Related Research Articles
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. Recently, artificial neural networks have been able to surpass many previous approaches in performance.
Ray Solomonoff was an American mathematician who invented algorithmic probability, his General Theory of Inductive Inference, and was a founder of algorithmic information theory. He was an originator of the branch of artificial intelligence based on machine learning, prediction and probability. He circulated the first report on non-semantic machine learning in 1956.
Michael Irwin Jordan is an American scientist, professor at the University of California, Berkeley, research scientist at the Inria Paris, and researcher in machine learning, statistics, and artificial intelligence.
Daphne Koller is an Israeli-American computer scientist. She was a professor in the department of computer science at Stanford University and a MacArthur Foundation fellowship recipient. She is one of the founders of Coursera, an online education platform. Her general research area is artificial intelligence and its applications in the biomedical sciences. Koller was featured in a 2004 article by MIT Technology Review titled "10 Emerging Technologies That Will Change Your World" concerning the topic of Bayesian machine learning.
Zoubin Ghahramani FRS is a British-Iranian researcher and Professor of Information Engineering at the University of Cambridge. He holds joint appointments at University College London and the Alan Turing Institute. and has been a Fellow of St John's College, Cambridge since 2009. He was Associate Research Professor at Carnegie Mellon University School of Computer Science from 2003–2012. He was also the Chief Scientist of Uber from 2016 until 2020. He joined Google Brain in 2020 as senior research director. He is also Deputy Director of the Leverhulme Centre for the Future of Intelligence.
Stephen Malvern Omohundro is an American computer scientist whose areas of research include Hamiltonian physics, dynamical systems, programming languages, machine learning, machine vision, and the social implications of artificial intelligence. His current work uses rational economics to develop safe and beneficial intelligent technologies for better collaborative modeling, understanding, innovation, and decision making.
Dimitri Panteli Bertsekas is an applied mathematician, electrical engineer, and computer scientist, a McAfee Professor at the Department of Electrical Engineering and Computer Science in School of Engineering at the Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, and also a Fulton Professor of Computational Decision Making at Arizona State University, Tempe.
Probabilistic programming (PP) is a programming paradigm in which probabilistic models are specified and inference for these models is performed automatically. It represents an attempt to unify probabilistic modeling and traditional general purpose programming in order to make the former easier and more widely applicable. It can be used to create systems that help make decisions in the face of uncertainty.
Jun S. Liu is a Chinese-American statistician focusing on Bayesian statistical inference, statistical machine learning, and computational biology. He was assistant professor of statistics at Harvard University from 1991 to 1994. From 1994 to 2004, he was Assistant, Associate, and full Professor of Statistics at Stanford University. Since 2000, Liu has been Professor of Statistics in the Department of Statistics at Harvard University and held a courtesy appointment at Harvard T.H. Chan School of Public Health.
Stuart Alan Geman is an American mathematician, known for influential contributions to computer vision, statistics, probability theory, machine learning, and the neurosciences. He and his brother, Donald Geman, are well known for proposing the Gibbs sampler, and for the first proof of convergence of the simulated annealing algorithm.
Eric Poe Xing is an American computer scientist whose research spans machine learning, computational biology, and statistical methodology. Xing is founding President of the world’s first artificial intelligence university, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI).
Regina Barzilay is an Israeli-American computer scientist. She is a professor at the Massachusetts Institute of Technology and a faculty lead for artificial intelligence at the MIT Jameel Clinic. Her research interests are in natural language processing and applications of deep learning to chemistry and oncology.
Tamara Ann Broderick is an American computer scientist at the Massachusetts Institute of Technology. She works on machine learning and Bayesian inference.
Animashree (Anima) Anandkumar is the Bren Professor of Computing at California Institute of Technology. Previously, she was a senior director of Machine Learning research at NVIDIA and a principal scientist at Amazon Web Services. Her research considers tensor-algebraic methods, deep learning and non-convex problems.
Finale Doshi-Velez is a computer scientist and the John L. Loeb Professor of Engineering and Applied Sciences at Harvard University. She works on machine learning, computational statistics and healthcare.
Cynthia Diane Rudin is an American computer scientist and statistician specializing in machine learning and known for her work in interpretable machine learning. She is the director of the Interpretable Machine Learning Lab at Duke University, where she is a professor of computer science, electrical and computer engineering, statistical science, and biostatistics and bioinformatics. In 2022, she won the Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI) for her work on the importance of transparency for AI systems in high-risk domains.
Rina Foygel Barber is an American statistician whose research includes works on the Bayesian statistics of graphical models, false discovery rates, and regularization. She is the Louis Block Professor of statistics at the University of Chicago.
Thomas L. Griffiths is an Australian academic who is the Henry R. Luce Professor of Information Technology, Consciousness, and Culture at Princeton University. He studies human decision-making and its connection to problem-solving methods in computation. His book with Brian Christian, Algorithms to Live By: The Computer Science of Human Decisions, was named one of the "Best Books of 2016" by MIT Technology Review.
Guosheng Yin is a statistician, data scientist, educator and researcher in Biostatistics, Statistics, machine learning, and AI. Presently, Guosheng Yin is Chair in Statistics in Department of Mathematics at Imperial College London. Previously, he served as the Head of Department and the Patrick S C Poon Endowed Chair in Statistics and Actuarial Science, at the University of Hong Kong. Before he joined the University of Hong Kong, Yin worked at the University of Texas M.D. Anderson Cancer Center till 2009 as a tenured Associate Professor of Biostatistics.
Causal AI is a technique in artificial intelligence that builds a causal model and can thereby make inferences using causality rather than just correlation. One practical use for causal AI is for organisations to explain decision-making and the causes for a decision.
References
- 1 2 "Emily Fox will be Statistics' newest professor", Department of Statistics, Stanford University, March 18, 2021, retrieved 2024-06-12
- 1 2 3 4 5 Curriculum vitae, Stanford University, September 3, 2022, retrieved 2024-06-12
- ↑ Emily B. Fox at the Mathematics Genealogy Project
- ↑ insitro Hires AI and Machine Learning Visionary, Emily Fox, Ph.D., as Senior Vice President of AI/ML (Press release), insitro, April 30, 2024, retrieved 2024-06-12– via Businesswire
- ↑ 2024 IMS Fellows Announced, Institute of Mathematical Statistics, May 17, 2024, retrieved 2024-06-12
