Suresh Venkatasubramanian
Alma materIIT Kanpur
Stanford University
Known fort-closeness
AwardsNSF CAREER Award
Scientific career
FieldsComputational geometry
Data mining
Differential privacy
InstitutionsAT&T Labs
Google
Simons Institute for the Theory of Computing
University of Utah
ThesisGeometric shape matching and drug design (1999)
Doctoral advisorRajeev Motwani
Jean-Claude Latombe
Websitehttp://blog.geomblog.org/

Suresh Venkatasubramanian is an Indian computer scientist and professor at Brown University. In 2021, Prof. Venkatasubramanian was appointed to the White House Office of Science and Technology Policy, advising on matters relating to fairness and bias in tech systems.[1] He was formerly a professor at the University of Utah. He is known for his contributions in computational geometry and differential privacy, and his work has been covered by news outlets such as Science Friday, NBC News, and Gizmodo.[2][3][4][5] He also runs the Geomblog, which has received coverage from the New York Times, Hacker News, KDnuggets and other media outlets.[6][7][8][9] He has served as associate editor of the International Journal of Computational Geometry and Applications and as the academic editor of PeerJ Computer Science, and on program committees for the IEEE International Conference on Data Mining, the SIAM Conference on Data Mining, NIPS, SIGKDD, SODA, and STACS.[10]

Career

Suresh Venkatasubramanian attended the Indian Institute of Technology Kanpur for his BTech and received his PhD from Stanford University in 1999 under the joint supervision of Rajeev Motwani and Jean-Claude Latombe.[11] Following his PhD he joined AT&T Labs and served as an adjunct professor at the University of Pennsylvania where he taught courses on computational geometry and streaming algorithms for GPGPUs.[12] In 2007 he joined the University of Utah School of Computing as the John E. and Marva M. Warnock Presidential Endowed Chair for Faculty Innovation in Computer Science.[10] He received a National Science Foundation CAREER Award in 2010, and in 2013-2014 he was a visiting scientist at the Simons Institute for the Theory of Computing at UC Berkeley and at Google.[13][10] In 2021, Prof. Venkatasubramanian was appointed to the White House Office of Science and Technology Policy, advising on matters relating to fairness and bias in tech systems,[1] in addition, he moved to Brown University to join the Computer Science department and their Data Science Initiative. At Brown, Prof. Venkatasubramanian will be starting a new center on Computing for the People, to help think through what it means to do computer science that truly responds to the needs of people, instead of hiding behind a neutrality that merely gives more power to those already in power.[1]

References

  1. 1 2 3 "Transitions". Retrieved 2021-05-21.
  2. ↑ "Why Machines Discriminate—and How to Fix Them - Science Friday". Science Friday. Retrieved 13 April 2017.
  3. ↑ Gholipour, Bahar (10 March 2017). "Algorithms learn from us — we can be better teachers". NBC News. Retrieved 13 April 2017.
  4. ↑ Pepitone, Julianne (17 August 2015). "Can Résumé-Reviewing Software Be As Biased As Human Hiring Managers?". NBC News. Retrieved 13 April 2017.
  5. ↑ Smith-Strickland, Kiona (15 August 2015). "Computer Programs Can Be as Biased as Humans". Gizmodo. Retrieved 13 April 2017.
  6. ↑ Rich, Motoko (14 April 2006). "'Fibs' Sprout On Web". The New York Times. Retrieved 13 April 2017.
  7. ↑ "Blogs on Big Data, Business Analytics, Data Mining, and Data Science". KDnuggets. Retrieved 13 April 2017.
  8. ↑ "HackerNews Search Results for 'geomblog'". Hacker News. Retrieved 13 April 2017.
  9. ↑ "The Geomblog: Racism/sexism in algorithms • r/MachineLearning". r/MachineLearning. Reddit. Retrieved 13 April 2017.
  10. 1 2 3 "Suresh Venkatasubramanian". Faculty Activity Report. University of Utah. Retrieved 13 April 2017.
  11. ↑ Suresh Venkatasubramanian at the Mathematics Genealogy Project
  12. ↑ "Developer Newsletter: Issue #24". NVIDIA. Retrieved 13 April 2017.
  13. ↑ "Long-Term Visitors". Simons Institute. UC Berkeley. Retrieved 13 April 2017.
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