جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Probability
• Mathematical Physics
• +۶ مورد دیگر

Boris Hanin is an Associate Professor at Princeton University's Department of Operations Research and Financial Engineering (ORFE) and Associated Faculty at the Program in Applied and Computational Mathematics (PACM). Prior to Princeton, he held academic positions at Texas A&M University (Assistant Professor of Mathematics), MIT (NSF Postdoctoral Fellow), and Northwestern University (PhD in Mathematics under Steve Zelditch). He works part-time at Foundry, an AI/computing startup, leading the Foundry Institute. PhD in Mathematics, Northwestern University NSF Postdoctoral Fellowship, MIT Mathematics Associate Professor, Princeton ORFE Part-Time Leader, Foundry Institute His research spans machine learning, probability theory, and mathematical physics, focusing on neural network theory (approximation power, optimization guarantees), random matrix theory, and spectral asymptotics. He has made foundational contributions to understanding gradient behavior, initialization, and infinite-width limits in deep learning. Boris has supervised numerous PhD students and postdocs, with former members securing prestigious positions at Harvard, MIT, and Huawei. He serves as Associate Editor for journals like Pure and Applied Analysis and Mathematics of Operations Research , and has taught short courses at Oxford, Luxembourg, and Tor Vergata on statistical physics of neural networks and deep learning theory. 2024 Sloan Fellowship in Mathematics NSF CAREER grant DMS-2143754 NSF grant DMS-2133806 His research group collaborates on topics including hyperparameter transfer, architecture-aware scaling, and spectral analysis of random waves and neural networks. He actively contributes to theoretical machine learning through foundational publications in venues like Probability Theory and Related Fields , Journal of Machine Learning Research , and Communications in Mathematical Physics .

Joshua D. Angristمشاهده پروفایل

استاد

• Econometrics
• Labor Economics
• Causal Inference
• +۳ مورد دیگر

Joshua D. Angrist is the Ford Professor of Economics at the Massachusetts Institute of Technology, where he has been a faculty member since 1996. He is also a co-founder and director of MIT's Blueprint Labs and a Research Associate at the National Bureau of Economic Research. Angrist shares the 2021 Nobel Prize in Economic Sciences with David Card and Guido Imbens for their methodological contributions to the analysis of causal relationships. Angrist received his B.A. from Oberlin College in 1982 and completed his Ph.D. in Economics at Princeton University in 1989. Prior to joining MIT, he taught at Harvard University and the Hebrew University of Jerusalem. His academic journey began somewhat unconventionally, as he left high school early after 11th grade, worked for over a year, and only later discovered his passion for economics through an inspiring teacher at Oberlin. Angrist's research focuses on developing and applying innovative econometric methods to answer important economic questions using natural experiments. His work spans labor economics, education economics, and causal inference methodology. He is particularly known for his contributions to instrumental variables methods and the Local Average Treatment Effect (LATE) framework developed with Guido Imbens. His research explores the economics of education and school reform, the impact of social programs on labor markets, and the effects of immigration and regulation. His recent publications reveal a continued focus on causal inference methods applied to education policy questions, labor market issues, and health economics. The trend shows increasing sophistication in research design, with particular attention to addressing selection bias and developing methods for external validity. His work spans theoretical econometric contributions alongside empirical applications in education, labor markets, and health. Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel (2021) Fama Prize for Graduate Education (2018) Fellow of the American Academy of Arts and Sciences Fellow of the Econometric Society Angrist is deeply committed to teaching and mentoring. He has developed influential econometrics textbooks including 'Mostly Harmless Econometrics' and 'Mastering Metrics' with Jörn-Steffen Pischke. At MIT, he teaches courses including Labor Economics I (14.661), Econometric Data Science (14.32), and Labor Economics and Public Policy (14.64). He emphasizes selecting UROP students who have mastered foundational economics through courses like 14.64 and 14.32. Beyond MIT, Angrist co-founded Avela, a software startup using cutting-edge research to help schools improve enrollment and operations. Angrist co-founded and directs MIT's Blueprint Labs, which brings together researchers from economics, computer science, and education to develop innovative solutions for educational challenges. Through Blueprint Labs and Avela, his work bridges academic research with practical applications in education policy and technology.

• Bioinformatics
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Ole Winther is Professor in High dimensional biological data analysis/Machine learning at the Department of Biology, University of Copenhagen and Professor in Data science and complexity at DTU Compute, Technical University of Denmark. He serves as CRO and co-founder of raffle.ai, CTO and co-founder of FindZebra, Head of ELLIS Unit Copenhagen, and co-PI of the Machine Learning for Life Science Center. His research spans Bioinformatics , Machine Learning , and AI for Science , focusing on applying deep learning to biological sequence analysis, latent variable models, and medical NLP. Winther's work develops predictive and generative models for bioinformatics, with significant contributions to protein localization tools (SignalP, DeepLoc, DeepTMHMM), single-cell genomics, and novel deep learning architectures like variational autoencoders and diffusion models. Analysis of Winther's recent publications (2023-2025) reveals a strong trend toward integrating protein language models with traditional bioinformatics approaches and applying diffusion models to scientific problems. His work bridges theoretical machine learning advancements with practical applications in biology and medicine, particularly in protein sequence analysis, medical search engines, and scientific simulation acceleration. Winther currently supervises a diverse research group including Panagiotis Antoniadis, Rachael M. DeVries, Jun Wang, Beatrix M. G. Nielsen, Felix G. Teufel, Irene R. Rodriguez, Anders Christensen, and Christopher Heje Grønbech. His former students have established successful careers at institutions including Google, Apple, and various startups, with notable alumni like Casper Sønderby (Google Brain) and Søren Sønderby (Apple). He leads significant research initiatives including the ELLIS Unit Copenhagen and the Machine Learning for Life Science Center, while maintaining active industry partnerships through his co-founded companies raffle.ai (enterprise search using NLP) and FindZebra (search engine for rare diseases). His teaching includes Deep Learning courses at both DTU (02456) and University of Copenhagen (NDAK24002U).

Ihab Ilyasمشاهده پروفایل

استاد

• Data Management
• Data Cleaning
• Machine Learning for Data Quality
• +۶ مورد دیگر

Professor Ihab Ilyas is a leading figure in data management and machine learning at the Cheriton School of Computer Science , University of Waterloo , where he holds the Thomson Reuters Research Chair in Data Quality . He is currently on leave from the university, serving as a Distinguished Engineer, Proactive Intelligence at Apple Inc . His research focuses on data cleaning , large-scale data integration , knowledge graphs , and machine learning applications in data quality . He has pioneered systems like HoloClean and Saga , with commercial impacts through co-founded startups Inductiv (acquired by Apple) and Tamr . PhD in Computer Science from Purdue University Co-founder of Inductiv (acquired by Apple) Co-founder of Tamr Research Interests include: Probabilistic and uncertain data management Machine learning for data quality and enrichment Big data systems and information extraction Knowledge graph construction and optimization Scientific Awards and Recognitions include: Fellow of the Royal Society of Canada (2024) C.C. Gotlieb Computer Award (2024) IEEE Fellow (2021) ACM Fellow (2020) Cheriton Faculty Fellowship (2013-2016) Ontario Early Researcher Award

Asaf Cidonمشاهده پروفایل

دانشیار

• Software Systems
• Storage Systems
• Machine Learning
• +۴ مورد دیگر

Asaf Cidon is an Associate Professor at Columbia University, jointly affiliated with the Department of Electrical Engineering and Computer Science, and a member of the Data Science Institute. His research focuses on software systems , storage , large-scale machine learning , and cybersecurity . Stanford University - PhD in Electrical Engineering Stanford University - MS in Electrical Engineering Technion - BS in Computer and Software Engineering His work in distributed storage systems has been commercialized by companies such as Facebook, Tibco, and Rubrik. He has led projects like Sentinel and Forensics during his industry career. Recent publications highlight advancements in software-based radiation protection (ASPLOS'26), PCIe pooling with CXL (HotOS'25), and AI phishing detection (IMC'25). These reflect his expertise in system architecture , security , and networking . Scientific recognitions include best paper awards at OSDI, Usenix Security, CIDR, and ATC, along with NSF CAREER and ARO Young Investigator Awards . His papers Cookie Monster (SOSP'24) and Chablis (CIDR'24) received notable accolades. He has mentored numerous PhD and Master's students , including Edward Guo, Harry Wang, and Teng Jiang, many of whom now hold roles at Google, Meta, Amazon, and academic institutions. His lab at Columbia is actively recruiting CS and EE PhD students. Prior to Columbia, he founded and led the startup Sookasa to acquisition and served as Senior Vice President of Email Protection at Barracuda Networks , managing a $200M business with 100 engineers.

David M. Dodsonمشاهده پروفایل

مدرس

• Entrepreneurship
• Business Management
• Entrepreneurial Acquisition
• +۳ مورد دیگر

David M. Dodson is a Lecturer in Management at Stanford University’s Graduate School of Business (GSB), where he teaches courses on managing growing enterprises and entrepreneurial acquisition. His career spans over 30 years in business management, including founding three search funds and serving as CEO of a technology manufacturer and Executive Chairman of a telecommunications firm. He co-founded Sanku (formerly Project Healthy Children), a nonprofit addressing micronutrient deficiencies in Africa through fortified grains, recognized for its life-saving impact. Dodson holds an MBA from Stanford GSB (1987) and a BA in Economics from Stanford University (1983). His research focuses on entrepreneurial acquisition strategies and managing small-to-medium enterprises. Notable awards include the MSx Teaching Excellence Award (2023, 2021) and recognition as a top lecturer by Stanford GSB students. Beyond academia, he invests in over 40 businesses and serves on 21 corporate boards. In 2020, he founded StudentVotes.org to empower student voting during the pandemic. His media contributions include columns for The Boston Globe and frequent TV commentary on CNBC and Fox Business.

Kristin Baker Spohnمشاهده پروفایل

مدرس

• Healthcare Technology
• Startup Development
• Digital Health Innovations
• +۳ مورد دیگر

Kristin Baker Spohn is a Lecturer in Management at the Stanford Graduate School of Business (GSB) and a General Partner at CRV, focusing on healthcare and technology startups. She has extensive experience as an operator and investor, leading roles at Collective Health and Castlight Health, and driving investments in ventures like Viz.ai and Marley Medical. Education: MBA, Stanford Graduate School of Business, 2010 BA, Middlebury College, 2005 Research Interests: Healthcare technology innovation, digital health equity, and policies enabling startup-driven healthcare access. Her work bridges translational research and commercialization, emphasizing scalable solutions for systemic healthcare challenges. Teaching: Teaches courses such as Startup Garage: Design and Testing and Launch , focusing on entrepreneurship and scalable business models. Affiliated with the Stanford-Coulter Translational Research Grant Committee.

Anwar Haqueمشاهده پروفایل

دانشیار

• Network Security
• 5G and Beyond Networks
• IoT
• +۹ مورد دیگر

Dr. Anwar Haque is an Associate Professor in the Department of Computer Science at Western University, Canada, and a Faculty of Science Distinguished Research Professor. He holds a Ph.D. in Electrical and Computer Engineering and an M.Sc. in Computer Science from the University of Waterloo. Prior to academia, he was Associate Director at Bell Canada. His research focuses on 5G networks, IoT, cybersecurity, AI, and autonomous systems, with over 100 peer-reviewed publications and $15M in collaborative grants. Dr. Haque leads the Western Information & Networking Group (WING) Lab and is the founder/CEO of Bamboo Innovations Inc., a tech startup developing socially responsible smart technologies. Leadership roles include industry expert-in-residence in the Faculty of Science, Undergraduate Chair of the Computer Science Department, and member of Western’s Senate. He has delivered over 30 keynote talks and media features include BBC Earth and The Globe and Mail. Awards include the IEEE CCECE Leadership Award and multiple grants from NSERC, MITACS, and Bell Canada. His work spans network reliability, smart grids, and cybersecurity, with industry partnerships like the Bell-Western 5G Research Centre.

Felipe Csaszarمشاهده پروفایل

استاد

• Strategic Management
• Artificial Intelligence
• Organizational Behavior
• +۳ مورد دیگر

Felipe Csaszar is a Professor of Strategy and Chair of the Strategy Department at the University of Michigan's Ross School of Business. His research focuses on decision structures' impact on innovation, financial performance, and social outcomes, with particular attention to cognitive frameworks, organizational processes, and AI's role in decision-making. He holds a PhD and MA from the Wharton School, University of Pennsylvania. Education: PhD in Strategy, University of Pennsylvania (2009) MA in Strategy, University of Pennsylvania (2007) Research Interests: Strategic decision-making under AI integration Cognitive and structural drivers of innovation Organizational decision processes and design Formal modeling and empirical strategy research Editorial Roles: Senior Editor, Strategy Science and Management Science Former Editor, Organization Science Co-editor, Handbook of AI and Strategy Professional Experience: Prior role: Assistant Professor at INSEAD Previous career: CEO of an internet startup and Head of Research at an asset management firm Labs/Teams: Leading the Strategy Science division at INFORMS Co-chair of the SMS Behavioral Strategy division

Stefanos Zeniosمشاهده پروفایل

استاد

• Operations Research
• Innovation
• Entrepreneurship
• +۳ مورد دیگر

Stefanos Zenios is Professor at Stanford Graduate School of Business with dual appointments in Entrepreneurship and Operations, Information & Technology . He directs Stanford GSB’s Center for Entrepreneurial Studies and co-directs the Doerr School of Sustainability ’s Program in Ecopreneurship. His Startup Garage course has launched companies like DoorDash while alumni have raised over $3B in venture capital. He co-authored the foundational Biodesign textbook and previously served as Editor-in-Chief of Operations Research . PhD, MIT Operations Research (1996) MA, University of Cambridge (1996) BA, University of Cambridge (1992) Research Focus Dr. Zenios’ work bridges operations research and innovation management , with significant contributions to: Healthcare operations : Administrative cost reduction, organ allocation optimization, and clinical workflow improvements Entrepreneurship : Venture creation frameworks and experiential education Ecopreneurship : Sustainable business model innovation His Precedents Thinking framework (HBR 2025) has gained global recognition for solving systemic inefficiencies. Current research includes the biennial Search Fund Study with Peter Kelly. Scientific Recognition INFORMS Fellow Multiple Best Paper Awards, INFORMS CAREER Award, National Science Foundation (2000) Dhirubhai Ambani Faculty Fellow (2017–2020) George E. Nicholson Award (1997) He has received extensive media coverage in Fast Company , Time Magazine , and Stanford Business . His research has been featured in over 150 press mentions including JAMA , Harvard Business Review , and Health Affairs .

Supratik Guhaمشاهده پروفایل

استاد

• Quantum Computing
• Semiconductor Materials
• Sensor Networks
• +۴ مورد دیگر

Supratik Guha is a Professor at the Pritzker School of Molecular Engineering and Senior Advisor to Argonne National Laboratory's Physical Sciences and Engineering directorate. His work bridges industrial R&D with academic and national lab research, focusing on quantum computing , semiconductor materials , and sensor networks for water and soil monitoring. Guha leads Argonne’s quantum information science strategy and serves as Faculty Director for the University of Chicago Center in Delhi. Education: PhD in Materials Science (USC, 1991), BTech in Engineering Physics (IIT Kharagpur, 1985) Research interests span multiple domains: Quantum technologies focusing on erbium-doped oxides for quantum memory and quantum interconnects Sensor networks for soil and water quality monitoring using cyberphysical systems Nanofabrication techniques including controlled spalling for heterogeneous material integration Advanced memory technologies exploring ferroelectric and optically addressable memory at atomic scales Scientific awards include: Election to National Academy of Engineering (2015) APS Prize for Industrial Applications of Physics (2015) Vannevar Bush Faculty Fellow (2018) Fellow of Materials Research Society and American Physical Society IBM Corporate Award (2013) Advising notable students like Manish Kumar Singh (co-founder memQ ), Cheng Ji (now at Intel), and Vamsi Nittala (now at Micron Technology). His group contributes to major DOE , NSF , and USDA funded projects including: Q-NEXT - DOE National Quantum Information Center AIFARMS - NSF/USDA AI for Agriculture Institute Thoreau Project - Geospatial sensor networks Labs and teams operate across University of Chicago and Argonne National Lab , with facilities for molecular beam epitaxy , nanofabrication , and optical/electrical characterization . The group has spawned startups like memQ (quantum networking) and K1 Semiconductors (wide-bandgap material transfer).

Min Huمشاهده پروفایل

استادیار

• Health Economics
• Applied Microeconomics
• Labour Economics
• +۷ مورد دیگر

Min Hu is an Assistant Professor in the Department of Economics, Philosophy, and Political Science at the University of British Columbia, Okanagan Campus. He holds an adjunct position at Dalhousie University's School of Health Administration. His primary research focuses on Health Economics, Applied Microeconomics, and Labour Economics, with an emphasis on vulnerable populations in Canada, Indigenous health, income inequalities, and cancer economics. He teaches courses in Microeconomics, Health Economics, and Statistics. Education: PhD in Economics (2019), Dalhousie University; Postdoctoral Fellowship in Health Economics (2019–2020), Dalhousie University. Previous degrees include an M.A. (2014–2016) and B.A. in Economics from Dalhousie University. Research interests include the socio-economic determinants of health disparities, particularly among Indigenous peoples and immigrants, and the economic impacts of cancer-related policies. He employs applied econometric methods to analyze labor market outcomes and social policy effectiveness. His recent articles explore sustainable biomass utilization, energy policies, and environmental engineering innovations. Key themes include biomass supply chain optimization, CO₂ reduction strategies, and waste-to-energy technologies. Scientific Awards: Recipient of SSHRC New Frontiers Grant (2023–2026), CIHR Team Grant (2024–2026), and multiple UBC startup grants. His work is supported by SSHRC, CRDCN, and Indigenous Services Canada. He advises students in Economics and Global Studies (IGS) programs. Grants and funding span health economics, Indigenous well-being, and sustainable energy systems. Collaborations include interdisciplinary teams in health administration and environmental policy. Labs/Teams: Engaged with UBC's Okanagan Sustainability Initiatives and Dalhousie's Health Economics Research Group. Affiliated with professional organizations like the American Economic Association and Canadian Health Economics Study Group.

Kenan Arifogluمشاهده پروفایل

دانشیار

• Healthcare Management
• Supply-Chain Management
• Pricing and Revenue Management
• +۳ مورد دیگر

Dr. Kenan Arifoglu is an Associate Professor at the UCL School of Management. He previously held a postdoctoral position at the Ross Business School, University of Michigan (2008–2012). His education includes a PhD in Industrial Engineering and Management Sciences from Northwestern University (2012), two MSc degrees from Northwestern University (2008) and Koç University (2007), and a BSc from Koç University (2005). His research focuses on behavioral motivations in healthcare, supply chains, pricing, and entrepreneurial operations. Key projects include analyzing inefficiencies in flu vaccine supply chains and developing frameworks for high-growth startups. His work bridges operations management with practical challenges in healthcare, retail, and entrepreneurship. Recent publications address topics such as luxury brand licensing dynamics, incentive programs in healthcare systems, and the theoretical foundations of lean startup methodologies. These contributions span disciplines like marketing, operations research, and public health, emphasizing cross-sectoral applications. Dr. Arifoglu’s advising and grant activities are not detailed here. He is affiliated with the UCL School of Management and actively contributes to academic discourse through his research and teaching roles.

Soroush Saghafianمشاهده پروفایل

دانشیار

• Operations Research
• Healthcare Delivery Optimization
• Public Policy Analytics
• +۳ مورد دیگر

Soroush Saghafian is an Associate Professor of Public Policy at Harvard Kennedy School, specializing in applying operations research and machine learning to address public health challenges. He leads the Public Impact Analytics Science Lab (PIAS-Lab), focusing on analytics-driven solutions for societal problems. His research spans healthcare delivery optimization, emergency department efficiency, and public health policy. Notable collaborations include Massachusetts General Hospital and Harvard's Center for Health Decision Science. Awards include the INFORMS MSOM Responsible Research Award and the Pierskalla Award for healthcare research. Recent work includes studies on hospital closures' impacts, predictive analytics for bipolar disorder using Fitbit data, and policy implications of race in disease risk models. He teaches courses on machine learning and big data for public impact.

• AI for Business
• Data Science
• Responsible AI
• +۵ مورد دیگر

David Martens is a Professor of Data Science at the University of Antwerp , where he directs the Applied Data Mining Research Group within the Faculty of Business and Economics . He also serves as Chair of the Department of Engineering Management and Director of the Antwerp Center on Responsible AI . His academic work spans data mining , interpretable machine learning , and the societal impact of AI . PhD in Applied Economic Sciences (KU Leuven, 2008) Director, Antwerp Center on Responsible AI Chair, Department of Engineering Management Martens' research focuses on responsible AI and data ethics , with applications in finance, public policy, and behavioral analysis. His recent publications emphasize counterfactual explanations , LLM interpretability , and privacy implications in AI systems. His articles reveal trends in Explainable AI (XAI) , including narrative-driven explanations , graph neural networks , and ethical challenges like monetization risks and algorithmic bias. Keywords span Computer Science , Artificial Intelligence , and Behavioral Data . Martens is a leading voice in data science ethics , authoring the book Data Science Ethics: Concepts, Techniques, and Cautionary Tales (Oxford University Press, 2022). He combines academic rigor with industry experience, having consulted for banks, telecom firms, and startups in fraud detection and digital advertising .