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Sonia MayoralView profile

Assistant Professor

• Glial Cell Biology
• Myelin
• Neuron-Glia Interactions
• +3 more

Sonia Mayoral is the Robert J. and Nancy D. Carney Assistant Professor of Neuroscience at Brown University. Her research focuses on studying cell-cell interactions in the brain, particularly the development and function of oligodendrocytes – glial cells critical for myelin formation. She explores how these cells contribute to myelination, remyelination processes, and their roles in neurological disorders like multiple sclerosis. Her work integrates cellular neuroscience, immunology, and drug screening methodologies. Research interests include glial cell biology, neuron-glial interactions, and the molecular mechanisms governing myelin repair. She investigates how environmental cues and signaling pathways regulate oligodendrocyte differentiation and function. Notable projects involve developing high-throughput screening platforms for MS therapeutics and studying sex-specific responses to neurodegenerative challenges. Her lab’s recent work includes clinical trials (Re-WRAP) evaluating Bazedoxifene for remyelination in women, and fundamental studies on regulatory T cell roles in myelin regeneration. She also examines how mechanical stimulation and epigenetic changes influence oligodendrocyte behavior. Her research bridges basic science and translational efforts, aiming to advance treatments for myelin-related disorders. Dr. Mayoral’s lab is active at Brown University, with a dedicated website detailing ongoing projects and collaborations. While no specific grants or students are listed here, her work reflects a strong focus on interdisciplinary approaches to neurodegenerative disease mechanisms.

Oded RegevView profile

Professor

• Theoretical Computer Science
• Lattice-based Cryptography
• Quantum Computation
• +3 more

Oded Regev is a Silver Professor at the Courant Institute of Mathematical Sciences, New York University. He has previously held positions at Tel Aviv University and École Normale Supérieure, Paris (CNRS). His research spans theoretical computer science, cryptography, quantum computation, and machine learning applications in biological discovery. Education: PhD in Computer Science, Tel Aviv University (2001) Regev is renowned for his work in lattice-based cryptography, including the introduction of the Learning With Errors (LWE) problem and Gaussian measures. He also leads research using interpretable machine learning to decode RNA splicing logic and nuclear speckle dynamics, with implications in disease and therapeutics. His recent articles focus on quantum factoring, RNA localization, and geometric lattice bounds. Scientific Awards: European Research Council (ERC) Starting Grant (2008) 2018 Gödel Prize 2019 Simons Investigator Award Best Paper Awards: STOC 2003, Eurocrypt 2006 Regev mentors students and postdocs in both theoretical computer science and computational biology. His lab has secured funding from NSF, NIH, and Additional Ventures. He co-founded the TCS+ online seminar series and serves as Associate Editor-in-Chief for Theory of Computing .

• Virology
• Molecular Pathology
• Host-Pathogen Interactions
• +5 more

Dr. Richard Y. Zhao is a tenured Professor in the Department of Pathology and Microbiology-Immunology at the University of Maryland School of Medicine. His research combines molecular biology, fission yeast genetics, mammalian biology, and virology to study virus-host interactions, particularly for HIV and Zika virus. He previously held academic positions at Northwestern University and Columbia University and has contributed to over 120 peer-reviewed articles. B.S., China Oceanography University (1981) M.S., Oregon State University (1995) Ph.D., Oregon State University (1991) Postdoctoral Training, Columbia University (1991-1992) Dr. Zhao's research focuses on: Virus-host interactions and pathogenicity High-throughput drug screening for antivirals Role of viral proteins in neuroinflammation and cancer Translational genomics in precision medicine His recent publications highlight SARS-CoV-2 ORF3a, Zika envelope proteins, and HIV protease inhibitors, emphasizing host-pathogen mechanisms across species. He has served on NIH panels and editorial boards for journals like Cell Research and Retrovirology . Scientific awards include: Fellow, American Academy of Microbiology (2019) Bernard L Mirkin Endowed Chair (2001-2004) Honorary Director, Shandong Gallo Institute (2009) Distinguished Service from SCBA (2015) Outstanding Service from CBA-USA (2016) Dr. Zhao also contributes to clinical diagnostics and personalized medicine through molecular testing and pharmacogenetics programs.

Wolfgang LorenzonView profile

Professor

• Particle Physics
• Nuclear Physics
• Astrophysics
• +4 more

Wolfgang Lorenzon is a Professor of Physics at the University of Michigan, specializing in experimental particle physics, nuclear physics, and astrophysics. His research spans three major experimental programs: the LUX-ZEPLIN (LZ) dark matter experiment at SURF, the MUSE experiment at PSI for proton radius measurements, and the SpinQuest collaboration at Fermilab studying hadronic physics. He has held significant roles in major collaborations including SeaQuest and HERMES, where he served as Deputy Spokesman from 1997-1998. His educational background includes a Ph.D. (1988) and Diploma (1984), both from the University of Basel. Lorenzon has built a distinguished research career focusing on precision measurements in particle and nuclear physics, with particular expertise in detector development and experimental techniques. Lorenzon's research interests center on fundamental questions in particle physics. His work on the LZ experiment involves developing the in-line radon removal system for the central time-projection chamber, crucial for enhancing the detector's sensitivity to WIMPs. At PSI, he leads the development of liquid hydrogen targets for the MUSE experiment, which aims to resolve discrepancies in proton charge radius measurements. His hadronic physics work with SeaQuest and SpinQuest focuses on understanding nucleon structure through antiquark distributions and polarized Drell-Yan processes. His research bridges theoretical questions with cutting-edge experimental techniques, often requiring innovative detector solutions. Analysis of his recent publications (2023-2025) reveals a strong focus on dark matter detection using liquid xenon technology, precision measurements of nucleon structure, and development of next-generation detectors. His work spans theoretical interpretation of experimental results, detector development, and analysis of fundamental particle interactions. The research shows increasing collaboration across international boundaries, with significant contributions to multiple major experiments simultaneously. Scientific Awards: Fellow of the American Physical Society Lorenzon has mentored numerous graduate students through completion of their Ph.D. degrees, with recent graduates including Haley Reid (2024), Noah Wuerfel and Chami Amarasinghe (2023), Maris Arthurs (2022), Marshall Scott (2020), and Daniel Morton (2019). His current research group includes postdocs, graduate students, and undergraduate researchers. His research is supported by multiple grants from the National Science Foundation (Grant 2110229) and the Department of Energy (Grant SC0019193 and Subcontract 734299), as well as University of Michigan funding. Lorenzon leads a research group with active laboratories at both the Homer A. Neal Laboratory (3265 HANL) and West Hall (357 WH) at the University of Michigan. His team collaborates with international groups at Fermilab, SURF in South Dakota, and the Paul Scherrer Institute in Switzerland. The group maintains strong connections with the LZ collaboration, MUSE experiment, and SpinQuest collaboration, contributing both technical expertise and physics analysis capabilities to these major international efforts.

Daniel CatchpooleView profile

Professor

• Childhood Cancer Research
• Genomics
• Biomedical Data Science
• +6 more

Professor Daniel Catchpoole serves as Deputy Head of School (Research) at the School of Computer Science, University of Technology Sydney (UTS), holding dual appointments at UTS and The Children's Hospital at Westmead. With over 20 years of research experience, he bridges computational sciences and pediatric cancer research through the Biomedical Data Science Lab in the Australian Artificial Intelligence Institute. His work integrates data analytics, artificial intelligence, and software development with molecular cancer biology to transform pediatric cancer treatment pathways. PhD in Cancer Cell Biology, University of New South Wales (1991-1995) Founding Fellow, Royal College of Pathologists Australasia (2010-present) Head, Children's Hospital at Westmead Tumour Bank (2001-present) Professor Catchpoole's research focuses on translational applications of genomics in childhood cancers, particularly acute lymphoblastic leukemia and neuroblastoma. His work combines high-throughput genomic technologies with advanced computational analysis to develop systems biology approaches for cancer patient assessment. Recent projects explore virtual reality applications for complex genomic data visualization and copper chelation therapies to enhance neuroblastoma immunotherapy. His research has received significant funding from Cancer Institute NSW, Sony Foundation, ARC, and NHMRC. His publication record spans biomedical data science, cancer genomics, and virtual reality applications in oncology. Recent work demonstrates leadership in 3D latent diffusion models for tumor segmentation, biobank economics, and innovative immunotherapies. His research consistently addresses the critical need for actionable knowledge from complex multidimensional biomedical data. Editorial Board Member, Cancers (2023) Associate Editor, Innovations in Digital Health, Diagnostics and Biomarkers (2019) Founding member and first President, Australasian Biospecimens Network Association Professor Catchpoole has supervised 17 Honours students (including 6 First Class Honours), 3 MSc students, and 12 PhD candidates across multiple institutions, with 6 current PhD students. His collaborative research bridges UTS's Faculty of Engineering and IT with The Children's Cancer Research Unit at The Children's Hospital at Westmead. Significant research funding includes Cancer Institute NSW grants, Sony Foundation VR projects, and ARC Discovery Projects focused on genomic data analysis and clinical decision support systems. His leadership extends to building frameworks for translational research, managing biobanks and clinical data linkages, and navigating governance requirements for cancer research. The Tumour Bank at Kids Research, CCRU, represents his long-standing commitment to pediatric cancer infrastructure development.

Miler T. LeeView profile

Associate Professor

• Gene Regulation
• Developmental Biology
• Computational Genomics
• +9 more

Miler T. Lee is an Associate Professor at the University of Pittsburgh , focusing on gene regulation during early embryonic development through high-throughput experimental and computational genomics. He earned his Ph.D. in Genomics and Computational Biology in 2009 from the University of Pennsylvania under Dr. Junhyong Kim, followed by postdoctoral work with Dr. Antonio Giraldez at Yale University. Joining the university in 2016, his research spans maternal-to-zygotic transition (MZT), RNA stability, pluripotency networks, and evolutionary developmental biology, utilizing model organisms like zebrafish, Xenopus, and Hydractinia symbiolongicarpus. Key Research Themes: Maternally inherited RNA dynamics during embryogenesis Mechanisms of RNA degradation and transcriptome remodeling Evolution of pluripotency networks in hybrid species Role of zinc signaling in fertilization barriers Computational tools for RNA regulation and sensing Scientific Awards: Pan-American Society for Evolutionary Developmental Biology Junior Faculty Award (2024) Outstanding New Investigator – International Xenopus Board (2023) Basil O'Connor Scholar – March of Dimes (2017-2019) Recent publications highlight his work on enhancer classification, RNA degradation mechanisms, and cross-species MZT comparisons. His lab develops innovative methods like RESA for regulatory sequence analysis and studies evolutionary divergence in RNA localization patterns. While the articles span computational and experimental approaches, they consistently address RNA's role in cellular identity, developmental timing, and evolutionary adaptation. Applications include understanding pluripotency, designing RNA biosensors, and elucidating fertilization barriers. Prospective Ph.D. students are encouraged to contact him for opportunities in gene regulation, development, evo-devo, and computational genomics.

Guy WoodwardView profile

Professor

• Ecology
• Aquatic Ecosystems
• Climate Change
• +7 more

Professor Guy Woodward is a Professor of Ecology at Imperial College London's Department of Life Sciences (Silwood Park), part of the Faculty of Natural Sciences. He leads the NERC ERCITE Programme and holds affiliations with the Freshwater Biological Association, serving on its Board of Directors. His research focuses on the impacts of stressors like chemical pollution, climate change, and habitat alteration on aquatic ecosystems, particularly food web dynamics and metabolic theory. Woodward has secured over £13M in grants, including a £2.5M ERCITE grant, and collaborates with international experts such as Dr. Jose Montoya and Prof. Owen Petchey. His work emphasizes individual-based approaches to ecological networks and the application of allometric scaling laws. Key contributions include studying geothermally heated streams in Iceland and experimentally warming mesocosms to understand climate impacts. Woodward has supervised numerous PhD students, including Dr. Gabriel Yvon-Durocher, Dr. Julia Reiss, and Dr. Eoin O'Gorman. Education: PhD in Ecology from the University of London and BSc (Hons) in Ecology & Environmental Management from Cardiff University. His research spans over 20 years, with notable grants from NERC, the European Science Foundation, and AXA Insurance. He co-authored the Next Generation Biomonitoring series and serves as Series Editor for Advances in Ecological Research (Elsevier). Current affiliations include the Georgina Mace Centre for the Living Planet and the Grantham Institute. Research highlights include quantifying climate-warming effects on food webs, developing metabolic theory applications, and investigating synergistic stressor impacts. His team explores ecological resilience, with projects like 'Restoration of Chalk Rivers' and 'Climate Change Impacts on Freshwater Food Webs'. Woodward's work bridges theoretical and applied ecology, aiming to inform conservation and ecosystem restoration strategies.

Yuan ZhongView profile

Associate Professor

• Applied Probability
• Stochastic Systems
• Operations Management
• +7 more

Yuan Zhong is an Associate Professor of Operations Management at the University of Chicago Booth School of Business . He previously held positions as an Assistant Professor at Columbia University’s Department of Industrial Engineering and Operations Research and was a Postdoctoral Scholar at UC Berkeley’s Computer Science Department. Education: PhD in Operations Research, MIT (2012) MA in Mathematics, Caltech (2008) BA in Mathematics, University of Cambridge (2006) His research focuses on applied probability and stochastic system design , with applications in cloud computing , supply chain management , and e-commerce logistics . Recent work explores multi-period production systems and dynamic resource allocation in data centers and healthcare operations . Recent publications analyze cloud value chains , sparse graph design for delivery networks, and process flexibility in manufacturing. He has contributed to journals like Operations Research , Annals of Applied Probability , and Stochastic Systems . Scientific Awards: 2012 Kenneth C. Sevcik Outstanding Student Paper Award Best Student Paper Award at ACM Sigmetrics (2012) He teaches courses in business process fundamentals and queueing theory , with a future schedule including Operations Management: Business Process Fundamentals (2025–2026). No explicit student advising list was provided.

David LatulippeView profile

Professor

• Membrane Science
• Bioprocessing
• DNA Purification
• +4 more

David Latulippe is a Professor in the Department of Chemical Engineering at McMaster University. He joined McMaster in 2012 after postdoctoral work at Cornell University and a PhD at Penn State University, focusing on membrane filtration for DNA purification. His industrial experience includes roles at ZENON Environmental (now GE Water) in hollow-fiber membrane design for water treatment. Research interests include Membrane science and technology Bioprocessing of therapeutic viruses Microscale systems for biological applications Environmental engineering solutions for water treatment Current projects involve collaborations with industry partners like Ceapro and Aevitas, and the development of a biomanufacturing automation lab with Sartorius. Recent publications highlight advancements in Nanofiltration and microfiltration for viral vectors Conductive membranes for electrochemical applications Microfluidic systems for DNA analysis Environmental monitoring of biocides and microplastics Scientific recognition includes the Young Membrane Scientist Award (2014). Teaching activities focus on Fluid Mechanics (CHEMENG 2O04) and Industrial Separation Processes (CHEMENG 4M03).

Alexei KoulakovView profile

Professor

• Neuroscience
• Theoretical Neurobiology
• Applied Mathematics
• +5 more

Alexei Koulakov is a Professor at Cold Spring Harbor Laboratory (CSHL) and the Charles Robertson Professor of Neuroscience. His research focuses on applying mathematical and computational approaches to unravel the principles of brain organization, particularly in sensory systems like olfaction and vision. Koulakov's work explores how neural circuits form during development, the role of genetic and experiential factors, and the evolutionary basis of brain architecture. Education: PhD in Physics from the University of Minnesota (1998). Key Research Areas: Olfactory system development, neural network modeling, and AI inspired by biological computation. Koulakov's recent publications emphasize cross-disciplinary integration of neuroscience and AI, including NeuroAI initiatives and DeepNose models predicting olfactory percepts. His team investigates how innate abilities are encoded genomically and how experience shapes neural networks. Scientific contributions include studies on primacy coding in olfaction, stochastic learning mechanisms , and high-throughput neural mapping . Awards include the Charles Robertson Professorship , reflecting his leadership in theoretical neuroscience. Koulakov collaborates extensively, with notable work on genomic bottlenecks , odor mixture interactions , and neural integrator models . His lab at CSHL is at the forefront of NeuroAI research, leveraging brain circuit insights to advance artificial intelligence.

• Materials Science
• Computational Modelling
• Optical Materials
• +3 more

Arslan Mazitov is a Researcher and Doctoral Assistant at the École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the School of Engineering (STI) and the Institute of Materials (IMX) . He is part of the Computational Science and Modelling Laboratory (COSMO) , focusing on computational materials science with an emphasis on van der Waals materials, optical properties, and machine learning applications. His research explores novel materials for photonics, energy storage, and nanotechnology. Mazitov's work bridges theory and experiment, employing advanced modeling techniques to predict material behavior and design innovative solutions. Key research areas include van der Waals heterostructures , optical anisotropy engineering , and AI-driven materials discovery . He has contributed to studies on semiconductors, 2D materials, and interfacial phenomena. His computational methods address challenges in predicting material stability, optical properties, and surface behavior under various conditions. Active in collaborative projects, Mazitov's work has practical implications for photonic devices, energy storage systems, and nanoscale engineering. His research emphasizes interdisciplinary approaches, combining computational modeling with experimental validation to advance material innovation.

Feng YanView profile

Associate Professor

• Big Data
• Machine Learning
• Systems
• +6 more

Dr. Feng Yan is an Associate Professor at the University of Houston's Computer Science Department, leading the Intelligent Data and Systems Lab (IDS Lab). He previously held an Associate Professor position at the University of Nevada, Reno. His research focuses on bridging Big Data, Machine Learning, and Systems, with interdisciplinary applications in wildfire science, materials engineering, and civil infrastructure. He has received prestigious awards such as the NSF CAREER Award and the Regents' Rising Researcher Award. Education: Ph.D. (2016) and M.S. (2011) in Computer Science from College of William and Mary; B.S. (2008) in Computer Science from Northeastern University. Research experience includes roles at Microsoft Research and HP Labs. Research Interests: Large Language Models (LLM), Distributed Deep Learning, AutoML, Serverless Computing, Federated Learning, and AI-driven domain sciences. His work emphasizes real-world impact through collaborations with industry and national labs. Publications: Over 60+ papers in top-tier venues like NeurIPS, ICLR, KDD, AAAI, SOSP, SC, and VLDB. Key contributions include ZeRO++ (collective communication optimization), Gradient Compression techniques, and Federated Learning frameworks like TiFL and HDFL. Awards: NSF EPSCoR Award ($20M), NSF CAREER Award, FAA BAKFAA Grant, and multiple best paper awards (IEEE CLOUD 2018, CLOUD 2019). Active in program committees for HPDC, ICAC, ICPE, and AAAI. Advising: Supervised over 30+ graduate/undergraduate students, with placements at Microsoft Research, IBM, Oak Ridge National Lab, Facebook, and MathWorks. Runs a vibrant lab with a focus on interdisciplinary AI/Systems research.

• Microbial Ecology
• Bacterial Interactions
• Carbon Cycling
• +3 more

Shaul Pollak is an Assistant Professor at the Division of Microbial Ecology within the Centre for Microbiology and Environmental Systems Science at the University of Vienna. His research focuses on bacterial interactions in ecosystems, particularly their roles in plant pathogen protection and carbon cycling across soil and marine environments. He leads a research group investigating how microbial processes scale from genetic mechanisms to planetary biogeochemical cycles. His primary research interests include microbial community assembly, bacterial metabolism of complex biopolymers, and evolutionary genomics of marine cyanobacteria. Current projects leverage genomic dark matter to predict soil carbon fluxes, examine plant-bacteria interactions under environmental change, and explore the diversity of Prochlorococcus marinus. His interdisciplinary approach integrates genomics, high-throughput experiments, and machine learning to bridge ecological and evolutionary theory. Analysis of his 2022-2025 publications reveals consistent themes in microbial community dynamics, with emphasis on polysaccharide degradation mechanisms, phage-bacteria interactions, and genomic predictors of bacterial metabolic functions. His work demonstrates how bacterial trade-offs and cross-feeding structures shape ecosystem processes from ocean biogeochemistry to human gut microbiome organization. Dr. Pollak actively recruits PhD students and postdoctoral researchers through university stipend programs, with current group members including Thomas Gaehtgens, Gerhard Gruber, Jyothsna Pujar, Qi Qi, Lior Shachar, Marco Sing, and Joana Valèrio. His laboratory maintains active collaborations across soil and marine microbial ecology projects, with research infrastructure supported by University of Vienna resources and external funding.

Katarina DomijanView profile

Associate Professor

• Bayesian applications to data analysis
• Machine learning
• Statistical computing
• +3 more

Katarina Domijan is an Associate Professor in Statistics at the Department of Mathematics and Statistics, Maynooth University, Ireland. She holds a PhD in Statistics from Trinity College Dublin (2008) and has been affiliated with Maynooth University since 2008, transitioning from Lecturer/Assistant Professor to her current role in 2024. Her academic career includes editorial roles as Associate Editor for The R Journal (2021–present) and the Journal of Computational and Graphical Statistics (2015–2024). Research Interests focus on Bayesian methods for high-dimensional data, particularly in classification problems. She specializes in feature selection and model visualization, with applications spanning agricultural data analysis (e.g., hyperspectral imaging for lactose prediction), medical diagnostics (e.g., sepsis and cancer detection), and space physics (e.g., Saturn Kilometric Radiation classification). Her work bridges theoretical statistics with real-world challenges, including socio-economic studies and forensic science. Key Research Areas Bayesian statistical inference Machine learning for large feature spaces Statistical computing and model interpretability Data visualization and chemometrics Scientific Contributions include leading projects like VistaMilk Phase II (2024–2030, €152,300) and Measuring Carbon Sequestration (2024–2028, €174,788.90). Her 15 most recent publications highlight advancements in ensemble modeling, spatial statistics, and medical diagnostics. Scientific Awards Associate Editor, The R Journal (2021–present) Associate Editor, Journal of Computational and Graphical Statistics (2015–2024) Student Supervision includes PhD and MSc graduates such as Dr. Bruna Wundervald (2024) and Dr. Mark O’Connell (2017). She also collaborates with researchers across disciplines, including Dr. Nadim Akasheh in food hypersensitivity studies.

• Theoretical Chemistry
• Electrochemistry
• Catalysis
• +6 more

Christopher J. Stein is an Associate Professor of Theoretical Chemistry at the Technical University of Munich (TUM), part of the TUM School of Natural Sciences. His research focuses on theoretical (electro-)catalysis, developing electronic-structure models and solvation/embedding methods to understand and optimize catalytic processes. He leads the Stein Group, which integrates computational chemistry with high-throughput simulations to advance energy materials and battery technologies. His work emphasizes realistic modeling of catalyst behavior under operational conditions and has contributed to advancements in quantum embedding and automated reaction mechanism exploration. Education and Career: Earned his PhD in Theoretical Chemistry, with postdoctoral research at Caltech (2017-2020). Became an Associate Professor at TU Munich in 2023. He previously held roles at Karlsruhe Institute of Technology and contributed to projects like the BIG-MAP Materials Acceleration Platform. Research Interests: Theoretical chemistry, electrochemical interfaces, battery materials, high-throughput computational methods, and machine learning integration. His group explores topics like solid electrolyte interphases, charge transfer mechanisms, and automated workflows for materials discovery. Awards: While no explicit awards are listed, his contributions to materials acceleration platforms and theoretical catalysis have been widely recognized in the field. His work has been featured in journals like Journal of Chemical Physics , Chemical Science , and Angewandte Chemie . Labs/Teams: Leads the Stein Group at TUM, collaborating with institutions like the Munich Data Science Institute and MIRMI. His lab focuses on computational tools for accelerating energy material development, including quantum embedding and cloud-based simulations.