جستجوی استاد راهنمای دانشگاهی

Qianwen Wang is a tenure-track Assistant Professor in the Computer Science department at the University of Minnesota, Twin Cities. Her research combines interactive visualization with interpretable machine learning to foster intuitive, efficient, and reliable Human-AI collaboration. She actively seeks motivated students, research assistants, and interns to join her dynamic research team at UMN CS. Dr. Wang's research focuses on three primary themes: Human-AI Collaboration, where she designs tools to facilitate Human-AI interaction; Automatic & Intelligent Visualization, where she develops techniques to make visualizations accurately interpreted and easily used; and VIS+(X)AI in Biomed/Healthcare, where she studies how visualization and explainable AI can promote scientific discoveries in biomedicine and healthcare. Her work has made significant contributions to visualization, human-computer interaction, and bioinformatics, with particular applications in biomedical knowledge graphs and single-cell omics analysis. Her recent publications demonstrate a strong trend toward integrating visualization with large language models and graph neural networks for biomedical applications. She has published extensively at top venues including IEEE VIS, ACM CHI, and Nature Medicine, with a focus on making AI systems more interpretable and useful for domain experts, particularly in healthcare contexts. Her work often bridges theoretical advances in visualization with practical applications in genomics and healthcare. Two IEEE VIS Honorable Mention Awards (2022, 2024) Best Paper Award from IMLH@ICML 2021 Two Best Abstract Awards from BioVis ISMB (2021, 2022) HDSI Postdoctoral Research Fund Award Research covered by MIT News and Nature Technology Features Dr. Wang actively contributes to the academic community through service roles including General Chair for ISMB BioVis, VisNotes and Poster Chair for IEEE PacificVis, and Program Committee member for IEEE VIS, ACM CHI, and ACM IUI. Her research has been supported by various grants that enable her team to develop innovative visualization techniques and explore their practical applications in biomedical domains. Her research group maintains an active presence in the visualization and HCI communities, with members participating in major conferences and workshops. The lab focuses on creating tools that bridge the gap between complex AI models and human understanding, with particular emphasis on making these technologies accessible and useful for domain experts in biomedical research.

• Interactive Visualization
• Interpretable Machine Learning
• Human-AI Collaboration
• +۵ مورد دیگر

Professor Mark Coles serves as Professor of Immunology and Lead for Industrial Strategy and Entrepreneurship at the Kennedy Institute of Rheumatology, University of Oxford, holding concurrent roles as Kennedy Trust Senior Research Fellow, Official Fellow at Reuben College, and Affiliate Faculty at the Wolfson Centre of Mathematical Biology. His interdisciplinary work bridges immunology, computational modeling, and translational research to accelerate therapies for immune-mediated inflammatory diseases. His academic journey began with a BSc in Microbiology from Cornell University (1992), followed by a PhD in Molecular and Cell Biology at UC Berkeley under David Raulet, and postdoctoral training with Dimitris Kioussis at the National Institute of Medical Research. At the University of York (2006-2017), he pioneered stromal immunology research and co-founded the York Computational Immunology Laboratory. Coles' research centers on stromal and systems immunology, with core expertise in stromal cell biology, inflammatory disease mechanisms, and mathematical modeling of immune responses. He champions 3Rs-based approaches (Replacement, Reduction, Refinement) to reduce animal testing through in silico models, integrating spatial single-cell biology with multi-scale computational frameworks to dissect immune function in human tissues. His 2025 publications reveal a cohesive research trajectory applying interdisciplinary methods across diverse disease contexts—from cardiac fibrosis and vaccine responses to arthritis pathogenesis and CAR-T cell therapy—unified by focus on stromal-immune crosstalk and quantitative modeling to identify therapeutic targets. Key honors include: Fellow of the Royal Society of Biology Kennedy Trust Senior Research Fellow As former Director of Graduate Studies (2017-2024) at the Kennedy Institute, Coles mentored numerous graduate students while co-leading major initiatives including the Arthritis Therapy Acceleration Program and Human Cell Atlas medicalization. His entrepreneurial impact spans three co-founded ventures: Simomics Ltd (in silico disease modeling), Lightox Ltd (phototherapy for oral cancer), and Mestag Therapeutics (fibroblast-targeted therapies for cancer/inflammation). He directs the Laboratory of Stromal and Systems Immunology and Oxford Mathematical Immunology Group, fostering collaborations with Christopher Buckley, Calliope Dendrou, and Eamonn Gaffney to develop Quantitative Systems Pharmacology models that translate mechanistic insights into patient therapies.

• Immunology
• Translational Immunology
• Computational Immunology
• +۴ مورد دیگر

Owen R. White is a Professor in the Department of Epidemiology & Public Health at the University of Maryland School of Medicine, serving as Associate Director of the Institute for Genome Sciences and Associate Director of Research Collaboration & Development. He leads a team of 25 scientists and engineers developing genomic annotation pipelines and data analysis tools for state-of-the-art research in microbiome and multi-omic studies. His academic background includes: BS in Biotechnology from the University of Massachusetts (1985) PhD in Molecular Biology from New Mexico State University (1992) Postdoctoral Fellowship in Genome Informatics at the Institute for Genomic Research (TIGR) (1994) Dr. White's research spans bioinformatics, genomics, transcriptomics, and metagenomics with emphasis on data management, metadata standards, ontologies, and cloud systems. His work has been foundational for large-scale initiatives like the Human Microbiome Project (HMP) and Integrative Human Microbiome Project (iHMP), generating over 50,000 datasets totaling 10 terabytes of multi-omic data. Analysis of his recent publications reveals a strong trend toward neuroscience multi-omics (BRAIN Initiative), cloud-based data infrastructure, and ethical data sharing frameworks. His work consistently bridges microbiome research with emerging fields like single-cell analysis and Alzheimer's disease biomarker discovery through integrated data platforms. Notable awards include: Benjamin Franklin Award for Open Access in the Life Sciences (2015) Kumho Science International Award in Plant Molecular Biology and Biotechnology (2001) As Principal Investigator for major NIH-funded centers, he has secured sustained support for the HMP Data Analysis and Coordination Center and iHMP Data Coordination Center. His team's work combines fee-for-service models with collaborative research funding to maintain cutting-edge genomic analysis capabilities. The Institute for Genome Sciences houses his computational team responsible for developing production annotation pipelines, database systems, and visualization tools that serve researchers across the University of Maryland School of Medicine and national consortia.

• Bioinformatics
• Genomics
• Transcriptomics
• +۶ مورد دیگر

Long Cai is a Professor at the California Institute of Technology, affiliated with the Biology and Biological Engineering department. He pioneered the field of spatial genomics and co-developed transformative technologies such as seqFISH and MEMOIR. Research Interests: His work focuses on decoding biological systems through spatial genomics, integrating molecular imaging with computational analysis to uncover cellular organization in tissues. Key areas include developmental biology, neuroscience, kidney regeneration, and cancer biology. Publications: Recent studies highlight applications of spatial transcriptomics in kidney disease, brain nuclear architecture, and multi-omics tissue mapping. His research emphasizes creating high-resolution atlases of cellular dynamics. Scientific Awards: NIH Director’s Pioneer Award (2022) Labs & Collaborations: He leads the Cai Lab, which develops cutting-edge imaging tools in collaboration with the Elowitz Lab and other interdisciplinary teams.

• Spatial Genomics
• Cellular Biology
• Developmental Biology
• +۴ مورد دیگر

Omer Bayraktar is a Group Leader at the Wellcome Sanger Institute , leading research in the Cellular Genomics Programme. His work focuses on decoding human brain cellular diversity using spatial transcriptomics , imaging , and functional screening to study neural complexity in health and disease. Bayraktar's educational background includes a PhD from HHMI under Chris Doe, investigating neural diversity development in Drosophila , followed by postdoctoral work at University of California, San Francisco and University of Cambridge as a Life Sciences Research Foundation Fellow. He developed a spatial transcriptomic pipeline during his postdoc to analyze astrocyte heterogeneity in the cerebral cortex. His research explores neural cell type mapping , glial-neuronal interactions , and cellular pathways in neurodevelopmental disorders . Recent publications emphasize 3D tissue mapping , multi-omic integration , and computational tools like Cell2fate and WebAtlas. His work bridges neurogenetics and computational biology to advance understanding of human tissue ecosystems. Bayraktar's lab collaborates with the Human Cell Atlas initiative and develops technologies such as automated histology pipelines and highly-multiplexed smFISH for molecular cell typing. His team also investigates glia-based therapies and astrocyte functional heterogeneity in neurodevelopmental contexts. Key scientific contributions include: Discovering astrocyte layer patterns independent of neuronal laminae Developing cell2location for spatial cell mapping Characterizing Drosophila neural stem cell models with human relevance Notable awards include the Life Sciences Research Foundation Fellowship during his postdoctoral training. His current group includes a PhD student , Senior Data Scientists , and Bioinformaticians .

• Neural Diversity
• Spatial Transcriptomics
• Glia Biology
• +۳ مورد دیگر

Brian Hie is an Assistant Professor of Chemical Engineering at Stanford University , a Dieter Schwarz Foundation Stanford Data Science Faculty Fellow , and an Innovation Investigator at Arc Institute . He leads the Laboratory of Evolutionary Design , focusing on the intersection of biology and machine learning . His prior roles include a Stanford Science Fellow in the Stanford University School of Medicine and a Visiting Researcher at Meta AI . Education: Ph.D. , Electrical Engineering and Computer Science , Massachusetts Institute of Technology (2021) Bachelor’s Degree , Stanford University Research Interests: Brian’s work bridges machine learning and computational biology , with a focus on protein engineering , single-cell RNA sequencing , and viral evolution . His Evolutionary velocity framework predicts protein evolutionary dynamics across timescales, while his Scanorama algorithm enables efficient integration of heterogeneous single-cell datasets. He also develops structure-informed language models for antibody optimization and uncertainty-aware ML for biological discovery. Publication Trends: His recent work (2023) emphasizes structure-based inverse folding for antibody evolution, evolutionary scale modeling , and unsupervised optimization . Earlier studies (2022-2021) cover evolutionary velocity , multi-modal single-cell analysis , and viral escape prediction using natural language analogies. Scientific Awards: Stanford Science Fellow (2021) National Defense Science and Engineering Graduate Fellowship (2019) Advising: He mentors doctoral students including Brandon Ameglio , Garyk Brixi , and Chang M. Yun , with a focus on biological design and computational methods . Labs & Collaborations: His lab collaborates with Bio-X and the Institute for Human-Centered Artificial Intelligence (HAI) , and he maintains affiliations with Sarafan ChEM-H and Stanford Data Science .

• Machine Learning
• Computational Biology
• Protein Engineering
• +۶ مورد دیگر

Giorgio Ascoli is a University Professor in the Department of Bioengineering at George Mason University, where he has been since 1997. He is the Founding Director of the Center for Neural Informatics, Structures, & Plasticity (CN3) and Founding Editor-in-Chief of the journal Neuroinformatics . His affiliations span computational neuroanatomy, neuroinformatics, and hippocampal modeling. Education : PhD in Biochemistry and Neuroscience (1996), Scuola Normale Superiore; MS in Chemistry and Biochemistry (1993), Pisa University; BS in Chemistry and Physics (1991), Scuola Normale Superiore. Dr. Ascoli investigates the relationship between brain structure, activity, and function from cellular to circuit levels. His research focuses on anatomically plausible neural networks to model mammalian brains, particularly the hippocampus, with implications for understanding human memory and consciousness . He pioneered computational neuroanatomy, developing tools like L-Neuron for neuronal shape modeling and curating NeuroMorpho.Org , a central repository for digitally reconstructed neurons. His recent publications emphasize neuronal classification , connectome analysis , and biologically informed machine learning . Awards include the 2012 Outstanding Faculty Award (Virginia), 2022 AIMBE fellowship , and 2023 Presidential Faculty Excellence Awards . He has mentored over 20 graduate students and postdoctoral fellows, with funding from NIH, NSF, DARPA, and private foundations. Scientific Contributions : Over 137 peer-reviewed articles, 4 patents, 2 authored/edited books, and leadership in NeuroMorpho.Org and Hippocampome. Grants : $20M+ in cumulative funding, including NIH R01s, NSF BRAIN EAGERs, and Burroughs-Wellcome Trust support. Labs : Leads the Computational Neuroanatomy Group within CN3, focusing on hippocampal modeling, neuronal morphology, and consciousness theories.

• Computational Neuroanatomy
• Neuroinformatics
• Neuronal Morphology
• +۵ مورد دیگر

Kep Kee Loh is a Senior Tutor in the Department of Psychology at the National University of Singapore (NUS). Currently, he also holds an NUS Overseas Postdoctoral Fellowship position at both the Montreal Neurological Institute (McGill University) and the University of Oxford. His research focuses on comparative primate neuroanatomy, examining what makes the human brain special compared to other primates through multimodal MRI techniques. Ph.D. in Neuroscience from Université Claude Bernard Lyon I (2014-2018) M.Sc. in Cognitive Neuroscience from University College London (2011-2012) B.Soc.Sci. (Hons.) in Psychology from National University of Singapore (2007-2011) Dr. Loh's research primarily investigates the anatomical organization of brains across humans and various primate species including chimpanzees, baboons, and macaques. He employs different magnetic resonance imaging techniques (anatomical, resting-state, diffusion-weighted MRI) to compare brain organization across species, with particular focus on the medial frontal cortex, sulcal anatomy, and the evolution of speech and language in the human brain. His work adopts a multimodal approach to provide an integrative view of what sets human brains apart from other primates. His recent publications demonstrate a strong focus on comparative neuroanatomy across species, with particular emphasis on primate brain evolution, frontal cortex organization, and language-related neural pathways. The research spans multiple disciplines including neuroscience, cognitive science, and evolutionary biology, with increasing attention to methodological advancements in neuroimaging techniques for cross-species comparisons. NUS Overseas Postdoctoral Fellowship (2021) Institute of Language, Communications and the Brain (ILCB) Postdoctoral Fellowship (2019) Fondation Recherche Médicale (FRM) Fin de Thèse (PhD funding) (2017) BRAIN Student Travel Award, 6th Motivation and Cognitive Control Symposium (2016) Dr. Loh has been involved in numerous collaborative research projects across international institutions, including the French Institute of Health and Medical Research (Stem Cell and Brain Research Institute), Aix-Marseille Université, and currently McGill University and the University of Oxford. His work has received significant recognition with over 1,000 citations for his 33 publications. While specific grant information isn't detailed in the provided text, his postdoctoral fellowships indicate successful competitive funding. Dr. Loh collaborates with several research groups including the Montreal Neurological Institute at McGill University and research teams at the University of Oxford. His work connects with broader initiatives like the collaborative resource platform for non-human primate neuroimaging, indicating participation in larger research networks focused on advancing primate neuroscience through shared resources and methodologies.

• Comparative primate neuroanatomy
• Sulcal anatomy
• Frontal cortex function
• +۴ مورد دیگر

Prashant Mali is a Professor in the Department of Bioengineering at the University of California, San Diego . His research bridges genome engineering, RNA biology, and biomedical applications, with a focus on CRISPR-Cas systems and ADAR-mediated RNA editing. Education : Ph.D. in Bioengineering Key Affiliations : UC San Diego, Altman Clinical and Translational Research Institute Dr. Mali's work centers on CRISPR-Cas9 technology , RNA editing , and human pluripotent stem cells . His lab develops tools for programmable gene regulation, synthetic lethal screens, and metabolic pathway analysis in disease contexts. Recent publications highlight innovations in circular RNA engineering , ADAR activity mapping , and metabolic reprogramming in cancer . His team employs multi-omics approaches and in vivo models to translate genome editing into clinical applications. Students and Collaborators Current Lab Members : Sami Nourreddine (Postdoc), Amir Dailamy (Graduate), Andrew Portell (Graduate), Michael Tong (Graduate) Alumni : Kyle Ford (PhD 2022), Nathan Palmer (PhD 2022), Udit Parekh (PhD 2021) Research Themes CRISPR Screens : Synthetic lethal interactions, oncogenic pathways, metabolic vulnerabilities RNA Editing : ADAR engineering, circular guide RNAs, clinical translation Tissue Engineering : Vascularized organoids, cardiac maturation, ex vivo models

• Genome Engineering
• RNA Editing
• Stem Cell Research
• +۴ مورد دیگر

Jonathan Weissman is a Professor of Biology at the Massachusetts Institute of Technology (MIT) and a Member of the Whitehead Institute. He is also an Investigator of the Howard Hughes Medical Institute and the Landon T. Clay Professor of Biology. His research spans protein folding mechanisms, ribosome profiling, CRISPR-based tools (CRISPRi/a), and genetic interaction mapping. Whitehead Institute Member MIT Professor HHMI Investigator Co-founder, Maze Therapeutics & KSQ Therapeutics Research Interests focus on: Protein folding in cellular contexts Endoplasmic reticulum (ER) function and stress responses Genome-wide CRISPR screening for gene regulation High-density genetic interaction maps in mammals Mitochondrial protein targeting and quality control Epigenomic engineering with synthetic tools Scientific Awards include: Protein Society Irving Sigal Young Investigator Award (2004) Raymond & Beverly Sackler Prize (2008) National Academy of Sciences election (2009) NAS Award for Scientific Discovery (2015) Genetics Society of America Ira Herskowitz Award (2020) Labs & Collaborations : Leads the Weissman Lab at MIT/Whitehead Institute, co-leads the Laboratory for Genomic Research with GlaxoSmithKline, and chairs the Stowers Institute Scientific Advisory Board.

• Protein Folding
• Systems Biology
• Genomics
• +۶ مورد دیگر

Prof. Markus Axer is a Professor and Deputy Head of the Structural and Functional Organisation of the Brain (INM-1) at the Institute of Neuroscience and Medicine (INM) within Forschungszentrum Jülich. His research focuses on connectomics, neuroimaging technologies (e.g., 3D-Polarized Light Imaging), and high-performance computing applications in brain architecture analysis. He leads the 'Fiber Architecture' working group, advancing microscopy techniques like scattered light imaging and MRI-histology correlation for studying brain microstructure. His work bridges experimental neuroscience with computational methods, aiming to decode brain organization at meso- and macroscales. Key achievements include developing the HippoMaps atlas of the human hippocampus and improving fiber orientation mapping in brain tissue. Awards include Fellowship in the Royal Netherlands Academy of Arts and Sciences (2024). Research emphasizes cross-modal data integration, with applications in Alzheimer’s disease biomarker validation and primate brain evolution studies. He collaborates with academic institutions like the University of Wuppertal and contributes to international initiatives like the BigBrain Analytics Learning Laboratory.

• Connectome
• Neuroimaging
• Polarization Microscopy
• +۳ مورد دیگر

Griffin Weber, M.D., Ph.D., is an Associate Professor of Medicine and Biomedical Informatics at Harvard Medical School (HMS) and Beth Israel Deaconess Medical Center (BIDMC). He directs the Biomedical Research Informatics Core (BRIC) at BIDMC. His research focuses on expertise mining, social network analysis, and biomedical informatics. Key contributions include developing Profiles RNS (an open-source research networking platform) and i2b2 / SHRINE federated query tools for clinical data. He holds MD and PhD degrees from Harvard (2007), and earlier degrees in bioengineering and computer science. Education: SB in Bioengineering (Harvard, 2000), SM/PhD in Computer Science (Harvard, 2004/2005), MD (Harvard, 2007). He served as Harvard Medical School's first Chief Technology Officer, building educational platforms for 500+ courses. His work spans DNA microarrays, breast cancer tumor modeling, and EHR bias analysis. Research Interests: Leveraging informatics to improve healthcare through federated data systems, team science dynamics, and EHR analysis. Projects include Profiles RNS for researcher networks and i2b2 for clinical data queries across institutions. He explores biases in EHR data filtering and visualizing healthcare system dynamics in biomedical data. Grant Leadership: Principal investigator on NIH grants addressing EHR biases (R01LM013345), healthcare system dynamics (U01CA198934), and scientific workforce networks (U01GM112623). Collaborator on PCORI and NIH-funded initiatives. Awards: 2020 Fellow of the American College of Medical Informatics; 2011 Top Podium Presentation (AMIA); 2007 Medical Technology Award (Massachusetts Medical Society). Labs/Teams: Leads BRIC at BIDMC, collaborates on i2b2/SHRINE, and contributes to the 4CE consortium for federated healthcare data analysis.

• Biomedical Informatics
• Social Network Analysis
• Team Science
• +۵ مورد دیگر

Heather R. Christofk is a Professor in the Department of Biological Chemistry at the David Geffen School of Medicine at UCLA. Her research focuses on the intricate relationship between cellular metabolism and various biological processes, particularly in the contexts of cancer development, stem cell function, and viral infections. Education: PhD in Cell and Developmental Biology from Harvard University (2007) BS in Molecular, Cell, and Developmental Biology from UCLA (2001) Dr. Christofk's research program centers on understanding how metabolic pathways regulate cellular processes in both normal physiology and disease states. Her laboratory has made significant contributions to understanding how cancer cells reprogram their metabolism to support rapid growth and proliferation, with particular focus on glucose metabolism, amino acid utilization, and metabolic adaptations in tumor microenvironments. She has also pioneered work on the metabolic regulation of stem cell function, especially in hair follicle stem cells, demonstrating how metabolic pathways control stem cell activation and differentiation. Her research has important implications for developing novel therapeutic approaches that target cancer metabolism while preserving normal tissue function. Analysis of Dr. Christofk's recent publications reveals a strong focus on metabolic heterogeneity across different biological contexts. Her work spans cancer metabolism (particularly in liposarcoma, melanoma, and hepatocellular carcinoma), stem cell metabolism (especially hair follicle stem cells), viral metabolism (including Epstein-Barr virus and Zika virus), and developmental metabolism (fetal development and organogenesis). A recurring theme is how metabolic pathways serve as regulatory nodes that control cell fate decisions, tumor progression, and therapeutic responses. Selected Research Funding: Metabolic Control of Hair Follicle Stem Cell Homeostasis and Tumorigenesis (NIH R01AR070245, 2018-2023) - Co-Principal Investigator Nutrient regulation of cancer cell growth (NIH R01CA215185, 2017-2022) - Principal Investigator Regulation of the Warburg Effect in Cancer (NIH DP2OD008454, 2011-2016) - Principal Investigator Dr. Christofk's laboratory maintains active collaborations across multiple disciplines, working with clinicians, basic scientists, and computational biologists to address complex questions in metabolism and disease. Her team employs a range of cutting-edge techniques including metabolomics, stable isotope tracing, molecular biology, and in vivo models to investigate metabolic regulation in health and disease.

• Cancer Metabolism
• Stem Cell Metabolism
• Metabolic Regulation of Cell Growth
• +۵ مورد دیگر

Young-Hee Lee is a Ph.D. candidate and Lecturer at the Technical University of Munich (TUM), affiliated with the TUM School of Engineering and Design and the Institute for Communications and Navigation. Her research focuses on proteomics, with emphasis on protein citrullination dynamics, phosphoproteomics in cancer diagnostics, and advanced mass spectrometry techniques. Her recent work includes the development of high-throughput proteomic workflows for ischemic stroke biomarker discovery and the application of deep learning to enhance citrullination identification. She contributes to methodological innovations in peptide extraction and single-cell proteomics sensitivity. Lee is part of the Chair of Communication and Navigation led by Prof. Christoph Günther, located at Theresienstraße 90, Munich. Her research bridges computational biology and biochemical analysis, with applications in cancer, neuroscience, and viral proteomics.

• Proteomics
• Bioinformatics
• Cancer Diagnostics
• +۳ مورد دیگر

George M. Church is a Professor of Genetics at Harvard Medical School and affiliated with MIT, where he directs PersonalGenomes.org, providing open-access genomic, environmental and trait data. His laboratory focuses on transformative technologies for reading and writing 3D/4D biological structures with attention to ethics, safety, and equitable access. Church has co-initiated major scientific initiatives including the BRAIN Initiative (2011) and multiple Genome Projects (GP-Read-1984, GP-Write-2016, PGP-2005). Church's research spans multiple cutting-edge domains including genome engineering, synthetic biology, aging reversal, and space genetics. His lab pioneered foundational methods for direct genome sequencing, molecular multiplexing and barcoding in 1984, leading to the first genome sequence in 1994. His innovations contributed to nearly all next-generation DNA sequencing methods and companies. Current research directions include machine learning for protein engineering, tissue reprogramming, organoids, gene therapy, and in situ 3D DNA/RNA/protein imaging. His work bridges fundamental biology with therapeutic applications across diverse fields from Alzheimer's disease to de-extinction biology. Church's recent publications reveal a remarkable breadth of scientific inquiry, spanning from fundamental genome editing techniques to applications in aging research, neuroscience, and space biology. His work increasingly integrates artificial intelligence with biological systems, as seen in papers on machine-guided cell-fate engineering and automation of systematic reviews with large language models. His research maintains a strong translational focus, with numerous papers addressing therapeutic applications in cancer immunotherapy, gene therapy, and diagnostics. The consistent theme across his diverse publications is the development and application of transformative technologies to address fundamental biological questions and medical challenges. National Academy of Sciences (NAS) membership National Academy of Engineering (NAE) membership Franklin Bower Laureate for Achievement in Science Co-initiator of the BRAIN Initiative (2011) Director of multiple NIH Centers for Excellence in Genomic Science (2004-2020) Church directs numerous research centers including the NIH-CEGS, Personal Genome Project (PGP), Lipper Center for Computational Genetics, and Wyss Institute Synthetic Biology center. His laboratory has trained PhD students across multiple Harvard and MIT programs including Biophysics, BBS, Biomedical Informatics, ChemBio, Chemistry, SSQB, MCO, Virology, HST, EE/CS, Physics and Applied Math. His commercial impact is extensive through companies spanning medical diagnostics (Knome/PierianDx, Alacris, Nebula, Veritas) and synthetic biology/therapeutics (AbVitro/Juno, Gen9/enEvolv/Zymergen/Warpdrive/Gingko, Editas, Egenesis). Church also pioneered new privacy, biosafety, ELSI, environmental and biosecurity policies. The Church Lab operates across multiple research domains including molecular multiplexing, next-generation sequencing, nanopore technology, and genome engineering. The lab maintains strong connections with the Personal Genome Project, Wyss Institute, and multiple commercial ventures. Current research directions include the Spatial Atlas of Human Anatomy (SAHA), human skin rejuvenation via mRNA, and space genetics research through the Consortium for Space Genetics and BioAstra. The lab's mission focuses on transformative technologies for reading and writing 3D/4D structures at any scale, inspired by but not limited by biology.

• Genomics
• Synthetic Biology
• Genome Engineering
• +۱۲ مورد دیگر