جستجوی استاد راهنمای دانشگاهی

René Vidalمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Biomedical Data Science
• +۳ مورد دیگر

René Vidal is the Rachleff & Penn Integrates Knowledge (PIK) University Professor at the University of Pennsylvania, with appointments in the Departments of Electrical and Systems Engineering, Radiology, Computer and Information Science, and Statistics and Data Science. He also serves as Director of the Center for Innovation in Data Engineering and Science (IDEAS) and the NSF-Simons Collaboration on the Mathematical Foundations of Deep Learning (THEORINET). A dual faculty member at Johns Hopkins University in Biomedical Engineering, Computer Science, and other departments, Vidal is an Amazon Scholar and Affiliated Chief Scientist at NORCE. PhD, Electrical Engineering and Computer Sciences, University of California, Berkeley (2003) M.S., Electrical Engineering, University of California, Berkeley (2000) B.S. (valedictorian), Electrical Engineering, Pontificia Universidad Catolica de Chile (1997) His research spans the mathematical foundations of deep learning, focusing on non-convex optimization , learning dynamics , and overparametrization . Key contributions include Sparse Subspace Clustering , Kernel GPCA , and Low-Rank Matrix Factorization , with applications in autism diagnosis , robotic surgery , and cardiac imaging . Recent work explores continual learning , adversarial robustness , and trustworthy AI in biomedical contexts. His 15 most recent publications highlight advances in medical imaging , language models , and robust computer vision , spanning topics from chest X-ray analysis to motor imitation tasks in autism . Articles like Geometric Analysis of Nonlinear Manifold Clustering underscore his theoretical contributions, while works on KDA: Knowledge-Distilled Attacker and Conformal Information Pursuit address practical AI safety and interpretability. Scientific accolades include: 2022 ACM Fellow 2021 IEEE McCluskey Technical Achievement Award 2017 Jean D’Alembert Fellowship 2012 J.K. Aggarwal Prize 2009 Sloan Research Fellow 2005 NSF CAREER Award His lab mentors 11 current PhD students across Johns Hopkins and University of Pennsylvania , with alumni contributing to institutions like Meta , Amazon , and GE Research . Vidal’s interdisciplinary work bridges mathematics , engineering , and healthcare , supported by grants from the DoD , NSF , and ONR .

• Natural Language Processing
• Knowledge Representation
• Question Answering
• +۶ مورد دیگر

Bhuwan Dhingra is an Assistant Professor of Computer Science at Duke University's Pratt School of Engineering. He also serves as a Research Scientist at Google Deepmind, where he spends summers working on AI research. His research focuses on natural language processing, knowledge representation, and machine learning. Dr. Dhingra completed his PhD in 2020 from the Language Technologies Institute at Carnegie Mellon University under the supervision of William Cohen and Russ Salakhutdinov. Prior to that, he earned his degree in Electrical Engineering from IIT Kanpur, where he worked with Amitabha Mukerjee. He also has industry experience from working at Qualcomm Research in San Diego. His research interests span multiple areas within NLP and AI, with a particular focus on question answering and information retrieval, reasoning over structured and unstructured knowledge, robustness to corrupted text inputs, misinformation and propaganda detection, and model calibration for inherently subjective NLP tasks. His work often bridges the gap between theoretical advances and practical applications, as evidenced by his industry collaborations and grants. Dr. Dhingra's recent publications indicate a strong focus on large language models, factuality assessment, knowledge attribution, public health content analysis, and efficient model training techniques. His research trajectory shows an evolution from foundational NLP work to more complex applications involving multimodal learning, reasoning, and societal impact. Amazon Research Award for 'Long-form QA via collaborative writing' NSF Medium grant with Jun Yang and Lavanya Vasudevan Learning Engineering Virtual Institute grant (joint with University of Florida) Gift from P&G for exploring search interfaces based on concept graphs Gift from Google for exploring NLP tools to combat misinformation Dr. Dhingra actively mentors students, with seven PhD students and four undergraduate/masters students listed on his page. Many of his former students have gone on to prestigious positions at Stanford, Nvidia, McKinsey, and Amazon. He teaches graduate-level courses in NLP and generative models at Duke University. His lab works on machine learning for natural language processing and knowledge representation, with current topics including question answering, reasoning over knowledge, robustness to corrupted inputs, misinformation detection, and model calibration.