جستجوی استاد راهنمای دانشگاهی

Howard A. Stone is the Donald R. Dixon '69 and Elizabeth W. Dixon Professor and Neil A. Omenn '68 University Professor in the Department of Mechanical and Aerospace Engineering at Princeton University's School of Engineering and Applied Science. He leads the Complex Fluids Group, conducting interdisciplinary research at the intersection of engineering, physics, chemistry, and biology. Dr. Stone received his B.S. in Chemical Engineering from UC Davis (1982) and Ph.D. from Caltech (1988). After a postdoctoral year at Cambridge University, he joined Harvard University's faculty in 1989, where he became the Vicky Joseph Professor of Engineering and Applied Mathematics before moving to Princeton in 2009. His research focuses on fluid dynamics phenomena across multiple scales, with particular emphasis on microfluidics, complex fluids, and biomechanics . His group investigates multiphase flows, colloidal systems, bio-inspired fluid phenomena, and physicochemical hydrodynamics. Recent work spans from fundamental studies of thin film drainage and droplet dynamics to applications in biological systems including blood flow, bacterial transport, and biomolecular condensates. The Complex Fluids Group employs experimental, theoretical, and computational approaches, often collaborating with industry partners on applications from medical devices to industrial processes. Analysis of his recent publications reveals a continued expansion into biological applications of fluid dynamics, with increasing focus on cellular mechanics, biomolecular condensates, and pathological hemodynamics, while maintaining strong contributions to fundamental fluid mechanics in complex systems. His work consistently bridges theoretical insights with practical applications across multiple disciplines. Major honors include: Election to the National Academy of Engineering (2009) Election to the National Academy of Sciences (2014) APS Fluid Dynamics Prize (2016) G.K. Batchelor Prize in Fluid Dynamics (2008) NSF Presidential Young Investigator Award Professor Stone has advised numerous PhD students through their Final Public Oral examinations, with recent graduates working on topics spanning microfluidics, bacterial transport, and complex fluid phenomena. His research has been supported by diverse funding sources including NSF, NIH, and industry partnerships. The Complex Fluids Group maintains state-of-the-art experimental facilities in the Engineering Quadrangle, featuring specialized equipment for microfluidics, rheology, and interfacial phenomena investigations. The group actively collaborates with researchers across Princeton and globally, maintaining strong connections to both academic and industrial partners working on fluid-related challenges.

• Fluid Dynamics
• Microfluidics
• Complex Fluids
• +۷ مورد دیگر

Daniel Finley is a Professor of Cell Biology at Harvard Medical School (HMS), leading the Finley Lab focused on the ubiquitin-proteasome pathway and related regulatory mechanisms. He holds academic appointments within the Department of Cell Biology and sits on the Scientific Advisory Boards of Proteostasis and X-Chem Pharmaceuticals. His research investigates proteasome function, ubiquitin-like proteins, and proteostasis roles in diseases like Alzheimer’s and ALS. Dr. Finley earned his undergraduate degree in biochemistry from Harvard University and a Ph.D. in molecular biology from MIT. After postdoctoral training at MIT, he joined HMS in 1988. His lab explores topics including erythroid proteome remodeling, mitochondrial dysfunction, and neurodegenerative disease mechanisms. Key research areas include: (1) Ubiquitin-proteasome pathway regulation, (2) Proteasome structure/function, (3) Nonproteolytic roles of ubiquitination, and (4) Pathophysiological roles of proteostasis defects in diseases. His work bridges basic cell biology with translational medicine, particularly in neurodegeneration and anemia. Finley has secured NIH funding for projects like 'Regulation of Proteasome Activity' (R35GM145246) and 'Erythrocyte maturation through global proteome remodeling' (R01HL153970). Collaborations with industry and academic partners extend his impact in drug discovery and proteasome-targeted therapies. His lab’s contributions include defining ubiquitin chain editing mechanisms, identifying USP14’s role in mitophagy, and elucidating proteostasis defects in Alzheimer's models. Research tools developed include advanced cryo-EM analyses of proteasomal structures and functional assays for ubiquitin system enzymes.

• Ubiquitin-Proteasome Pathway
• Proteostasis
• Protein Degradation
• +۷ مورد دیگر

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 .

• Genomics
• Machine Learning
• Computational Biology
• +۳ مورد دیگر

James B. Kaper is a Professor and Chair of the Department of Microbiology & Immunology at the University of Maryland School of Medicine. He serves as Vice Dean for Academic Affairs and previously held leadership roles as Senior Associate Dean (2014–2019) and Chair (2007–present). His research focuses on the molecular pathogenesis of diarrheagenic Escherichia coli and Vibrio cholerae , including vaccine development and bacterial-host interactions. Education: BS (1973) and PhD (1979) in Microbiology from University of Maryland; Postdoc in Molecular Pathogenesis at University of Washington (1979–1981) Dr. Kaper’s work has led to the creation of live attenuated cholera vaccines, including CVD 103-HgR, the first licensed recombinant bacterial vaccine. His lab investigates bacterial genetics, intestinal colonization, and immune system activation, particularly TLR5 response to V. cholerae flagellin. He has authored 303 peer-reviewed articles and 68 book chapters. His research has been funded continuously by NIAID since 1982. Key publications include foundational work on V. cholerae vaccines (1984), genomic structure (1998), and quorum sensing in EHEC/EPEC (1999). His lab’s recent studies focus on phosphotyrosine proteomics (2013) and pathogenicity island regulation (2007). Scientific awards: Fellow, American Academy of Microbiology (1994); NIH Merit Award (2004); ASM DC White Award (2019) Editorial roles: Editor-in-Chief, EcoSal (2006–present); Associate Editor, International Journal of Medical Microbiology (2000–present) As an academic leader, Dr. Kaper has mentored over 60 graduate students and postdoctoral fellows. He holds multiple patents for cholera vaccines and E. coli diagnostics, including U.S. Patents 4,935,364; 5,399,494; and 6,204,004. His lab at UMSOM combines basic science with translational applications for enteric disease prevention.

• Microbiology
• Immunology
• Bacterial Vaccines
• +۵ مورد دیگر

Dr. Giulia Biancon is an Assistant Professor Adjunct in the Department of Medical Oncology and Hematology at Yale School of Medicine. She holds a PhD from the University of Milan (2019) and is a member of the Halene Lab, focusing on RNA biology and hematologic malignancies. Her research combines high-throughput methodologies to study RNA mechanisms in diseases like myeloid leukemias and splicing factor mutations. Education: PhD in Molecular Biology from the University of Milan (2019). Research Interests: RNA splicing, stress granules in cancer, epitranscriptomics, clonal hematopoiesis, and the interplay between genetic mutations and cellular pathways in blood cancers. Awards: 2024 Eclipse Award, 2022 ASH Abstract Achievement Award, and 2022 RNA Society Best Poster Award. Her work has been published in journals like Cell Reports , Blood , and Molecular Cell . Labs/Teams: Principal member of the Halene Lab and coordinator at the Yale Center for RNA Science and Medicine. Collaborates with institutions like the SeroNet network for immunology studies.

• RNA Biology
• Myeloid Malignancies
• Hematology
• +۴ مورد دیگر

Hyunghoon Cho is an Assistant Professor at Yale School of Medicine in the Department of Biomedical Informatics & Data Science, with a secondary appointment in the Department of Computer Science. He received his PhD in Electrical Engineering and Computer Science from MIT (2019) and MS/BS in Computer Science from Stanford University (2013). His research focuses on computational challenges in biomedical data privacy, single-cell genomics, and network biology. Assistant Professor (Primary): Biomedical Informatics & Data Science Assistant Professor (Secondary): Computer Science Appointments: Yale School of Medicine | Broad Institute (Schmidt Fellow) Research Themes: Privacy-Enhancing Technologies for genomic and health data Scalable AI/ML tools for omics data analysis Structured biological modeling for system-level discovery His work includes secure GWAS, transcriptomic privacy assessment, and sfkit - a federated genomic analysis toolkit. He received the NIH Director's Early Independence Award and leads NSF-funded projects on confidential genome analytics. Awards: NIH Director's Early Independence Award Lab Members: Haris Smajlović (Postdoc), Vincent Angelo (CBB MS), Denis Loginov (Senior Software Engineer), Lucy Zheng (CBB PhD)

• Biomedical Data Privacy
• Genomics
• Machine Learning
• +۳ مورد دیگر

Shasha Chong is an Assistant Professor of Chemistry at the California Institute of Technology and a Ronald and JoAnne Willens Scholar. She earned her B.S. from the University of Science & Technology of China (2008) and Ph.D. from Harvard University (2014). Her research bridges chemistry, physics, and biology to investigate the molecular mechanisms of cellular processes, focusing on intrinsically disordered regions (IDRs) in transcription proteins. Research Focus: IDRs in transcriptional regulation, cancer biology, liquid-liquid phase separation, and single-molecule imaging techniques. Grants & Awards: CCE Innovation Award (2024), ALSF Innovation Grant, Mallinckrodt Research Grant, Margaret E. Early Medical Research Trust Grant. Collaborations: Caltech-City of Hope Biomedical Research Initiative Grant (2025). Teaching: Co-instructor for courses like Biochemistry Laboratory (Ch 11) and Advanced Topics in Biochemistry (BMB/Bi/Ch 174). Labs & Teams: Leads the Chong Laboratory at Caltech, focusing on interdisciplinary approaches combining single-molecule imaging, genome editing, and bioinformatics.

• Transcriptional Regulation
• Intrinsically Disordered Proteins
• Single-Molecule Biophysics
• +۴ مورد دیگر

John Paisley is an Associate Professor of Electrical Engineering at Columbia University's Fu Foundation School of Engineering and Applied Science, and a member of Columbia's Data Science Institute (DSI). He holds a B.S., M.S., and Ph.D. in Electrical and Computer Engineering from Duke University (2004-2010), followed by postdoctoral research in Computer Science at Princeton University and UC Berkeley. His research focuses on Bayesian models, posterior inference techniques for Big Data, and applications in data analysis, recommendation systems, information retrieval, and compressed sensing. He has pioneered methods like Bayesian Gaussian Process ODEs and Double Normalizing Flows, with recent work emphasizing uncertainty quantification in environmental modeling and neuroimaging analysis. His collaborative workflows (e.g., bneR ) address air pollution exposure and PM2.5 concentration uncertainties, combining Bayesian nonparametric ensembles with geospatial data. He has also developed frameworks for neural network interpretability, image denoising, and compressed sensing MRI. Paisley's work bridges statistical theory and applied machine learning, with applications in healthcare, environmental science, and geophysics. His academic contributions include over 50 publications since 2016, spanning topics like deep metric learning, adversarial learning, and variational inference optimization. He maintains an active research group and serves on editorial boards for machine learning and signal processing journals.

• Machine Learning
• Bayesian Statistics
• Data Science
• +۳ مورد دیگر

Britt Adamson is an Associate Professor in the Department of Molecular Biology and the Lewis-Sigler Institute for Integrative Genomics at Princeton University, where she serves as Director of the Undergraduate Program in Quantitative and Computational Biology. Her lab investigates molecular networks in human cells with focus on stress response mechanisms and genome editing technologies. She received her B.S. in Biology from the Massachusetts Institute of Technology (2005) and Ph.D. in Genetics and Genomics from Harvard University (2012), followed by postdoctoral training at UCSF under Jonathan Weissman supported by a Damon Runyon Cancer Research Foundation Fellowship. Adamson's research centers on how cells organize stress response networks during DNA damage and endoplasmic reticulum stress, developing CRISPR-based functional genomics and single-cell sequencing tools to map molecular behaviors. Her work bridges fundamental cell biology with therapeutic applications in genome editing. Analysis of her 15 most recent publications reveals dominant themes in precision genome editing (prime/base editing optimization) and systematic dissection of DNA repair pathways through combinatorial CRISPR screening. Her lab consistently integrates computational approaches with high-resolution experimental techniques to uncover context-dependent cellular behaviors. Her scientific recognitions include: Damon Runyon Cancer Research Foundation Postdoctoral Fellowship Princeton IP Accelerator Award (2025) STAT Who to Know: 10 Scientists leading a new generation of gene editors (2024) Adamson actively mentors eight graduate students (including alumni Ann Cirincione and Jun Hussmann) and two postdocs, with research funded through institutional awards and collaborative grants. Her lab's technological developments have enabled projects spanning virology, immunology, and developmental biology. The Adamson Lab operates within Princeton's Lewis-Sigler Institute for Integrative Genomics, fostering an interdisciplinary environment that merges cell biology, genomics, and computational science. Current projects focus on improving prime editing efficiency and understanding stress response adaptation in disease contexts.

• Stress Response Networks
• DNA Damage Response
• Genome Editing
• +۳ مورد دیگر

Anirban Paul is an Associate Professor in the Department of Neuroscience and Experimental Therapeutics at Pennsylvania State University, affiliated with the Penn State Neuroscience Institute. His research focuses on cellular and molecular mechanisms of GABAergic inhibitory circuits, with particular emphasis on interneuron biology and its implications in neurological disorders. Dr. Paul's research spans multiple neuroscience domains, with primary focus on GABAergic inhibitory circuits and interneuron biology. His work investigates how specific neuron subtypes, particularly Chandelier cells and cortical interneurons, contribute to brain function and dysfunction. He has made significant contributions to understanding the role of these cells in schizophrenia, Alzheimer's disease, and other neurological conditions. His research integrates molecular, cellular, and systems-level approaches to uncover fundamental mechanisms of neural circuit assembly, plasticity, and function. Key areas include RNA regulation in neuronal development, transcriptomic subtypes of inhibitory neurons, and cell-type specific vulnerabilities in neurodegenerative diseases. His research portfolio demonstrates consistent productivity with publications spanning from 2003 to 2025, showing an evolving focus from basic molecular neuroscience to translational research in neurological disorders. Recent work emphasizes single-cell analysis techniques and the role of specific interneuron populations in disease mechanisms, particularly in schizophrenia and Alzheimer's disease. His publications appear in high-impact neuroscience journals including Neuron, BMC Biology, and Frontiers in Cellular Neuroscience. Dr. Paul has received the NARSAD Young Investigator Award (2018), recognizing his promising research in neuroscience. His scientific contributions have been supported by multiple competitive grants from prestigious organizations including the National Institute on Aging (NIA) and the Brain and Behavior Research Foundation. He serves as Principal Investigator on multiple active research projects, including two major grants from the National Institute on Aging focused on cell-type specific risk and resilience in Alzheimer's disease and aging (2021-2024 and 2024-2026), as well as previous projects from the Brain and Behavior Research Foundation investigating Chandelier cells in schizophrenia. His research program demonstrates sustained funding and scientific leadership in the field of interneuron biology and its clinical implications.

• Neuroscience
• GABAergic inhibitory circuits
• Interneuron biology
• +۵ مورد دیگر

David R. Koes is an Associate Professor in the Department of Computational and Systems Biology at the University of Pittsburgh, affiliated with the School of Medicine. He holds roles such as Associate Director of the Joint CMU-Pitt Computational Biology PhD Program (CPCB) and is involved in multiple graduate programs including Intelligent Systems and Computational Biomedicine. His research focuses on developing computational algorithms and systems for drug discovery, emphasizing open-source software and machine learning applications in biomedical data. Koes teaches courses like MSCBIO2025 (Bioinformatics Programming in Python) and MSCBIO2065 (Scalable Machine Learning for Big Data Biology). He has secured NIH funding (R35GM140753) and collaborated on projects with institutions like NVIDIA and Google Cloud. His lab develops tools such as GNINA, Pharmit, and 3Dmol.js, and actively contributes to open drug discovery initiatives. Education: PhD in Computer Science from Carnegie Mellon University (CMU). Research Interests: Leveraging computation and AI for drug design, molecular docking, pharmacophore modeling, and open science. Specific areas include developing scalable machine learning pipelines, virtual screening systems, and tools for 3D molecular analysis. Grants and Funding: Current NIH R35 grant and prior support from NSF, Relay Therapeutics, and others. His work emphasizes translating computational methods into practical drug discovery solutions. Lab and Teams: Directs a lab focused on computational drug discovery, collaborating with multiple academic and industry partners. Supervises graduate students and postdocs in projects spanning AI-driven drug design, molecular modeling, and software development.

• Computational Drug Discovery
• Machine Learning in Biology
• Open Source Software
• +۳ مورد دیگر

Emma Pierson is an Assistant Professor of Computer Science at the University of California, Berkeley, affiliated with the Berkeley Artificial Intelligence Research Lab (BAIR) , Computational Precision Health , and the Center for Human-Compatible AI . She focuses on developing data science and machine learning methods to address issues in healthcare equity and social inequality . Her work includes studies on race adjustments in clinical algorithms, migration patterns, and leveraging LLMs for health equity. Education: Ph.D. in Computer Science from Stanford University (2020), Master’s in Statistics from the University of Oxford. Prior roles include Assistant Professor at Cornell Tech, Senior Researcher at Microsoft Research, and data scientist at 23andMe and Coursera. Research Interests: Her research spans fair clinical prediction , sparse autoencoders , health disparities , and algorithmic fairness . Notable projects include the MIGRATE dataset for granular migration analysis and studies on policing disparities. Awards: NSF CAREER Award, Rhodes Scholarship, Hertz Fellowship, MIT Technology Review 35 Innovators Under 35, and Samsung AI Researcher of the Year. She writes a statistics blog ( Obsession with Regression ) and contributes to media outlets like The New York Times and FiveThirtyEight . Labs/Teams: Leads the MIGRATE project, a collaboration to analyze fine-grained migration data. Engages in interdisciplinary work across AI, healthcare, and social science.

• Artificial Intelligence
• Healthcare
• Health Equity
• +۳ مورد دیگر

Michele Klingbeil is a Professor in the Department of Microbiology at the University of Massachusetts Amherst, where she leads the Klingbeil DNA Replication Laboratory. She received her PhD in Cell and Molecular Biology from the University of Toledo in 1996 and previously worked at Johns Hopkins School of Medicine before moving to UMass in July 2007. Her educational background includes: PhD in Cell and Molecular Biology, University of Toledo, 1996 Dr. Klingbeil's research focuses on the unique biology of trypanosomatid parasites, particularly Trypanosoma brucei , the causative agent of African sleeping sickness. Her laboratory investigates two main areas: (1) replication of the unusual mitochondrial DNA network called kinetoplast DNA (kDNA), and (2) nuclear DNA replication initiation. Her work on kDNA is particularly significant as this structure is essential for parasite survival but has no counterpart in mammalian hosts, making it an attractive drug target. She employs a combination of reverse genetics (RNAi), cell biology, and biochemistry to understand the replication and repair mechanisms of kDNA, with a special focus on a family of four DNA polymerases related to bacterial Pol I. Dr. Klingbeil's recent publications reveal her laboratory's deep investigation into mitochondrial DNA polymerases in trypanosomatids, with discoveries showing multiple polymerases having specialized functions in kDNA replication and repair. Her research has established that several of these polymerases are essential for parasite viability, opening new avenues for drug development. She has also made significant contributions to understanding the simplified Origin Recognition Complex in trypanosomatids compared to other eukaryotes. Dr. Klingbeil has received the Thomas G. Lessie Distinguished Lectureship Award for her impact on teaching at the graduate level. Her research is funded by the National Institutes of Health, U.S. Department of Agriculture, the Joeph P. Healey Endowment, and the University of Massachusetts Amherst. She has mentored numerous graduate and undergraduate students, including current PhD candidates Dave Bruhn, Jeniffer Concepción, and Juemin Luo, as well as visiting scholar Eva Vidal Rico. Her former students have gone on to positions at institutions including Dana Farber/Broad Institute, Regis College, and Flagship Ventures. The laboratory regularly participates in scientific conferences including the Molecular Parasitology Meeting at Woods Hole and the Kinetoplastid Molecular Cell Biology conference. Dr. Klingbeil teaches several courses including Parasitology (MICRO 590S), Parasitology Lab (MICRO 590L), Molecular Mechanisms of Pathogenesis (MICRO 797P), Advanced Cell Biology (MCB 641), and Writing in Microbiology (MICRO 360). Her laboratory organizes regular social events including pumpkin carving parties and outings to Six Flags New England and Mt. Sugarloaf.

• Parasitology
• Molecular Biology
• Microbiology
• +۴ مورد دیگر

Daiwei (David) Zhang, PhD, is an Assistant Professor (tenure-track) in the Department of Biostatistics at the University of North Carolina at Chapel Hill School of Medicine, with a joint appointment in the Department of Genetics. His research focuses on developing AI frameworks for analyzing high-dimensional biomedical data, particularly in spatial omics, computational pathology, and medical imaging. Education: MS (Biostatistics) and PhD (Biostatistics and Scientific Computing) from the University of Michigan. Postdoctoral Training: University of Pennsylvania. Research interests include applying machine learning to address biomedical challenges such as tumor heterogeneity, immune interactions, and tissue architecture. His work spans computational methods for spatial transcriptomics, proteomics, and histology integration. Recent publications emphasize spatial multi-omics analysis of cancer ecosystems, tertiary lymphoid structures, and metabolic coordination. These studies leverage advanced machine learning algorithms and interdisciplinary approaches to advance precision medicine. No scientific awards are explicitly mentioned, but his work reflects significant contributions to biomedical AI research. Grants and advising details are not provided in the text.

• Artificial Intelligence
• Machine Learning
• Spatial Omics
• +۳ مورد دیگر

Weiqiang Chen is a Professor of Mechanical and Biomedical Engineering at New York University's Tandon School of Engineering and Director of Research and PhD Programs. He holds a joint appointment at NYU Langone's Perlmutter Cancer Center as a Faculty Member of the Tumor Immunology Research Program. B.S. in Physics (Nanjing University, 2005) M.S. in Electrical Engineering (Shanghai Jiao Tong University, 2008) M.S. in Electrical and Computer Engineering (Purdue University, 2009) Ph.D. in Mechanical Engineering (University of Michigan, 2014) His research focuses on Lab-on-a-Chip , Organ-on-Chip systems, Biomaterials , and Mechanobiology , with applications in cancer biology, stem cell engineering, and immune monitoring. He pioneers microfabrication technologies for real-time observation of cellular interactions, including CAR T-cell immunotherapy efficacy and tumor microenvironment dynamics. Recent grants include NSF funding for leukemia bone marrow niche modeling, NIH Trailblazer Awards for glioblastoma immunotherapy research, and collaborations with the Arthritis Foundation for synovium-on-chip rheumatoid arthritis studies. His work has been supported by over $2M in federal and institutional research funding. National Science Foundation (NSF) grants for leukemia-on-chip and glioblastoma modeling National Institutes of Health (NIH) awards for immunotherapy research American Heart Association fellowships and institutional training programs Chen's scientific awards include the American Heart Association Fellow distinction, multiple Young Investigator Awards from Lab on a Chip and Biomedical Engineering Society, and recognition for his dissertation on nanotopography in stem cell differentiation. He leads the Applied Micro-Bioengineering Laboratory (AMBL) , which develops microphysiological systems for drug testing and personalized medicine. His team has created the first immunocompetent leukemia-on-a-chip for CAR T-cell therapy screening and glioblastoma models that enable patient-specific immunotherapy validation.

• Lab-on-a-Chip
• Organ-on-Chip
• Biomaterials
• +۷ مورد دیگر