جستجوی استاد راهنمای دانشگاهی

Stefano Ermonمشاهده پروفایل

دانشیار

• Machine Learning
• Generative AI
• Computational Sustainability
• +۷ مورد دیگر

Stefano Ermon is an Associate Professor in the Department of Computer Science at Stanford University, affiliated with the Artificial Intelligence Laboratory and a Senior Fellow at the Woods Institute for the Environment. His research focuses on advancing machine learning and generative AI techniques to address societal and environmental challenges, including computational sustainability, geospatial analysis, and climate science. He holds a Ph.D. from Cornell University (2015). Education: Ph.D. in Computer Science, Cornell University (2015). Research Interests: Ermon’s work bridges foundational machine learning (e.g., diffusion models, generative AI, and optimization) with applications in sustainability, geospatial analysis (via satellite imagery), and earth observation systems. Notable contributions include predicting poverty using satellite data and developing scalable methods for molecule generation. Articles Trends: His recent work emphasizes diffusion models for generative tasks (e.g., text-to-image, molecule design), geospatial AI (e.g., environmental monitoring), and ethical AI (e.g., bias mitigation in LLMs). He also explores applications in robotics and scientific computing. Awards: He has received prestigious awards, including the ICML 2024 Best Paper Award, Sloan Research Fellowship, Microsoft Research Faculty Fellowship, and the IJCAI Computers and Thought Award. Advising and Grants: Ermon teaches courses like Probabilistic Graphical Models (CS228) and has secured grants from NSF, ONR, AFOSR, and private foundations. His lab develops tools for climate science and sustainable development. Labs/Teams: Leads the Stanford AI Lab group focused on computational sustainability and generative AI, collaborating with institutions like the Woods Institute for environmental applications.

Harris H. Wangمشاهده پروفایل

دانشیار

• Systems Biology
• Synthetic Biology
• Genome Engineering
• +۱۷ مورد دیگر

Harris H. Wang is an Associate Professor in the Department of Systems Biology and Department of Pathology and Cell Biology at Columbia University's Vagelos College of Physicians and Surgeons, where he also serves as Interim Chair of Systems Biology. He is affiliated with the Center for Computational Biology and Bioinformatics (C2B2) and the Integrated Program in Cellular, Molecular and Biomedical Studies (CMBS). B.S., Physics and Mathematics, MIT Ph.D., Biophysics, Harvard University Dr. Wang's research lies at the intersection of systems and synthetic biology, focusing on developing foundational technologies for genome engineering, microbiome manipulation, and synthetic genomics. His lab pioneers methods such as MAGE, MAGIC, CAST, and CAMII to enable high-throughput genetic manipulation, in situ microbiome engineering, and AI-driven microbial culturomics. Key research themes include understanding microbial community dynamics, engineering cellular memory systems, designing biocontained genetic circuits, and applying synthetic biology to human health challenges in personalized medicine and infectious disease. His recent publications reveal a strong trend in spatial and functional metagenomics, CRISPR-based microbiome editing, and synthetic biology tools for data storage and genetic stability. The articles span high-impact journals like Nature , Science , and Nature Biotechnology , reflecting his leadership in developing scalable, programmable biological systems. Scientific Awards: NIH Director’s Early Independence Award Forbes 30 Under 30 in Science Sloan Research Fellowship NSF CAREER Award ONR Young Investigator Award Burroughs Wellcome Fund PATH Award Schaefer Scholar Blavatnik National Award Vilcek Prize PECASE Dr. Wang has advised numerous PhD and postdoctoral researchers, many of whom have gone on to independent scientific careers. His lab is supported by major grants from NIH, NSF, DARPA, DOE, and foundations including the Bill & Melinda Gates Foundation and CZ Biohub NY. He is actively involved in educational initiatives, including organizing Columbia’s iGEM team and the Cold Spring Harbor Laboratory Synthetic Biology course. The Wang Lab is based at the Columbia University Irving Medical Center and is part of national consortia such as the Engineering Biology Research Consortium (EBRC) and the Genome Project-Write (GP-Write) initiative. The lab develops and applies cutting-edge technologies in automation, machine learning, and synthetic biology to engineer microbiomes for applications in medicine, global health, and climate change.

Daniel Goldmanمشاهده پروفایل

استاد

• Autonomy
• Molecular Biomechanics
• Cellular Biomechanics
• +۸ مورد دیگر

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.

Wojciech Matusikمشاهده پروفایل

استاد

• Computer Graphics
• Computational Design and Fabrication
• Computer Vision
• +۷ مورد دیگر

Wojciech Matusik is a Professor of Electrical Engineering and Computer Science at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). He leads the Computational Design and Fabrication Group and is a member of the Computer Graphics Group. His research spans computer graphics, robotics, and AI-driven manufacturing, with a focus on computational design, tactile sensing, and material science. Matusik holds a PhD in Computer Science from MIT (2003), an MS from MIT (2001), and a BS from UC Berkeley (1997). His work includes groundbreaking projects like differentiable cloth simulation (DiffCloth), AI-enhanced molecular design, and tactile sensing gloves. He has received prestigious awards such as the MIT TR35 (2004), DARPA Young Faculty Award (2012), and Ruth and Joel Spira Teaching Award (2014). Matusik teaches courses on computer graphics, machine learning, and computational fabrication at MIT. Key research themes include: Robotics: Robotic assembly, tactile interaction, and soft robotics Graphics: 3D holography, procedural material generation Manufacturing: Additive fabrication, topology optimization His recent articles explore AI-driven molecular synthesis, holographic displays, and tactile-enabled VR systems. Matusik collaborates on open-source tools like the WiReSens tactile platform and Simit language for sparse systems.

Subhransu Majiمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Subhransu Maji is an Associate Professor in the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst, and the co-director of the Computer Vision Lab. He is also affiliated with the Center for Data Science and holds a part-time role as an Amazon Scholar. His research focuses on high-level visual recognition algorithms and interdisciplinary applications in ecology and astronomy. He has received prestigious awards including the NSF CAREER Award (2018), Best Paper at WACV 2015, and the Google Graduate Fellowship (2008). Education: PhD in Computer Science from UC Berkeley (2011), BTech from IIT Kanpur (2006). Prior roles include Research Assistant Professor at Toyota Technological Institute at Chicago (2012-2014). Research Interests: Computer Vision Machine Learning AI Applications in Ecology and Astronomy 3D Shape Understanding Climate Science Grants and Funding: Supported by NSF, NASA, Climate Change AI, and industry grants from Facebook, NVIDIA, Adobe, and Dolby. Current projects include satellite imagery analysis for ecology and material science applications using deep learning. Labs and Teams: Leads the Computer Vision Lab, collaborates with interdisciplinary teams on ecological monitoring (e.g., bird migration tracking via radar data) and material property prediction (e.g., zeolite adsorption modeling).

Michael McAlpineمشاهده پروفایل

استاد

• 3D Printing
• Nanotechnology
• Biomedical Engineering
• +۴ مورد دیگر

Michael McAlpine is a Professor in the Mechanical Engineering department at the University of Minnesota . He also holds affiliations with the Biomedical Engineering and Electrical and Computer Engineering departments. His research focuses on 3D printing functional materials & devices , Nanoscale inks , Biomedical devices , Bioelectronics , and Flexible Microsystems . Research Interests : 3D Printing, Biomedical Engineering, Nanotechnology, Flexible Electronics, Microfluidics Labs : ME 361/363 Contact : mcalpine@umn.edu , (612) 626-3303, ME 117 Recent Research Trends include 3D Printed Biomedical Devices , Flexible Electronics , and Bioprinting Applications . His work spans from Spinal Organoid Formation to Programmable Drug Release Capsules . Scientific Award : Circulation Research 2020 Best Manuscript Award

Christopher Kananمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Deep Learning
• Continual Learning
• +۵ مورد دیگر

Christopher Kanan is a tenured Associate Professor of Computer Science at the University of Rochester, leading the AI Initiative within the Hajim School of Engineering & Applied Sciences. He holds secondary appointments in Brain and Cognitive Sciences, the Goergen Institute for Data Science and AI (GIDS-AI), and the Center for Visual Science. His research focuses on deep learning systems for artificial general intelligence (AGI), including continual learning, medical computer vision, and visual question answering. Previously, he was an Associate Professor at RIT’s Carlson Center for Imaging Science and a leader at Paige.AI, contributing to the FDA-cleared Paige Prostate system. Kanan earned his PhD from UC San Diego, completed postdoctoral work at Caltech, and worked at NASA JPL. Education: PhD in Computer Science, UC San Diego MS in Computer Science, University of Southern California Bachelor’s in Philosophy and Computer Science, Oklahoma State University Research Interests: Kanan’s work spans foundational AI capabilities like continual learning, medical imaging (pathology and radiology), multi-modal reasoning, and cognitive science-inspired models. His lab develops bias-robust AI systems and applies deep learning to healthcare and fusion research. Articles Trends: His recent work emphasizes out-of-distribution generalization, foundation models in pathology, and stability in continual learning. Key themes include AI applications in healthcare, model robustness, and neuroscience-inspired algorithms. Awards: NSF CAREER Award Senior Member, AAAI and IEEE DoE and NSF grants totaling $5M+ DARPA/ARL awards Advising & Grants: Mentored over 10 PhD students, including Robik Shrestha and Usman Mahmood. Secured grants for AI in nuclear fusion and medical imaging. Led RIT’s Center for Human-aware AI (CHAI) as Associate Director. Labs & Teams: Heads the University of Rochester AI Initiative, collaborates with Paige.AI, and leads teams advancing AI in pathology and robotics. His lab’s KLab (klab.cis.rit.edu) focuses on vision and learning systems.

Connor Coleyمشاهده پروفایل

استادیار

• Machine Learning for Chemistry
• Computer-Aided Molecular Design
• Synthesis Planning
• +۵ مورد دیگر

Connor Coley is the Henri Slezynger (1957) Career Development Assistant Professor at the Massachusetts Institute of Technology (MIT) School of Engineering. His research bridges chemistry and machine learning, focusing on autonomous molecular discovery, predictive chemistry, and laboratory automation. Education: Ph.D., MIT (2019) M.S.CEP., MIT (2016) B.S., Caltech (2014) Research Interests: Dr. Coley’s work centers on domain-informed machine learning for chemistry, computer-aided molecular design, and autonomous laboratories. Key themes include predictive modeling of chemical reactivity, optimization of synthesis pathways, and integration of AI with experimental data for drug discovery and materials science. Publications: His recent articles highlight advancements in AI-driven reaction prediction, molecular representation learning, and laboratory automation. Trends include applications of Bayesian optimization, contrastive learning, and diffusion models to chemical discovery. Scientific Awards: Camille Dreyfus Teacher-Scholar Award (2025) James W. Swan Outstanding Faculty (2025) Schmidt Futures AI2050 Early Career Fellow (2022) NSF CAREER Award (2021) Forbes 30 Under 30: Healthcare (2019) Software & Tools: He leads the open-source ASKCOS software suite for synthesis planning, adopted by 35,000+ chemists and deployed at 15+ pharmaceutical companies. His team also develops tools for metabolomics and molecular representation learning.

Rebecca Schulmanمشاهده پروفایل

دانشیار

• DNA Self-Assembly
• Smart Biomaterials
• Synthetic Biology
• +۷ مورد دیگر

Rebecca Schulman is an Associate Professor in the Department of Chemical and Biomolecular Engineering at the Whiting School of Engineering, Johns Hopkins University. She holds secondary appointments in Chemistry and Computer Science and is affiliated with multiple interdisciplinary institutes, including the Institute for NanoBioTechnology, the Hopkins Extreme Materials Institute, the Chemistry-Biology Interface Program, the Center for Cell Dynamics, and the Laboratory for Computational Sensing and Robotics. She currently co-directs the Passport to Future Technology Leadership program for PhD students. Research Interests: Schulman's research lies at the intersection of DNA nanotechnology, synthetic biology, and smart materials. Her group develops intelligent, adaptive biomolecular materials and nanostructures by integrating concepts from materials science, biochemistry, circuit design, and soft matter physics. The team focuses on engineering dynamic self-assembly processes using DNA to create reconfigurable materials, molecular circuits, and autonomous soft micro-robots. Key themes include self-healing nanostructures, feedback-regulated crystallization, programmable hydrogels, and synthetic genetic networks for materials control. Publication Trends: Her recent publications demonstrate a consistent focus on using DNA-based chemical reaction networks to program spatial and temporal behavior in materials. The work spans from fundamental mechanisms like catalytic polymerization and crystal growth regulation to applications in soft robotics, self-wiring circuits, and synthetic pattern formation. The research is highly interdisciplinary, combining synthetic biology with materials engineering to achieve life-like functionalities in non-living systems. Scientific Awards: AIMBE Fellowship Award Vannevar Bush Faculty Fellowship Award Hartwell Individual Biomolecular Research Award President’s Early Career Award in Science and Engineering (PECASE) DARPA Young Faculty Award DARPA Directors Fellowship NSF CAREER Award Turing Scholar Award DOE Early Career Award Advising and Grants: Schulman mentors graduate students and leads a vibrant research group focused on next-generation biomolecular engineering. Her work is supported by major federal grants, including the NSF CAREER, DOE Early Career, DARPA, and the Vannevar Bush Fellowship—a prestigious Department of Defense award for basic research. She is actively involved in training future leaders through programs like the Passport to Future Technology Leadership. Labs and Teams: The Schulman Lab at Johns Hopkins is a multidisciplinary team working on DNA-powered materials and molecular programming. The lab is embedded within several collaborative centers, enabling strong cross-departmental and cross-institutional research. Their work combines experimental biochemistry with theoretical modeling to design and implement complex molecular systems.

Daniel J. Prestonمشاهده پروفایل

استادیار

• Energy Efficiency
• Thermal Management
• Fluid Mechanics
• +۷ مورد دیگر

Dr. Daniel J. Preston is an Assistant Professor of Mechanical Engineering at Rice University, leading the Preston Innovation Laboratory (PI Lab). He holds a B.S. from the University of Alabama (2012), M.S. and Ph.D. from MIT (2014, 2017), and postdoctoral training at Harvard University (2017-2019). His research focuses on energy efficiency, soft materials, fluid mechanics, and robotics, with applications in wearable technologies and sustainable systems. Key achievements include the NSF CAREER Award (2022) and pioneering work on necrobotics using biotic materials. The PI Lab collaborates widely, with projects involving biomimetic surfaces, smart textiles, and fluidic control systems. Education: B.S. Mechanical Engineering, University of Alabama (2012) M.S./Ph.D. Mechanical Engineering, MIT (2014/2017) Research Interests: Energy : Thermal management, heat transfer optimization, and waste heat recovery. Materials : Soft actuators, surface coatings, and functional biomaterials. Fluids : Interfacial phenomena, droplet dynamics, and fluid-structure interactions. Notable Publications: Recent work includes advancements in wearable haptic devices ( Science Advances ), necrobotics ( Advanced Science ), and fluidic logic textiles ( PNAS ). Over 50 peer-reviewed articles span multidisciplinary topics from magnetic levitation to virus decontamination. Honors: In addition to the CAREER Award, Dr. Preston has received the NSF Graduate Research Fellowship, Tau Beta Pi Fellowship, and Wunsch Foundation Award. His lab fosters innovation through grants and industry partnerships. Advising & Grants: Supervises ~15 graduate and undergraduate students, including NSF GRFP recipients. Active in mentoring initiatives like the Randall Research Scholars Program and AATCC grants. Labs & Teams: The PI Lab collaborates with MIT’s DRL, Harvard’s Whitesides Group, and institutions globally. Core projects include smart wearables, energy harvesting fabrics, and autonomous soft robots.

Vanessa Samouëlianمشاهده پروفایل

دانشیار بالینی

• Gynecological Oncology
• Cervical Cancer
• Endometrial Cancer
• +۳ مورد دیگر

Vanessa Samouëlian, MD, PhD, serves as an Associate Clinical Professor in the Department of Obstetrics and Gynecology at the University of Montreal. Based at the Montreal University Hospital Center (CHUM), she specializes in gynecological oncology within the Gynecological Oncology division. Her institutional roles include leading Tumor Board meetings and serving as a service representative on CHUM's medical act evaluation committee and the University of Montreal externship committee. Her educational background includes: MD from University of Montpellier 1, France (1992-1998) Certificate of Clinical and Therapeutic Synthesis and Master's in Biological/Medical Sciences (1998) IUD in Colposcopy and Cervicovaginal Pathology (1999) DES in Gynecology-Obstetrics from University of Lille 2, France (2005) PhD from Biology-Health Doctoral School, University of Lille 2 (2007) Clinical Fellowship in Gynecology Oncology at CHUM (2009-2011) Dr. Samouëlian's research centers on gynecological malignancies with emphasis on cervical, endometrial, and vulvar cancers. She investigates molecular biomarkers for nodal metastasis, treatment outcomes in high-risk endometrial carcinoma, and surgical innovation including robotic techniques. Her work bridges clinical oncology, cancer pathology, and HPV vaccination strategies through national collaborations. Her 2015-2016 publications reveal a cohesive research trajectory focused on endometrial cancer through the Canadian High Risk Endometrial Cancer (CHREC) Consortium. Key themes include adjuvant therapy optimization, pathological pattern analysis (MELF invasion), and surgical training innovation using virtual reality simulation. These works demonstrate integration of clinical practice, molecular diagnostics, and surgical education within gynecologic oncology. Within CHUM's organizational structure, Dr. Samouëlian contributes to the Historical Assignment Team and Gynecological Oncology division. She co-developed the Contemporary Clinical Questions on HPV-Related Diseases and Vaccination booklet with Gynecologic Oncology Canada and Merck Canada, endorsed by major Canadian gynecological societies including the Society of Obstetricians and Gynaecologists of Canada.

Julia R. Greerمشاهده پروفایل

استاد

• Mechanics of Hierarchical Architectures
• Nanomaterials
• Additive Manufacturing
• +۷ مورد دیگر

Julia R. Greer serves as the Ruben F. and Donna Mettler Professor of Materials Science, Mechanics and Medical Engineering at the California Institute of Technology (Caltech), where she also holds the position of Executive Officer for Applied Physics and Materials Science since 2025. She earned her B.S. from MIT (1997) and M.S./Ph.D. from Stanford University (2000/2005), joining Caltech as Assistant Professor in 2007, promoted to Professor in 2013, and appointed to her current named professorship in 2019. Her research spans mechanics of hierarchical architectures , nanomaterials , and additive manufacturing , with significant contributions to energy storage systems and biomedical materials . Key focus areas include nano-scale mechanical properties, in-situ deformation analysis, and development of novel fabrication techniques for micro-architected materials. Her group pioneered hydrogel infusion additive manufacturing for metals and multiphoton 3D lithography standards. Analysis of recent publications reveals strong emphasis on solid-state battery interfaces (2025), bioresorbable microrobots (2024), and AI-enabled material design (2024), demonstrating cross-disciplinary impact across energy, healthcare, and quantum technologies. Her work consistently bridges fundamental nanomechanics with practical applications in energy storage and medical devices. 2024 ASME Nadai Medal 2024 SES A.C. Eringen Medal Elected to National Academy of Sciences (2025) Fletcher Jones Foundation Director (2019-2025) Professor Greer has advised over 40 PhD students including Seola Lee (2025) and Wenxin Zhang (2025), with research funded by collaborations spanning MIT, UCSF, Purdue, and ETH Zurich. Her group maintains active projects in lightweight nanoarchitected materials for impact absorption, electroactive polymers for braille devices, and 3D interdigitated solid-state batteries. Current leadership includes Editor-in-Chief of the Journal of Applied Physics (2024-) and direction of Caltech's Materials Science department.

Yongmin Liuمشاهده پروفایل

استاد

• Nano Optics
• Nanomaterials Engineering
• Plasmonics
• +۵ مورد دیگر

Yongmin Liu is a Professor in Mechanical and Industrial Engineering and Electrical & Computer Engineering at Northeastern University, and a member of the Cross-College Magnetics Center. He holds a PhD in Applied Science and Technology from UC Berkeley (2009), with earlier degrees from Nanjing University. His research focuses on nano-optics, metamaterials, plasmonics, and their applications in optical devices and systems. His interdisciplinary work bridges engineering, physics, and AI, with notable contributions to metasurface design and optical neural networks. Education: PhD, Applied Science and Technology, UC Berkeley (2009) M.S. and B.S., Physics, Nanjing University (2003, 2000) Research Interests: Nano-optics, nanoscale materials engineering, metamaterials, plasmonics, and applied physics. His group develops novel optical materials and devices for applications like super-resolution imaging, efficient light harvesting, and biomedical detection. Recent projects include AI-driven photonic materials design and meta-optical neural networks. Key Achievements: Recipient of the Søren Buus Outstanding Research Award (2024) NSF CAREER Award (2017) and ONR Young Investigator Award (2016) Elected SPIE Fellow (2023) and Optica Fellow (2023) Lab & Collaborations: Head of the Yongmin Liu Research Group, collaborating with institutions like Georgia Tech and Purdue University. Recent grants include a $1.5M NSF DMREF grant for AI-driven photonic materials and a $468K NSF grant for meta-optical neural networks.

• Biophysics
• Parasite mechanics
• Functional interfaces
• +۸ مورد دیگر

Christine Selhuber-Unkel is a Full Professor (W3) for Molecular Systems Engineering at the Institute for Molecular Systems Engineering and Advanced Materials (IMSEAM) at Heidelberg University. She serves as co-chair of the Executive Board of the Flagship Initiative 'Engineering Molecular Systems' and is a spokesperson for the 'Cellular Biophysics' section of the German Biophysical Society. Additionally, she is a member of the executive board of the Cluster of Excellence '3D Matter Made to Order'. Education: Studied physics at Heidelberg University (2000-2002) M.Sc. degree in Physics from Uppsala University (2003) PhD in Physics from Heidelberg University (biological adhesion on nanopatterned substrates) Professor Selhuber-Unkel's research focuses on functional interfaces and their interactions with biological systems, including responsive interfaces, micro-/nanostructured interfaces (including 2-photon laser printing), and biofunctionalized hydrogels. Her work specifically targets controlling cellular properties such as parasite migration, with potential applications in soft robotics and biomaterials. She also experimentally studies biophysical properties of cells including mechanosensing, cellular force generation, adhesion forces, and statistical properties of intracellular motion and migration. Her research group is involved in multiple projects related to parasite physics, including studies on Giardia adhesion, Plasmodium infected erythrocytes, and Toxoplasma gondii. Her recent publications demonstrate a strong focus on hydrogel engineering, cellular mechanics, and microfluidic systems for studying cell behavior. The research spans from fundamental biomaterials development to applications in ophthalmology, tissue engineering, and parasite mechanics. Scientific Awards: European Research Council Consolidator Grant (PHOTOMECH) European Research Council Starting Grant (CELLINSPIRED) Feodor Lynen Fellow for research stay at Cornell University Emmy Noether postdoctoral fellowship Otto Hahn Medal from the Max Planck Society Professor Selhuber-Unkel has received significant research funding, including multiple ERC grants and DFG funding. She previously served as spokesperson for the DFG research training group 'Materials for Brain' at Kiel University (2017-2020). Her research group maintains strong collaborations across multiple institutions focused on biophysical approaches to understanding cellular and parasite mechanics. Her laboratory develops advanced techniques including traction force microscopy, atomic force microscopy (AFM), and microengineered systems for studying cellular mechanics in confined environments. The group's work bridges materials science, biophysics, and parasitology to develop novel approaches for understanding and controlling cellular behavior.

Kevin C. Zhouمشاهده پروفایل

استادیار

• Computational Imaging
• Biomedical Engineering
• Optical Systems
• +۳ مورد دیگر

Kevin C. Zhou is an Assistant Professor in the Department of Biomedical Engineering at the University of Michigan. His research focuses on developing high-performance computational optical imaging systems with unprecedented spatiotemporal throughput, integrating advanced optical instrumentation with machine learning-driven algorithms to analyze big data in biology and medicine. His lab specializes in creating imaging systems capable of capturing high-resolution, high-speed, and high-dimensional datasets. Dr. Zhou holds a Ph.D. in Biomedical Engineering from Duke University (NSF GRFP Fellow) and a B.S. in Biomedical Engineering from Yale University (Barry Goldwater Scholar). Prior to joining U-M, he was a Schmidt Science Fellow and postdoctoral researcher at UC Berkeley. Key research areas include: High-throughput microscopy (gigapixel-scale systems) 3D tomographic imaging Light field and Fourier-based imaging modalities Machine learning for image reconstruction and analysis Biomedical applications in cellular/molecular imaging His recent work has advanced technologies like multi-camera array microscopes (MCAM/MCAS) and Fourier light field mesoscopes, achieving video-rate 3D imaging of freely moving organisms. These innovations enable applications in digital cytopathology, behavioral tracking, and high-content biological studies. Notable awards include the NSF Graduate Research Fellowship and Barry Goldwater Scholarship. His research has been featured in top journals and conferences with a focus on advancing optical imaging hardware and computational pipelines.