Biography:Bin Yu
Bin Yu | |
|---|---|
郁彬 | |
| Education | Peking University (BA, 1984) University of California, Berkeley (MS, 1987; PhD, 1990) |
| Awards | IMS Fellow (1999) IEEE Fellow (2001) ASA Fellow (2005) AAAS Fellow (2013) Member of NAS (2014) Elizabeth L. Scott Award (2018) |
| Scientific career | |
| Fields | Statistics Machine Learning |
| Institutions | University of California, Berkeley University of Wisconsin–Madison Bell Labs |
| Website | www |
Bin Yu (Chinese: 郁彬) is a Chinese-American statistician. She is currently Chancellor's Professor in the Departments of Statistics and of Electrical Engineering & Computer Sciences at the University of California, Berkeley.[1][2]
Biography
Yu earned a bachelor's degree in mathematics in 1984 from Peking University, and went on to pursue graduate studies in statistics at Berkeley, earning a master's degree in 1987 and a Ph.D. in 1990. Her dissertation, Some Results on Empirical Processes and Stochastic Complexity, was jointly supervised by Lucien Le Cam and Terry Speed.[3]
After postdoctoral studies at the Mathematical Sciences Research Institute and an assistant professorship at the University of Wisconsin–Madison, she returned to Berkeley as a faculty member in 1993, was tenured in 1997, and became Chancellor's Professor in 2006. She also worked at Bell Labs from 1998 to 2000, while on leave from Berkeley, and has held visiting positions at several other universities. She chaired the Department of Statistics at Berkeley from 2009 to 2012, and was president of the Institute of Mathematical Statistics in 2014.[1][2][4]
Research
Yu's work leverages computational developments to solve scientific problems by combining statistical machine learning approaches with the domain expertise of many collaborators, spanning many fields including statistics, machine learning, neuroscience, genomics, and remote sensing.[5] Her recent work has focused on solidifying a vision for data science, including a framework for veridical data science[6] and a framework for interpretable machine learning.[7] Yu has received recent news coverage regarding her veridical data science framework,[8] investigations into the theoretical foundations of deep learning,[9] and work forecasting COVID-19 severity in the US.[10]
Honors and awards
Yu is a fellow of the Institute of Mathematical Statistics, the IEEE, the American Statistical Association, the American Association for the Advancement of Science, the American Academy of Arts and Sciences, and the National Academy of Sciences.[1][2][11][12][13] In 2012, she was the Tukey Lecturer of the Bernoulli Society for Mathematical Statistics and Probability.[1][2] In 2018, she was awarded the Elizabeth L. Scott Award. She was invited to give the Breiman lecture at NeurIPS 2019 (formally known as NIPS), on the topic of veridical data science.[14][15][16][17]
References
- ↑ 1.0 1.1 1.2 1.3 Faculty biography, UC Berkeley, accessed 2020-10-18.
- ↑ 2.0 2.1 2.2 2.3 "Bin Yu", Amstatnews (American Statistical Association), August 1, 2012, http://magazine.amstat.org/blog/2012/08/01/people8_12/.
- ↑ Bin Yu at the Mathematics Genealogy Project
- ↑ Current officials , Institute of Mathematical Statistics, retrieved 2013-04-24.
- ↑ "Google Scholar Profile for Bin Yu". https://scholar.google.com/citations?user=xT19Jc0AAAAJ&hl=en&oi=ao.
- ↑ Yu, Bin; Kumbier, Karl (2019-11-12). "Veridical Data Science". PNAS 117 (8): 3920–3929. doi:10.1073/pnas.1901326117. PMID 32054788. PMC 7049126. https://www.pnas.org/content/pnas/117/8/3920.full.pdf.
- ↑ Murdoch, W. James; Singh, Chandan; Kumbier, Karl; Abbasi-Asl, Reza; Yu, Bin (2019-10-29). "Interpretable machine learning: definitions, methods, and applications". Proceedings of the National Academy of Sciences 116 (44): 22071–22080. doi:10.1073/pnas.1900654116. ISSN 0027-8424. http://arxiv.org/abs/1901.04592.
- ↑ "Bin Yu | Computing, Data Science, and Society". https://data.berkeley.edu/people/bin-yu.
- ↑ "UC Berkeley to lead $10M NSF/Simons Foundation program to investigate theoretical underpinnings of deep learning | Computing, Data Science, and Society". https://data.berkeley.edu/news/uc-berkeley-lead-10m-nsfsimons-foundation-program-investigate-theoretical-underpinnings-deep.
- ↑ "Getting the right equipment to the right people" (in en-US). https://engineering.berkeley.edu/news/2020/04/getting-the-right-equipment-to-the-right-people/.
- ↑ Honored fellows , Institute of Mathematical Statistics, retrieved 2013-04-24.
- ↑ Directory of IEEE Fellows , retrieved 2013-04-24.
- ↑ Newly elected members , American Academy of Arts and Sciences, April 2013, retrieved 2013-04-24.
- ↑ "Elizabeth L. Scott Award". https://community.amstat.org/copss/awards/scott.
- ↑ "Yu Award Release". 2018-07-12. https://bids.berkeley.edu/news/bin-yu-receives-prestigious-elizabeth-l-scott-award.
- ↑ "Yu Award Release". 2018-09-11. https://www.ipam.ucla.edu/news/bin-yu-receives-2018-elizabeth-l-scott-award/.
- ↑ "Breiman Lecture recording". 2020-10-18. https://www.youtube.com/watch?v=yUJ9-CQDvn8.
External links
- A conversation with Professor Bin Yu By Tao Shi, July 9, 2013
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