Manik Varma (computer scientist)
Manik Varma | |
|---|---|
| Nationality | Indian |
| Alma mater | University of Oxford |
| Awards | Shanti Swarup Bhatnagar Prize for Science and Technology (2019) |
| Scientific career | |
| Fields | Computer Science Computational Advertising |
| Institutions | Microsoft Research India Indian Institute of Technology Delhi |
| Thesis | Statistical approaches to texture classification (2004) |
| Doctoral advisor | Andrew Zisserman |
| Website | http://manikvarma.org/ |
Manik Varma is an Indian computer scientist and a Distinguished Scientist and Vice President at Microsoft Research India.[1] He has an adjunct professor position at the Indian Institute of Technology Delhi.
Education
[edit] | This section of a biography of a living person does not include any references or sources. (January 2025) |
He completed his undergraduate degree in Physics from St. Stephen’s College, Delhi. He was a Rhodes Scholar and earned his PhD from the University of Oxford under the guidance of Andrew Zisserman working on Texture Classification in Computer Vision. He also held a post-doctoral fellowship at the Mathematical Sciences Research Institute, Berkeley before joining Microsoft Research.
Career
[edit]He conducts research in the fields of Machine Learning, Artificial Intelligence and Information Retrieval. In 2013, he started and popularized a new area in machine learning called Extreme Classification (also known as Extreme Multi-label Classification).[1][2][3] Extreme Classification focuses on Multi-Label Classification at the scale of millions of labels and helps rethink traditional problems of ranking and recommendation.[4] Extreme Classification is thriving in both academia and industry with product integrations in Bing and Amazon.[4][1] Manik Varma along with his colleagues at MSR India also proposed another paradigm in machine learning called Edge Machine Learning[5] to enable machine learning predictions on tiny IoT devices with as little as 2 KB of RAM assisting in low-energy, low-latency and privacy preserving applications of AI. In the past, he worked on statistical approaches to texture classification, object detection, multiple kernel learning and ranking.
Recognition
[edit]He was awarded the Shanti Swarup Bhatnagar Prize for Science and Technology for his contributions to Engineering Sciences in 2019.[6][7] His research works won the WSDM Best Paper award[8] and BuildSys Best Paper Runner-Up award[9] in 2019. He has been elected a Fellow of the Association for Computing Machinery, the Indian National Science Academy and the Indian National Academy of Engineering.[10] He has also held a Visiting Miller Professorship at the University of California, Berkeley.[11][1] He is associate editor-in-chief for the IEEE Transactions on Pattern Analysis and Machine Intelligence.[12]
References
[edit]- ^ a b c d "Manik Varma". manikvarma.org. Retrieved 2020-07-26.
- ^ "The Extreme Classification Repository". manikvarma.org. Retrieved 2020-07-26.
- ^ Bengio, Samy; Dembczynski, Krzysztof; Joachims, Thorsten; Kloft, Marius; Varma, Manik (2019). Bengio, Samy; Dembczynski, Krzysztof; Joachims, Thorsten; Kloft, Marius; Varma, Manik (eds.). "Extreme Classification (Dagstuhl Seminar 18291)". Dagstuhl Reports. 8 (7): 62–80. doi:10.4230/DagRep.8.7.62. ISSN 2192-5283.
- ^ a b Varma, Manik. "Extreme Classification". cacm.acm.org. Retrieved 2020-07-26.
- ^ microsoft/EdgeML, Microsoft, 2020-07-25, retrieved 2020-07-26
- ^ "Awardee Details: Shanti Swarup Bhatnagar Prize". ssbprize.gov.in. Retrieved 2020-07-26.
- ^ Bureau, Our (27 September 2019). "Microsoft researcher Manik Varma among Shanti Swaroop Bhatnagar award winners this year". @businessline. The Hindu.
{{cite news}}:|last1=has generic name (help) - ^ "Home | 12th ACM International WSDM Conference". www.wsdm-conference.org. Retrieved 2020-07-26.
- ^ "BuildSys 2019". buildsys.acm.org. Retrieved 2020-07-26.
- ^ "Nomination Information". Indian National Academy of Engineering. Retrieved 2020-07-26.
- ^ "2018 - 2019 Lunch Lectures". miller.berkeley.edu. Retrieved 2020-07-26.
- ^ "TPAMI Editorial Board | IEEE Computer Society". Retrieved 2020-07-26.