جست‌وجوی استاد و پژوهشگر

Joel Gohمشاهده پروفایل

دانشیار

• Health services and systems
• Transportation, logistics and supply chains
• Operations research
• +۶ مورد دیگر

Joel Goh is Associate Professor at the Department of Analytics and Operations, NUS Business School, National University of Singapore. He serves as Director of the J.Y. Pillay Comparative Asia Research Centre (under NUS Global Asia Institute) and PhD Program Director at the Institute of Operations Research and Analytics (IORA). Previously, he was Assistant Professor at Harvard Business School (2014-2017) and Visiting Scholar (2017-2022). BSc, MSc, PhD in Operations, Information, and Technology from Stanford University His research focuses on healthcare analytics (preventing health conditions, hospital operations, frailty assessment), supply chain analytics (digital business models, platform leakage), and service platform operations (hospital-at-home programs, incentive design). He co-created the Robust Optimization Made Easy (ROME) software. Recent publications analyze workplace psychological safety (2024), hospital-at-home models (2024), and platform leakage dynamics (2023). His work spans 18+ journals with 740+ citations for burnout cost studies (2022) and 606+ citations for physician well-being research (2017). Teaching Honors : 2023: Best MBA Teaching & Skinner Innovation Award 2021: NUS Annual Teaching Excellence Award 2020: Early Career Research Excellence Award & 40 Under 40 Best MBA Professors Advising & Grants : Served as PhD Program Director. Received NUS Start-Up Grant R-314-000-110-133 (2021) and Humanities & Social Sciences Fellowship (2021). Editorial roles include Associate Editor at Management Science , Manufacturing & Service Operations Management , and Senior Editor at Production and Operations Management .

• Fibrosis Research
• Liver Fibrosis
• Kidney Fibrosis
• +۹ مورد دیگر

Karen Piper Hanley is Professor of Molecular Medicine and Head of Division in the Division of Diabetes, Endocrinology & Gastroenterology at the University of Manchester. She serves as the fibrosis lead in the Wellcome Trust Centre for Cell-Matrix Research and previously served as Director of Core Research Technologies (2019-2022). She is also an editorial board member for Scientific Reports. Her research focuses on fibrosis (scarring) mechanisms across multiple organs, particularly liver, kidney, and lung fibrosis. Her lab investigates the cellular and molecular basis of fibrotic disease, with emphasis on how pathological scar components are produced and how they signal to surrounding cells. Key areas include the role of SOX9 transcription factor, integrin beta-1 signaling, Group 1 PAKs, and YAP1 in fibrosis progression. Her recent publications reveal trends toward increased clinical translation of fibrosis research, with studies on health inequalities in liver cancer care, post-COVID diabetes incidence, and innovative approaches to liver disease detection. Her work increasingly integrates spatial transcriptomics and advanced omics technologies to understand cellular transitions in liver disease. Career-track postdoctoral fellowship from the University of Southampton (2006) As senior postgraduate tutor, she has mentored numerous PhD students who have presented at key conferences and authored high-quality manuscripts. All her PhD students have submitted and been awarded their degrees within 4 years. She has successfully guided previous Academic Clinical Fellows to win MRC clinical training fellowships. Her teaching extends to undergraduate Personal & Professional Development and supervision of MRes and BSc students, many of whom have achieved first-class degrees and prestigious awards. Her lab maintains active collaborations with Professor Neil Hanley's group on human development, stem cells, and regenerative medicine, bridging developmental biology with fibrosis research to understand why regeneration is impaired in chronic diseases.

Andre Levchenkoمشاهده پروفایل

استاد

• Systems Biology
• Signal Transduction
• Cell Communication
• +۵ مورد دیگر

Andre Levchenko is the John C. Malone Professor of Biomedical Engineering at Yale University, with secondary appointments in the Department of Neurosurgery and affiliations with the Cancer Signaling Networks, Immunology, and the Yale Program in Neurodevelopment and Regeneration. His research focuses on systems biology, signal transduction, and cell-cell communication, utilizing microfluidics and computational modeling to study cancer progression, stem cell behavior, and neurological disorders. PhD, Columbia University MEng, Moscow Institute of Physics and Technology Levchenko's work explores how cells process dynamic signals to make critical decisions, particularly in glioblastoma migration, organoid development, and cardiovascular tissue engineering. His lab develops innovative microfluidic platforms and mathematical models to dissect multicellular communication and signaling networks. Recent publications highlight his contributions to understanding YAP-driven cancer invasion , NOTCH signaling in angiogenesis , and metabolic regulation of hypoxia responses . He has pioneered methods for organoid modeling and single-cell analysis , advancing precision in biological signaling studies. Scientific Awards : Computational Molecular Biology Post-Doctoral Fellowship (Burroughs Wellcome Fund) National Academies Keck Futures Conference Invitee Distinguished Guest Lecturer, University of Virginia American Asthma Foundation Early Excellence Award Fellow, American Institute for Medical and Biological Engineering Levchenko leads the Levchenko Lab at the Yale Systems Biology Institute, collaborating with institutions like Mayo Clinic and Yale Cancer Center. His research has received recognition in Faculty of 1000 and multiple journal highlights.

David Ericksonمشاهده پروفایل

استاد

• Global Health Technology
• Medical Diagnostics
• Microfluidics
• +۵ مورد دیگر

David Erickson is the SC Thomas Sze Director and Sibley College Professor at Cornell University's Sibley School of Mechanical and Aerospace Engineering. He also holds a joint professorship in the Division of Nutritional Sciences. His research focuses on global health technologies, medical diagnostics, microfluidics, photonics, nanotechnology, and energy systems. He previously served as Associate Dean of Engineering for Research and Graduate Programs. Erickson leads the NIH-funded PORTENT Center for Point-of-Care Technologies in Global Health and has co-founded companies like Dimensional Energy and VitaScan to commercialize diagnostic and energy technologies. Education: B.Sc., Mechanical Engineering, University of Alberta (1999) M.A.Sc., Mechanical Engineering, University of Toronto (2001) Ph.D., Mechanical Engineering, University of Toronto (2004) Postdoctoral Scholar, Electrical Engineering, California Institute of Technology (2005) Research Interests: Erickson’s work spans global health diagnostics , nanobio applications , and clean energy innovation . He develops portable medical devices for low-resource settings, including smartphone-integrated diagnostic tools for malaria, iron deficiency, and cancer. His lab also pioneers photothermal reactors for CO2 conversion into sustainable fuels. Key areas include: Point-of-care testing for infectious diseases and nutritional deficiencies Nanofluidic and optofluidic technologies for biomolecular analysis Solar-driven energy systems for carbon-neutral fuels Awards: Presidential Early Career Award for Scientists and Engineers (2011) Fellowships from the Optical Society, ASME, and Canadian Academy of Engineering Carbon X-Prize Finalist (2019) for Dimensional Energy’s CO2-to-fuel technology Grants & Industry Collaboration: Erickson’s research is funded by NIH, NSF, ARPA-E, DOE, and USAID. His lab’s innovations have spun off start-ups addressing global health and energy challenges. Notable projects include: - Portable cancer diagnostics in sub-Saharan Africa using mobile phone-based systems - Solar-powered CO2 conversion reactors tested in Wyoming and Arizona Labs & Teams: The Erickson Lab collaborates with the Cornell Atkinson Center for Sustainability and the McGovern Center for Entrepreneurship. Key initiatives include the PORTENT Center and the Dimensional Energy CO2-to-fuel project.

Vakil Takhaveevمشاهده پروفایل

مدرس

• DNA Damage and Repair
• Aging Mechanisms
• Cancer Biology
• +۶ مورد دیگر

Dr. Vakil Takhaveev is a Lecturer at ETH Zurich's Department of Health Sciences and Technology, within the Institute of Food, Nutrition and Health. His research focuses on DNA damage mechanisms, aging, cancer, and neurodegeneration, with particular emphasis on developing novel DNA-damage-sequencing methods like click-code-seq and TRABI-Seq . He investigates anticancer drug action (e.g., trabectedin), aging clocks using DNA oxidation profiling, and stress-induced carcinogenesis. His work integrates multi-omics approaches and advanced sequencing techniques. Research Directions: Novel DNA-Damage-Sequencing Methods: Developed click-code-seq and TRABI-Seq for genomic mapping of DNA lesions and repair dynamics. Anticancer Drug Action: Explored mechanisms of trabectedin and other chemotherapeutics, linking DNA repair vulnerabilities to therapy resistance. Aging Clocks: Created DNA oxidation-based biomarkers for biological aging using genome-wide profiling in human and mouse models. Stress-Induced Pathologies: Studies metabolic and DNA damage links to early tumorigenesis and neurodegeneration. Awards & Recognition: 2025 Public Award Winner in PIs of Tomorrow competition 2024 ETH Zurich Career Seed Award Best presentation awards (Swiss Chemical Society, American Chemical Society) Grants & Collaborations: Impetus grants for aging clock development Swiss Chemical Society and American Chemical Society fellowships Labs & Teams: Leads research on DNA damage and aging mechanisms at ETH Zurich, collaborating with international groups in oncology and toxicology.

Shasha Chongمشاهده پروفایل

استادیار

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

• Biomaterials
• Tissue Engineering
• Mechanobiology
• +۳ مورد دیگر

Dr. Yogambha Ramaswamy is a Senior Lecturer in the School of Biomedical Engineering at The University of Sydney and a member of the Sydney Nano Institute. She holds a Master’s in Biotechnology from the University of Queensland and a PhD in Biomedical Engineering from the University of Sydney (2009). Her postdoctoral career began as a Vice-Chancellor’s Postdoctoral Research Fellow at the University of New South Wales, followed by a Peter Doherty Early Career Fellowship in 2013 before joining the University of Sydney in 2015. Dr. Ramaswamy’s research focuses on biomaterials, tissue engineering, and mechanobiology, with a particular emphasis on developing calcium silicate-based ceramics and biopolymers for orthopedic and regenerative applications. Her recent work explores the role of physical cues in modulating stem and cancer cell behavior. She teaches courses such as AMME1961 (Introduction to Biomedical Engineering B) and AMME5962 (Introduction to Mechanobiology). Her research has been supported by grants including the NHMRC Early Career Fellowship and collaborations with institutions like the CSIR-Indian Institute of Chemical Technology and the University of Otago. Her publications span biomaterials, nanotechnology, and mechanobiology, with recent work addressing atherosclerosis, hydrogel design, and nanomedicine. She currently supervises PhD students Frank (biomaterials) and Alexander (atherosclerosis research).

Kelly Arnoldمشاهده پروفایل

دانشیار

• Biomedical Computation and Modeling
• Drug Delivery and Therapeutics
• Systems Immunology
• +۵ مورد دیگر

Kelly Arnold is an Associate Professor in the Department of Biomedical Engineering at the University of Michigan. Her research integrates systems engineering principles with immunology to investigate variability in immune responses across infection, vaccination, and injury, with a focus on computational modeling and clinical translation. Research Focus Systems-level immune response modeling Vaccination and antibody functionality Vaginal microbiome-host interactions Chronic lung disease progression Computational serology and proteomics Recent Work Her 2025 studies examine SARS-CoV-2 vaccination responses in cancer patients and computational frameworks for vaginal probiotics. Earlier works (2024-2007) span COPD progression, lupus fibrosis, HIV susceptibility, and tissue engineering for fertility preservation. Methodologies include proteomic profiling, network modeling, and microfluidic systems.

Matthias Mannمشاهده پروفایل

استاد

• Mass Spectrometry
• Proteomics
• Systems Biology
• +۶ مورد دیگر

Professor Matthias Mann is a world-leading scientist serving as Director of the Proteomics and Signal Transduction department at the Max Planck Institute of Biochemistry in Martinsried, Germany, and Director of the Proteomics department at the Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Denmark. With an h-index exceeding 277 and over 350,000 citations, he is recognized as the highest cited German researcher and one of the most influential scientists globally in proteomics. His educational background includes: Ph.D. in Chemical Engineering from Yale University (1988) Master's Degree in Physics from Georg August University Göttingen (1984) Bachelor's of Arts in Mathematics from Georg August University Göttingen (1982) Professor Mann's research focuses on advancing mass spectrometry-based proteomics to understand biological systems at the protein level. His work spans technological developments in mass spectrometry, bioinformatics and computational analysis, signal transduction and posttranslational modifications, and clinical proteomics applications for disease diagnosis and treatment. The Mann lab has pioneered groundbreaking methods like SILAC for quantitative proteomics and MaxQuant for proteome data analysis. Their vision is to translate proteomics knowledge into clinical practice for predictive, diagnostic, and preventive medicine, with recent work focusing on AI-guided platforms for analyzing proteomes from minimal tissue samples. Analysis of Professor Mann's recent publications reveals a strong trend toward clinical applications of proteomics, particularly in cancer research, metabolic diseases, and neurodegenerative disorders. His work increasingly integrates spatial proteomics, single-cell resolution techniques, and artificial intelligence approaches to uncover disease mechanisms and identify potential biomarkers, with a clear shift from basic technology development toward direct clinical applications and personalized medicine. Professor Mann has received numerous prestigious awards throughout his career: 2025: Elected member of the American National Academy of Sciences 2024: Dr. H.P. Heineken Award for Biochemistry and Biophysics 2023: Otto Warburg Medal 2019: Nominated member of the Bavarian Academy of Sciences 2013: Elected member of Leopoldina German National Academy of Sciences 2012: Körber European Science Award, Louis-Jeantet Foundation Prize for Medicine, Ernst Schering Prize, and Leibniz Prize Professor Mann leads a highly collaborative research team involved in multiple international networks including the Bill & Melinda Gates Foundation, Michael J. Fox Foundation for Parkinson's Research, CLINSPECT-M, and Munich Heart Alliance. His lab has mentored numerous successful researchers, with several former postdocs receiving prestigious ERC Starting Grants. The Mann group has developed innovative clinical proteomics pipelines for analyzing archived tissue specimens and body fluids, aiming to identify protein markers for early detection of diseases such as diabetes and cancer. The Mann lab operates across two major research centers with state-of-the-art mass spectrometry facilities. Their Clinical Knowledge Graph platform integrates multi-omics data with extensive metadata, creating an ecosystem for machine learning applications in proteomics. Current research focuses on developing highly sensitive methods that can profile thousands of proteins from minimal cell samples, enabling the identification of critical disease-related proteins and supporting the development of individualized therapies.

John P.A. Ioannidisمشاهده پروفایل

استاد

• Meta-research
• Evidence-based Medicine
• Research Reproducibility
• +۱۲ مورد دیگر

John P.A. Ioannidis is the C.F. Rehnborg Professor in Disease Prevention and Professor of Medicine, Health Research and Policy, Biomedical Data Science, and Statistics at Stanford University. He is Co-Director of the Meta-Research Innovation Center at Stanford (METRICS) and an Einstein BIH Visiting Fellow at Charité - Universitätsmedizin Berlin. His academic appointments span multiple departments and institutes at Stanford, including the Stanford Prevention Research Center, Biomedical Data Science, and Statistics. He is internationally recognized for his work in meta-research, evidence-based medicine, and research reproducibility. Ioannidis holds an MD and DSc in Biopathology from the National University of Athens, with training in internal medicine and infectious diseases from Harvard and Tufts. He previously chaired the Department of Hygiene and Epidemiology at the University of Ioannina Medical School and held adjunct positions at Harvard, Tufts, and Imperial College. He joined Stanford in 2010, where he launched the PhD program in Epidemiology & Clinical Research, the MS in Community Health & Prevention Research, and METRICS in 2014. His research focuses on improving research methods, appraising biases, enhancing reproducibility, and integrating evidence across scientific disciplines. He is a pioneer in meta-research, with seminal contributions on the reliability of published findings, statistical practices, and research synthesis. His influential 2005 paper, "Why Most Published Research Findings Are False," is the most-accessed article in PLoS history. His recent work examines peer review, data sharing, AI in medicine, and pandemic research impact, consistently advocating for transparency and methodological rigor. His publications span epidemiology, statistics, genomics, clinical trials, and meta-analysis, with a strong emphasis on bias detection, replication, and open science. Trends in his recent articles highlight concerns about research integrity, citation practices, peer review reform, and the scientific response to global health crises. Founders' Medal for Lifetime Contributions to Meta-science (2024) Honorary doctorates from McMaster, Thessaloniki, Edinburgh, Tilburg, Athens, and Rotterdam Elected member, US National Academy of Medicine (2018) Elected member, European Academy of Sciences and Arts (2015) President, Association of American Physicians (2023–2024) President, Society for Research Synthesis Methodology Gordon Award, NIH (2019) Chanchlani Global Health Award (2017) Highly Cited Researcher (Clarivate) in Clinical Medicine, Social Sciences, and Psychiatry Ioannidis has advised numerous students and mentored early-career researchers. He has served as Senior Advisor for Knowledge Integration at the National Cancer Institute (2012–2016) and Editor-in-Chief of the European Journal of Clinical Investigation (2010–2019). He has received over 700 invited lectures and is deeply involved in shaping research policy and scientific infrastructure. He leads METRICS, a hub for meta-research innovation, and is affiliated with multiple Stanford institutes, including Bio-X, the Cardiovascular Institute, and the Stanford Cancer Institute.

Canan Dagdevirenمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Piezoelectric Devices
• Wearable Electronics
• +۶ مورد دیگر

Dr. Canan Dagdeviren is an Associate Professor and LG Career Development Professor of Media Arts and Sciences at the Massachusetts Institute of Technology, where she directs the Conformable Decoders research group at the MIT Media Lab. She joined the MIT faculty in January 2017 and has established herself as a leading innovator in conformable biomedical devices. Education: Ph.D. in Materials Science and Engineering, University of Illinois at Urbana-Champaign M.Sc. in Materials Science and Engineering, Sabanci University, Istanbul, Turkey B.Sc. in Physics Engineering, Hacettepe University, Ankara, Turkey Dr. Dagdeviren's research focuses on creating mechanically adaptive electromechanical systems that can intimately integrate with biological surfaces for sensing, actuation, and energy harvesting. She believes vital information from nature and the human body is 'coded' in various physical patterns, and her work develops 'conformable decoders' to translate these patterns into beneficial signals and energy. Her research spans wearable and implantable medical devices, with particular emphasis on piezoelectric systems that can be twisted, folded, stretched, wrapped, and implanted onto curvilinear surfaces of the human body without damage or significant alteration in performance. Analysis of her recent publications reveals a strong focus on medical applications of conformable electronics, particularly in ultrasound technology for breast cancer detection, deep brain stimulation, and bladder monitoring. Her work consistently bridges materials science, electrical engineering, and medical applications, with increasing emphasis on practical healthcare solutions that can be deployed outside clinical settings. Major Scientific Awards: NSF CAREER Award (2021) 3M Non-Tenured Faculty Award (2021) MIT Technology Review's Top 35 Innovators Under 35 (2015) Forbes' Top 30 Under 30 in Science (2015) National Academy of Engineering US Frontiers of Engineering Symposium participant (2019) Frank E. Perkins Award for Excellence in Graduate Advising Aziz Sancar Science Award Dr. Dagdeviren actively mentors graduate students and has received recognition for her advising excellence. Her research is supported by significant grants including the NSF CAREER award and has resulted in numerous patents and commercialization opportunities. She has developed innovative cleanroom-based courses at MIT that train students in microfabrication techniques for biomedical devices. The Conformable Decoders research group operates a specialized cleanroom facility at the MIT Media Lab, enabling the development and fabrication of novel conformable electronic systems. The group's work has attracted attention from major media outlets including BBC, CNN, and Nature, and has potential applications across multiple medical specialties including neurology, oncology, and urology.

Tim Q. Duongمشاهده پروفایل

استاد

• Medical Imaging
• MRI
• Image Analysis
• +۹ مورد دیگر

Tim Q. Duong, Ph.D., is a Professor at Albert Einstein College of Medicine, affiliated with the Departments of Radiology, Biochemistry, Ophthalmology & Visual Sciences, and Neuroscience. His research focuses on medical imaging, MRI, image analysis, machine learning, and predictive modeling for studying diseases like COVID-19 , neurodegeneration (Alzheimer's, multiple sclerosis), brain injuries , and breast cancer . Develops AI-driven MRI techniques for early disease detection Investigates neuroplasticity in glaucoma and diabetic retinopathy Leads grants from NIH and National Eye Institute Research Trends : Recent publications emphasize AI integration in medical imaging, long-term effects of SARS-CoV-2, and advanced MRI applications for ocular and neurological disorders. Grants include multiple R01 awards for diabetic retinopathy and glaucoma studies. Training Opportunities : Actively recruits postdocs, research coordinators, and faculty. Offers research positions for graduate, medical, and high school students, including Regeneron Scholar programs. Labs & Teams : Leads the Duong Lab at Montefiore Medical Center, focusing on translational research for clinical imaging solutions.

Vasilis Ntziachristosمشاهده پروفایل

استاد

• Biomedical Imaging
• Optoacoustic Imaging
• Medical Diagnostics
• +۳ مورد دیگر

Prof. Vasilis Ntziachristos is a Professor and Chair of Biological Imaging at the Technical University of Munich (TUM), leading the Institute of Biological and Medical Imaging at the Helmholtz Centre Munich. His research focuses on developing novel optical and optoacoustic imaging techniques for early disease detection, diagnostics, and theranostics. He holds a PhD in Bioengineering from the University of Pennsylvania and previously served as an Assistant Professor at Harvard University and Massachusetts General Hospital. Affiliations: TUM School of Medicine and Health, Helmholtz Munich, Institute of Biological and Medical Imaging. Key Research Themes: Non-invasive imaging methods, molecular imaging, optoacoustic technology, and clinical translation. His work bridges theoretical developments with clinical applications, including advancements in glucose monitoring, cancer imaging, and drug delivery systems. Notable awards include the Leibniz Prize (2013) and the World Molecular Imaging Society Gold Medal (2015). Labs/Teams: Imaging to Sensing I2S, Optoacoustic Mesoscopy, Fluorescence Imaging, and AI in Optoacoustics. Grants/Projects: Involvement in Horizon Europe initiatives and collaborations with TranslaTUM and Helmholtz Munich. Prof. Ntziachristos actively contributes to education via courses like 'Biological Imaging' and 'Introduction to Bioengineering', fostering the next generation of imaging scientists.

• Machine Learning
• Statistical Learning Theory
• Optimization
• +۳ مورد دیگر

Professor Yiming Ying is a faculty member in the Faculty of Science at the University of Sydney, where he joined in December 2023. Previously, he held tenured positions at SUNY Albany (Departments of Mathematics & Statistics and Computer Science) and was a Lecturer at the University of Exeter. He completed his PhD in Mathematics at Zhejiang University (2002) and postdoctoral training at CityU Hong Kong, UCL, and University of Bristol. Research Focus His research spans statistical learning theory, optimization algorithms, trustworthy AI, and data science mathematics. Key applications include cancer informatics for early detection. His work aligns with Faculty research strengths in Data and Decisions and Decision-Making for a Sustainable Future. Recent Research Trends Analysis of recent publications shows strong focus on theoretical foundations of machine learning: differential privacy, fairness algorithms, optimization methods for AUC maximization, generalization guarantees, and robust learning techniques for adversarial settings and biological data. Awards and Honors SUNY Chancellor’s Award for Excellence (2023) University at Albany Presidential Research Award (2022) University of Exeter Merit Award (2012) Grants and Advising Significant funding includes current ARC DP250101359 (2025-2028) and multiple past NSF grants. He founded the UALBANY Machine Learning Group and currently advises PhD student Peilin LIU on operator learning.

Adam Yalaمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Precision Medicine
• +۵ مورد دیگر

Adam Yala is an Assistant Professor of Computational Precision Health, Statistics, and Electrical Engineering and Computer Science at UC Berkeley and UCSF. He is also the Founder & CEO of Voio Inc., a company focused on clinical translation of AI tools. PhD in Computer Science from MIT (2022) His research lies at the intersection of Machine Learning and Precision Medicine, with a focus on robust AI tools for clinical deployment, personalized screening policies, and private data sharing. Current work includes multi-modal imaging analysis, decision guarantees in clinical workflows, and prospective trials in oncology and radiology. Recent publications highlight advancements in AI for cancer risk prediction, vision-language models in healthcare, and data privacy techniques. Tools like Mirai are implemented in 66 hospitals across 30 countries. Bakar Fellows Spark Award (2024) Eppy Award: Investigative Reporting (2022) Falling Walls Finalist: Life Science (2022) NSF Fellowship (2016) He advises PhD students in AI-driven healthcare and collaborates with hospital systems globally. His lab emphasizes clinical translation of machine learning methods in radiology and oncology.