Biography:Inderjit Dhillon
Inderjit S. Dhillon | |
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| Alma mater | Indian Institute of Technology, Bombay (B.Tech.,1989) University of California, Berkeley (Ph.D.,1997) |
| Known for | Machine Learning, Computational Mathematics |
| Awards | ACM Fellow,[1] IEEE Fellow,[2] SIAM Fellow,[3] AAAS Fellow,[4] SIAM Linear Algebra Prize,[5] SIAM Outstanding Paper Prize[6] |
| Scientific career | |
| Fields | Computer Science Mathematics |
| Institutions | The University of Texas at Austin |
| Thesis | A New O(n^2) Algorithm for the Symmetric Tridiagonal Eigenvalue/Eigenvector Problem (1997) |
| Doctoral advisor | Beresford N. Parlett James W. Demmel |
| Doctoral students |
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| Website | https://www.cs.utexas.edu/~inderjit/ |
Inderjit S. Dhillon is the Gottesman Family Centennial Professor of Computer Science and Mathematics at the University of Texas at Austin, where he is also the Director of the ICES Center for Big Data Analytics. His main research interests are in machine learning, data analysis, parallel computing, network analysis, linear algebra and optimization.
Biography
Dhillon received his B.Tech. degree from the Indian Institute of Technology, Bombay in 1989. He subsequently worked at AT&T Bell Laboratories as a Research Staff Member under Dr. Narendra Karmarkar. He received his Ph.D. from the University of California at Berkeley in 1997 under the direction of Beresford Parlett and James Demmel. Dhillon joined the Computer Science faculty at the University of Texas at Austin in 1999.[citation needed]
Academic works
Dhillon's main research interests are in machine learning, data analysis and computational mathematics. His emphasis is on developing novel algorithms that respect the underlying problem structure and are scalable to large data sets. In computational mathematics, he is best known for his work on developing the first numerically stable O(n^2) algorithm for the symmetric tridiagonal eigenvalue problem. His software[7] is now part of LAPACK,[8] and is the method of choice in various software packages, such as the function "eigen" in R.[9] In machine learning, Dhillon is well known for his work on clustering and co-clustering high dimensional data sets, metric and kernel learning, inverse covariance estimation, divide-and-conquer methods, and NOMADic methods[10] for large-scale problems in machine learning.
Honors and awards
Dhillon is a fellow of the Association for Computing Machinery (ACM),[1] a fellow of the Institute of Electrical and Electronics Engineers (IEEE),[2] a fellow of the Society for Industrial and Applied Mathematics (SIAM),[3] and a fellow of the American Association for the Advancement of Science (AAAS).[4] In addition, he has received the ICES Distinguished Research Award, the SIAM Outstanding Paper Prize,[6] the Moncrief Grand Challenge Award, the SIAM Linear Algebra Prize,[5] the University Research Excellence Award, and the NSF Career Award.
References
- ↑ 1.0 1.1 Dhillon named a 2014 ACM Fellow, retrieved 2015-01-20.
- ↑ 2.0 2.1 Inderjit Dhillon named IEEE fellow, retrieved 2013-11-25.
- ↑ 3.0 3.1 Dhillon and Ghattas elected SIAM fellows, retrieved 2014-03-28.
- ↑ 4.0 4.1 Dhillon Named Fellow of AAAS, retrieved 2016-11-21.
- ↑ 5.0 5.1 SIAG/Linear Algebra Prize, Society for Industrial and Applied Mathematics(SIAM).
- ↑ 6.0 6.1 Dhillon team wins international 2011 Outstanding Paper Prize, retrieved 2011-05-18.
- ↑ http://www.netlib.org/lapack/explore-3.1.1-html/dsyevr.f.html, DSYEVR code.
- ↑ http://www.netlib.org/lapack/ LAPACK.
- ↑ eigen, The R Base Package.
- ↑ Using Supercomputers and Machine Learning Algorithms, Nomadic Computing Speeds Up Big Data Analytics, Scientific Computing, November, 2015.
External links
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