Roni Rosenfeld | |
---|---|
Born | רוני רוזנפלד 1959 (age 63–64) |
Nationality | Israeli-American |
Education | Tel Aviv University University of Chicago Carnegie Mellon University |
Scientific career | |
Fields | Computer Science Statistical Epidemiology Machine Learning |
Institutions | |
Doctoral advisors | Raj Reddy Xuedong Huang |
Website | www |
Roni Rosenfeld is an Israeli-American computer scientist and computational epidemiologist, currently serving as the head of the Machine Learning Department at Carnegie Mellon University. [1] He is an international expert in machine learning, infectious disease forecasting, statistical language modeling and artificial intelligence. [2]
Rosenfeld received his B.Sc. in mathematics and physics from Tel Aviv University in 1985. He received his Ph.D. in computer science from Carnegie Mellon University in 1994. While a graduate student, he developed and open-sourced a statistical language-modeling toolkit to allow anyone to create statistical language models from their own corpora and experiment with and extend the toolkit's capabilities. [3] The toolkit has been used by more than 100 NLP laboratories in more than 20 countries. [4]
Rosenfeld's Ph.D. thesis, A Maximum Entropy Approach to Adaptive Statistical Language Modeling, [5] was advised by Raj Reddy and Xuedong Huang and won the 2001 Computer, Speech and Language award for "Most Influential Paper in the Last 5 Years." [6]
Shortly after receiving his Ph.D., Rosenfeld joined the faculty of the Carnegie Mellon School of Computer Science as an assistant professor. He was promoted to the rank of associate professor in 1999 and received tenure in 2001. [7] In 2005 he was promoted to professor of language technologies, machine learning computer science and computational biology in the School of Computer Science at Carnegie Mellon University. Rosenfeld also holds adjunct appointments at the University of Pittsburgh School of Medicine, department of computational and systems biology. [8] [9]
From 2002 to 2003, Rosenfeld was a visiting professor at the University of Hong Kong. [7]
Rosenfeld is the director of Carnegie Mellon's Machine Learning for Social Good (ML4SG) program. [10] He has held educational leadership positions in a variety of programs, including the M.S. in computational finance (1997–1999), graduate computational and statistical learning (2001–2003), M.S. in machine learning (2017) and undergraduate minor in machine learning. [7]
Rosenfeld was appointed Head of Carnegie Mellon's Machine Learning Department in 2018. [1]
Rosenfeld's research interests include epidemiological forecasting, information and communication technologies for development (ICT4D), and machine learning for social good. [11]
Rosenfeld is a world expert in epidemiological forecasting. [12] He founded and directs the Delphi research group, which has won most of the epidemiological forecasting challenges organized by the U.S. CDC and other U.S. government agencies. [13] In December 2016, the CDC named his group the "Most Accurate Forecaster" for 2015–2016, [14] and in October 2017, the Delphi group's two systems took the top two spots in the 2016-2017 flu forecasting challenge. [15] The CDC recognized Rosenfeld's Delphi group at Carnegie Mellon University as having contributed the most accurate national-, regional-, and state-level influenza-like illness forecasts and national-level hospitalization forecasts to the site. [16] [17] In 2019, the CDC recognized forecasts provided by the Delphi group at Carnegie Mellon as having been the most accurate for five seasons in a row, [18] and named the Delphi group an Influenza Forecasting Center of Excellence, a five-year designation that includes $3 million in research funding. [19]
Rosenfeld describes his forecasting research goal as "to make epidemiological forecasting as universally accepted and useful as weather forecasting is today." [20] His recent work in the area has focused on selecting high value epidemiological forecasting targets (e.g. Influenza and Dengue); creating baseline forecasting methods for them; establishing metrics for measuring and tracking forecasting accuracy; estimating the limits of forecastability for each target; and identifying new sources of data that could be helpful to the forecasting goal.
Carnegie Mellon University (CMU) is a private research university in Pittsburgh, Pennsylvania. The institution was originally established in 1900 by Andrew Carnegie as the Carnegie Technical Schools. In 1912, it became the Carnegie Institute of Technology and began granting four-year degrees. In 1967, it became the current-day Carnegie Mellon University through its merger with the Mellon Institute of Industrial Research, founded in 1913 by Andrew Mellon and Richard B. Mellon and formerly a part of the University of Pittsburgh.
The School of Computer Science (SCS) at Carnegie Mellon University in Pittsburgh, Pennsylvania, US is a school for computer science established in 1988. It has been consistently ranked among the top computer science programs over the decades. As of 2022 U.S. News & World Report ranks the graduate program as tied for second with Stanford University and University of California, Berkeley. It is ranked second in the United States on Computer Science Open Rankings, which combines scores from multiple independent rankings.
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Jaime Guillermo Carbonell was a computer scientist who made seminal contributions to the development of natural language processing tools and technologies. His extensive research in machine translation resulted in the development of several state-of-the-art language translation and artificial intelligence systems. He earned his B.S. degrees in Physics and in Mathematics from MIT in 1975 and did his Ph.D. under Dr. Roger Schank at Yale University in 1979. He joined Carnegie Mellon University as an assistant professor of computer science in 1979 and lived in Pittsburgh from then. He was affiliated with the Language Technologies Institute, Computer Science Department, Machine Learning Department, and Computational Biology Department at Carnegie Mellon.
Kathleen M. Carley is an American computational social scientist specializing in dynamic network analysis. She is a professor in the School of Computer Science in the Carnegie Mellon Institute for Software Research at Carnegie Mellon University and also holds appointments in the Tepper School of Business, the Heinz College, the Department of Engineering and Public Policy, and the Department of Social and Decision Sciences.
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Chris Harrison is a British-born, American computer scientist and entrepreneur, working in the fields of human–computer interaction, machine learning and sensor-driven interactive systems. He is a professor at Carnegie Mellon University and director of the Future Interfaces Group within the Human–Computer Interaction Institute. He has previously conducted research at AT&T Labs, Microsoft Research, IBM Research and Disney Research. He is also the CTO and co-founder of Qeexo, a machine learning and interaction technology startup.
Geoffrey J. Gordon is a professor at the Machine Learning Department at Carnegie Mellon University in Pittsburgh and director of research at the Microsoft Montréal lab. He is known for his research in statistical relational learning and on anytime dynamic variants of the A* search algorithm. His research interests include multi-agent planning, reinforcement learning, decision-theoretic planning, statistical models of difficult data, computational learning theory, and game theory.
Jian Ma is an American computer scientist and computational biologist. He is the Ray and Stephanie Lane Professor of Computational Biology in the School of Computer Science at Carnegie Mellon University. He is a faculty member in the Computational Biology Department. His lab develops machine learning algorithms to study the structure and function of the human genome. During his Ph.D. and postdoc training, he developed algorithms to reconstruct the ancestral mammalian genome. His research group has recently pioneered a series of new machine learning methods for 3D epigenomics and spatial genomics. He received an NSF CAREER award in 2011. In 2020, he was awarded a Guggenheim Fellowship in Computer Science. He is an elected Fellow of the American Association for the Advancement of Science. He leads an NIH 4D Nucleome Center to develop machine learning algorithms to better understand the cell nucleus.
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Maria-Florina (Nina) Balcan is a Romanian-American computer scientist whose research investigates machine learning, algorithmic game theory, theoretical computer science, including active learning, kernel methods, random-sampling mechanisms and envy-free pricing. She is an associate professor of computer science at Carnegie Mellon University.
Shirley Ho is an American astrophysicist and machine learning expert, currently at the Center for Computational Astrophysics at Flatiron Institute in NYC and at the New York University and the Carnegie Mellon University. Ho also has visiting appointment at Princeton University.
Cleotilde Gonzalez is a Research Professor of Decision Sciences in the Social and Decision Sciences Department. She is also the founding director of the Dynamic decision-making laboratory at Carnegie Mellon University. Gonzalez is also affiliated with the Security and Privacy Institute (CyLab), the Center for Behavioral Decision Research (CBDR), the Human Computer Interaction Institute, the Center for Cognitive Brain Imaging, and the Center for Neural Basis of Cognition.
Elizabeth A. Holm is a materials scientist at Carnegie Mellon University, working on computational materials. She worked at Sandia National Laboratories for 20 years before joining the faculty of Carnegie Mellon in 2012. She is a Fellow of The Minerals, Metals & Materials Society and Fellow of ASM International. She was the 2013 President of the society. She is internationally known for her theory and modeling work on microstructural response, interfaces, carbon nanotubes, and additive manufacturing.