Yoonkyung Lee | |
---|---|
Alma mater | Seoul National University University of Wisconsin-Madison |
Known for | kernel method dimensionality reduction machine learning |
Scientific career | |
Fields | Statistics |
Thesis | Multicategory Support Vector Machines, Theory, and Application to the Classification of Microarray Data and Satellite Radiance Data (2002) |
Doctoral advisor | Grace Wahba |
Yoonkyung Lee is a professor of statistics at Ohio State University, and also holds a courtesy appointment in computer science and engineering at Ohio State. Her research takes a statistical approach to kernel methods, dimensionality reduction, and regularization in machine learning.
Lee earned bachelor's and master's degrees in computer science and statistics from Seoul National University in Korea in 1994 and 1996. [1] She completed her Ph.D. in statistics in 2002 at the University of Wisconsin–Madison, under the supervision of Grace Wahba and Yi Lin, with a dissertation about support vector machines and their applications to microarray and satellite data. [1] [2] She joined the Ohio State faculty in 2002 and was promoted to full professor in 2016. [1]
In 2015, Lee was elected as a Fellow of the American Statistical Association "for fundamental and influential research on the multicategory support vector machine; for work at the edge of statistics and computer science and building a bridge between the statistics and machine learning communities; and for editorial and program committee service to the profession." [3] [4]
Vladimir Naumovich Vapnik is a computer scientist, researcher, and academic. He is one of the main developers of the Vapnik–Chervonenkis theory of statistical learning and the co-inventor of the support-vector machine method and support-vector clustering algorithms.
Michael Irwin Jordan is an American scientist, professor at the University of California, Berkeley and researcher in machine learning, statistics, and artificial intelligence.
Manuela Maria Veloso is the Head of J.P. Morgan AI Research & Herbert A. Simon University Professor in the School of Computer Science at Carnegie Mellon University, where she was previously Head of the Machine Learning Department. She served as president of Association for the Advancement of Artificial Intelligence (AAAI) until 2014, and the co-founder and a Past President of the RoboCup Federation. She is a fellow of AAAI, Institute of Electrical and Electronics Engineers (IEEE), American Association for the Advancement of Science (AAAS), and Association for Computing Machinery (ACM). She is an international expert in artificial intelligence and robotics.
Richard John Samworth is the Professor of Statistical Science and the Director of the Statistical Laboratory, University of Cambridge, and a Teaching Fellow of St John's College, Cambridge. He was educated at St John's College, Cambridge. His main research interests are in nonparametric and high-dimensional statistics. Particular topics include shape-constrained density estimation and other nonparametric function estimation problems, nonparametric classification, clustering and regression, the bootstrap and high-dimensional variable selection problems.
Jerome Harold Friedman is an American statistician, consultant and Professor of Statistics at Stanford University, known for his contributions in the field of statistics and data mining.
Eric Poe Xing is an American computer scientist, academic administrator, and entrepreneur. Prior to his appointment as President of MBZUAI, Xing was a professor in the School of Computer Science at Carnegie Mellon University and researcher in machine learning, computational biology, and statistical methodology. Xing is also the Founder, Chairman, Chief Scientist, and former CEO of Petuum Inc.
William Swain Cleveland II is an American computer scientist and Professor of Statistics and Professor of Computer Science at Purdue University, known for his work on data visualization, particularly on nonparametric regression and local regression.
Vanja Dukic is an expert in computational statistics and mathematical epidemiology who works as a professor of applied mathematics at the University of Colorado Boulder. Her research includes work on using internet search engine access patterns to track diseases, and on the effects of climate change on the spread of diseases.
Catherine Ann Sugar is an American biostatistician at the University of California, Los Angeles, where she is Professor in Residence in the Departments of Biostatistics, Statistics and Psychiatry and director of the biostatistics core for the Semel Institute for Neuroscience and Human Behavior. Her research concerns cluster analysis, covariance, and the applications of statistics in medicine and psychiatry.
Grace Yun Yi is a professor of the University of Western Ontario where she currently holds a Tier I Canada Research Chair in Data Science. She was a professor at the University of Waterloo, Canada, where she holds a University Research Chair in Statistical and Actuarial Science. Her research concerns event history analysis with missing data and its applications in medicine, engineering, and social science.
Catherine A. "Kate" Calder is an American statistician who works as chair of Statistics and Data Sciences at the University of Texas at Austin. She was previously a professor of statistics at Ohio State University. Calder earned a bachelor's degree in mathematics from Northwestern University in 1999, and completed her Ph.D. in statistics from Duke University in 2003 under the joint supervision of David Higdon and Michael L. Lavine. She joined the Ohio State faculty in 2003, and was promoted to full professor in 2015.
Yulia R. Gel is a professor in the Department of Mathematical Sciences at the University of Texas at Dallas and an adjunct professor in the Department of Statistics and Actuarial Science of the University of Waterloo.
Elizaveta (Liza) Levina is a Russian and American mathematical statistician. She is the Vijay Nair Collegiate Professor of Statistics at the University of Michigan, and is known for her work in high-dimensional statistics, including covariance estimation, graphical models, statistical network analysis, and nonparametric statistics.
Peiyong "Annie" Qu is a Chinese-American statistician known for her work on estimating equations and semiparametric models. Her research interests also include longitudinal analysis, nonparametric statistics and robust statistics, missing data, and biostatistics.
Deborah Jean Rumsey-Johnson is an American statistician and statistics educator. She is an associated professor and program specialist in statistics at the Ohio State University.
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.
Kary Lynn Myers is an American statistician whose research has included work on scientific data analysis and radiation monitoring. She is a scientist at the Los Alamos National Laboratory, where she has been the deputy leader of the Statistical Sciences group. She is also known as the founder and organizer of the biennial Conference on Data Analysis (CoDA), for data-driven research within the United States Department of Energy.
Kellie Jo Archer is a biostatistician specializing in microarray analysis techniques. She is a professor of biostatistics and chair of the biostatistics department at the Ohio State University.
Rui Song is a Chinese-American statistician. Her research interests include machine learning, causal inference, and independence screening for variable selection, with applications to precision medicine and economics. She works for Amazon as a senior principal scientist.
Genevera Irene Allen is an American statistician whose research has involved interpretable machine learning, the reproducibility of machine learning results, and the neuroscience of synesthesia. She is an associate professor of electrical and computer engineering, statistics, and computer science at Rice University, and also holds affiliations with Texas Children's Hospital and the Baylor College of Medicine.