Control Robotics Research Trends : His publications emphasize principles of locomotion, interaction with complex substrates (sand, bark, etc.), and robotics applications, using experimental, computational, and robophysical modeling approaches. Scientific Awards Dunn Family Professor (2017-2023) APS Fellow (2014) Georgia Power Professor of Excellence (2014) PECASE (2014) DARPA Young Investigator Award (2012) NSF CAREER Award (2012) Blanchard-Milliken Fellowship, Georgia Tech (2010) Sigma Xi Young Faculty Award, Georgia Tech (2010) Burroughs Wellcome Fund Career Award (2006) Outstanding Dissertation Award, UT Austin (2003) Advising & Grants : While specific students aren't listed, he leads a research group studying organism-robot interactions. His grants include NSF CAREER, DARPA Young Investigator, and Burroughs Wellcome Fund Career Award. He also participates in IRI's Robotics and Bioengineering and Bioscience initiatives.
Adam Runions is a researcher in the Department of Computer Science at the University of Calgary, leading the MPG Partner Group in computational analysis of leaf development through collaborative work with Miltos Tsiantis. His group is embedded in the Graphics Cluster, focusing on interdisciplinary problems at the intersection of computer science and developmental biology. University of Calgary - Department of Computer Science MPG Partner Group (2022) Graphics Cluster affiliation His research explores computational modeling and analysis of plant form and development across multiple scales, integrating geometric modeling, physically-based simulation, and computer-aided design. Key themes include plant morphogenesis, self-organization of natural forms, and cross-disciplinary applications in computer graphics and animation. Recent publications emphasize plant development (leaf shape, bark patterning), mathematical modeling (auxin-driven patterning), and geometric techniques (subdivision surfaces, PUPs). Collaborations span institutions like the Max Planck Institute for Plant Breeding Research. Scientific Awards Marie Sklodowska-Curie Fellowship Best Paper Award (International Conference on Cyberworlds 2015) Best Student Paper Award (Computer Graphics International 2011) The group actively recruits BSc, MSc, and PhD students with backgrounds in computer science and mathematics for projects on plant form simulation and digital content creation. Research integrates evolutionary biology, biomechanical modeling, and computational techniques.
Prof. Marcy Zenobi-Wong is a Full Professor at ETH Zurich's Department of Health Sciences and Technology, specializing in biofabrication and tissue engineering. Her research focuses on cartilage regeneration using advanced biomaterials, including nanofilm coatings and 3D printing techniques. She holds patents in tissue engineering and has pioneered methods like filamented light (FLight) biofabrication for creating anisotropic tissues. Her academic journey includes a B.Sc. from MIT (1985), M.Sc. and Ph.D. from Stanford (1987, 1990), followed by postdoctoral work at the University of Michigan. She leads the Biofabrication Group at ETH, developing therapies for joint repair and regenerative medicine. Courses taught include Biomedical Engineering and Materials and Mechanics in Medicine . Research highlights include engineered hydrogels for cartilage protection, CRISPR-driven gene editing in chondrocytes, and biohybrid neural interfaces. Her work bridges material science, cell biology, and clinical applications, with a focus on translational medicine. Collaborative projects involve creating elastic cartilage grafts for microtia reconstruction and volumetric printing of complex tissue constructs.
Megan Valentine is a Professor of Mechanical Engineering at the University of California, Santa Barbara (UCSB), affiliated with the College of Engineering. She leads an interdisciplinary research group focused on biological and bioinspired materials, investigating how forces are generated and transmitted in living systems to design responsive synthetic materials. Her work bridges engineering, physics, chemistry, and biology. Education: PhD in Physics from Harvard University, MS in Physics from the University of Pennsylvania, and BS in Physics from Lehigh University. Affiliations include the California NanoSystems Institute (CNSI), Materials Research Laboratory (MRL), Neuroscience Research Institute, and the Center for Stem Cell Biology and Engineering. Research interests span soft material mechanics, bioengineering, and systems biology, with applications in marine-inspired materials, mechanobiology, and soft robotics. Her lab employs advanced experimental techniques to study biophysical and biochemical mechanisms in living systems and translate them into engineered materials capable of self-healing, movement, and environmental responsiveness. Notable awards include the NSF Early CAREER Award, Fulbright Scholarship, and election as Fellow of the American Physical Society and American Institute for Medical and Biological Engineering. Her contributions emphasize creativity, collaboration, and diversity, with a focus on addressing societal challenges through interdisciplinary innovation.
Andrew Holle is an Assistant Professor at the Mechanobiology Institute , National University of Singapore , where he leads the Confinement Mechanobiology Lab within the Department of Biomedical Engineering . His work spans mechanobiology, stem cell differentiation, cancer mechanobiology, and microfluidics, with a focus on understanding how physical confinement influences cellular behavior. Education: B.S.E. in Bioengineering (Minor in Statistics), Arizona State University (2008) Ph.D. in Bioengineering, University of California San Diego (2013) Research in the Confinement Mechanobiology Lab centers on the hypothesis that stem cell differentiation is driven by mechanical cues during migration through confined extracellular matrix (ECM) environments. The lab develops microfluidic systems to mimic ECM confinement and studies its impact on osteogenic differentiation , cancer cell migration , and cellular condensates . Recent publications highlight interdisciplinary approaches combining mechanobiology , nanotechnology , and microfluidics to explore nuclear morphological changes, volume regulation, and ligand signaling in confined cellular environments. Laboratory Members: Privita Edwina (Research Fellow) Vaishnavi Rangaraj (Research Assistant) Sriram Muthukumar (Research Fellow) Chang Ye Ji (PhD Student) Gao Xu (PhD Student) Lim Yuan Bin (PhD Student) Shinny Sunny (PhD Student) Lee Jia Wen Nicole (PhD Student) Li Yixuan (PhD Student)
Vivek Shenoy is the Eduardo D. Glandt President's Distinguished Professor at the University of Pennsylvania, with primary appointments in the Department of Materials Science and Engineering and secondary appointments in Bioengineering and Mechanical Engineering and Applied Mechanics. He leads the Multiscale Mechanobiology and Biomaterials Laboratory, which focuses on developing theoretical frameworks and numerical methods to understand complex biological and engineering systems across multiple length scales. Shenoy's research spans mechanobiology, chromatin organization, cell mechanics, and biomaterials. His work addresses the fundamental challenge of modeling how small-scale cellular phenomena couple with long-range tissue-level interactions across micrometers to centimeters. By integrating insights from soft matter physics, solid mechanics, chemistry, and applied mathematics, his group develops multiphysics continuum and mesoscale theories to elucidate mechanisms controlling both biological and engineering systems. His recent publications demonstrate an increasing focus on nuclear mechanics, chromatin organization, and the interplay between mechanical forces and gene regulation. Analysis of Shenoy's publication record reveals a strong interdisciplinary approach, with high-impact papers spanning biophysics, materials science, and cell biology. His work shows consistent evolution from fundamental mechanics of materials to complex biological systems, with recent emphasis on the mechanical regulation of chromatin architecture, cell migration dynamics in 3D environments, and mechanotransduction in development and disease. His publications appear regularly in top journals including Nature, Science, and their affiliated publications, demonstrating significant influence across multiple fields. Eduardo D. Glandt President's Distinguished Professor Multiple publications in Nature, Science, and PNAS Active research program with publications through 2025 Shenoy actively mentors students and postdocs through his laboratory, with numerous co-authored publications indicating strong mentorship. His research program appears to be well-funded through multiple grants supporting his work in mechanobiology and biomaterials. The Multiscale Mechanobiology and Biomaterials Laboratory maintains active collaborations across disciplines and institutions, reflecting the interdisciplinary nature of his research. The Multiscale Mechanobiology and Biomaterials Laboratory, housed within the Department of Materials Science and Engineering at the University of Pennsylvania, serves as the primary research hub for Shenoy's work. The lab maintains an active presence on social media (Twitter: @ShenoyLab) for updates on activities and publications. Their research approach combines theoretical modeling with experimental validation to address fundamental questions at the interface of mechanics, materials science, and biology.
Aisha Ameen is a Researcher in the Department of Veterinary and Animal Sciences (Pathobiological Sciences) at the University of Copenhagen's Faculty of Health and Medical Sciences, holding dual appointments as Research Assistant and Guest Researcher. Her research centers on Alzheimer's disease mechanisms with emphasis on astrocyte metabolism, glucose/glutamate dynamics, and short/medium-chain fatty acid roles. She employs functional metabolic mapping, dMRI, immunohistochemistry, and hiPSC models to investigate neurodegenerative processes at cellular and systemic levels. Analysis of her 2022-2025 publications reveals consistent focus on metabolic dysregulation in Alzheimer's pathology, particularly astrocyte energy substrate competition and fatty acid interventions. Her work bridges neuroscience, metabolism, and translational disease modeling with significant citation impact and media attention.
Craig Davis is a Professor and holds the Bollenbach Chair in Wildlife Management at Oklahoma State University's Department of Natural Resource Ecology & Management. He has been a faculty member since 2001, advancing from Assistant Professor (2001-2007) to Associate Professor (2007-2012), and has served as Bollenbach Chair since 2014. Davis earned his PhD in Wildlife Science from Texas Tech University (1996), an MS from Iowa State University (1991), and a BS from Ohio State University (1988). He is also a Certified Wildlife Biologist through The Wildlife Society. His research focuses on avian ecology, wetland restoration, and gamebird management, with specific interests in fire-grazing interactions, invertebrate communities, and climate change impacts on ecosystems. Key areas include grassland bird survival, wetland classification systems, and the effects of anthropogenic development on wildlife habitats. Davis actively collaborates with conservation organizations and agencies, addressing challenges like invasive species management and water infrastructure resilience. Teaching responsibilities include undergraduate courses on Wildlife Management Techniques and Wetland Ecology, as well as graduate courses like Advanced Wetland Ecology. His grants emphasize wetland restoration outreach, climate adaptation strategies, and studies on northern bobwhite and wild turkey populations. Notable projects include evaluating cellular transmission technology in wildlife monitoring and assessing the impact of extreme weather on gamebird survival. Grants (Selected): Expansion of potential wetland restoration opportunities in Oklahoma (2024-2027) Linking Research and Stakeholder Engagement for Wetland Conservation (2024-2026) Effects of Extreme Weather and Hunting on Northern Bobwhite (2023-2025) Research Themes: Aligns with UN Sustainable Development Goals 15 (Life on Land), 13 (Climate Action), 6 (Clean Water), 11 (Sustainable Cities), 14 (Life Below Water), and 9 (Industry/Infrastructure).
Pierre Vandergheynst is a Full Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) in the Department of Electrical Engineering, with a courtesy appointment in Computer and Communication Sciences. He serves as EPFL’s Vice-Provost for Education since 2015 and leads the Signal Processing Laboratory 2 (LTS2). His research spans harmonic analysis, sparse approximations, mathematical data processing, and applications in signal/image processing, computer vision, machine learning, and graph-based data analysis. PhD in Mathematical Physics (1998), Université catholique de Louvain Postdoctoral Researcher at EPFL (1998-2001) Assistant Professor at EPFL (2002-2007) His research explores geometry/symmetry in high-dimensional data, redundant dictionaries for dimensionality reduction, and computational harmonic analysis on manifolds. Recent work focuses on protein structure modeling, geometric deep learning, and graph-based signal processing. Key article trends include graph neural networks for protein analysis, geometric deep learning in neuroscience, and structured knowledge priors in neural models. His 2023-2025 publications emphasize interpretable AI, long-range dependencies in graphs, and molecular representation learning. Scientific Awards: IEEE Signal Processing Magazine Best Paper Award (2023) Signal Processing Society Best Paper Award (2022) Apple ARTS Award (2007) De Boelpaepe Prize, Royal Academy of Sciences of Belgium (2009-2010) He has supervised over 30 PhD theses and contributed to foundational work in graph signal processing, compressive sensing, and geometric deep learning. His lab develops tools for data science on non-Euclidean structures, with applications in medicine, astronomy, and wireless systems.
Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .
Yaojun Zhang is an Assistant Professor in the Department of Physics & Astronomy and the Department of Biophysics at Johns Hopkins University. She earned her PhD in Physics from the University of California, San Diego (2015), followed by postdoctoral fellowships at the Princeton Center for Theoretical Science (2015-2018) and the Princeton Center for the Physics of Biological Function (2018-2021). Her research focuses on biological physics, particularly the complex behaviors of biomolecules and their assemblies across scales—from single-molecule folding to intracellular transport and biomolecular phase separation. She employs theoretical, mathematical, and computational tools to bridge biological questions with physical principles. Education PhD in Physics, University of California, San Diego (2015) Postdoctoral Fellowships: Princeton University (2015-2021) Research Interests Her group studies biomolecular condensates and liquid-liquid phase separation, exploring how microscopic interactions determine macroscopic properties of cellular compartments. Key areas include: Biomolecular condensate formation and dynamics Phase separation in cellular environments Interactions between biomolecules and cellular components Biophysics of intracellular transport Collaborations & Tools Zhang collaborates with experimentalists to validate theoretical models and develops frameworks for understanding condensate functions, such as surface tension, stoichiometry, and phase diagrams. Her work addresses challenges like condensate stability, molecular exclusion, and biological function regulation. Labs & Resources She leads the Zhang Lab , which integrates experimental and computational approaches. Her team’s research is supported by resources at the Bloomberg Center for Physics and Astronomy.
