Kristen Grauman

Early life and education

Grauman studied computer science at Boston College, graduating summa cum laude in 2001. She joined Massachusetts Institute of Technology for her postgraduate studies, earning a Master of Science degree in 2003[5] followed by a PhD in 2006 supervised by Trevor Darrell.[1][6][3] During her PhD Grauman worked as a research intern at Intel and Lawrence Berkeley National Laboratory.

Career and research

In 2007 Grauman was appointed Clare Boothe Luce Assistant Professor at University of Texas at Austin.[7] Her research looks to develop algorithms that can categorise and detect objects.[8] She is interested in how computer vision can solicit information from humans.[9][10] She was promoted to Associate Professor with tenure in 2011.[11]

She is an Alfred P. Sloan Foundation Fellow.[12] She was awarded an Office of Naval Research young investigator award in 2012.[13] In 2013 she was awarded a Pattern Analysis and Machine Intelligence (PAMI) Young Researcher Award.[14] She is working on techniques to get computers to watch and summarise videos for easy viewing.[15] The egocentric films will be used to aid the elderly and those with impaired-memories.[16][17]

She has developed several patents for machine learning; including pyramid match kernel methods[6] and a technique to efficiently identifying images.[18][19][20]

Grauman serves as associate editor-in-chief of the IEEE Transactions on Pattern Analysis and Machine Intelligence.[21] As of May 2018, Grauman is on leave at Facebook AI Research (FAIR).[22]

Awards and honors

Her awards and honors include:

References
  1. Grauman, Kristen Lorraine (2006). Matching sets of features for efficient retrieval and recognition (PhD thesis). Massachusetts Institute of Technology. hdl:1721.1/38296. OCLC 153915528.
  2. Kristen Grauman publications indexed by Google Scholar
  3. "Kristen Grauman Bio". cs.utexas.edu. Retrieved 2018-09-17.
  4. Kristen Grauman at DBLP Bibliography Server
  5. Grauman, Kristen Lorraine (2003). A statistical image-based shape model for visual hull reconstruction and 3D structure inference (MS thesis). Massachusetts Institute of Technology. OCLC 53225478.
  6. Grauman, K.; Darrell, T. (2005). "The pyramid match kernel: discriminative classification with sets of image features" (PDF). Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1. pp. 1458–1465 Vol. 2. CiteSeerX 10.1.1.644.6159. doi:10.1109/ICCV.2005.239. ISBN 978-0-7695-2334-7.
  7. "UTCS Welcomes New Faculty". www.cs.utexas.edu. Department of Computer Science. Retrieved 2018-09-17.
  8. "Robotics". robotics.utexas.edu. Retrieved 2018-09-17.
  9. "Robotics Seminar". www.cs.cmu.edu. Carnegie Mellon School of Computer Science. 2013-09-25. Retrieved 2018-09-17.
  10. "Oct 18: Kristen Grauman: Capturing Human Insight for Large-Scale Visual Learning". Machine Learning @ Johns Hopkins University. 2011-10-11. Retrieved 2018-09-17.
  11. "Alumni Announcements" (PDF). Boston College. 2012. Retrieved 2018-09-17.
  12. "Topic: Alfred P. Sloan Research Fellowship | Department of Computer Science". www.cs.utexas.edu. Retrieved 2018-09-17.
  13. "Grauman Wins Young Investigator Research Award". www.cs.utexas.edu. Department of Computer Science. Retrieved 2018-09-17.
  14. "Kristen Grauman Wins 2013 PAMI Young Researcher Award". www.cs.utexas.edu. Department of Computer Science. Retrieved 2018-09-17.
  15. Akst, Daniel (2013-09-21). "Stop, Rewind, Summarize". Wall Street Journal. ISSN 0099-9660. Retrieved 2018-09-17.
  16. "Professor continues research on video summarization technology | Department of Computer Science". www.cs.utexas.edu. Retrieved 2018-09-17.
  17. Lee, Yong Jae; Grauman, Kristen (2015-01-07). "Predicting Important Objects for Egocentric Video Summarization". International Journal of Computer Vision. 114 (1): 38–55. arXiv:1505.04803. Bibcode:2015arXiv150504803L. doi:10.1007/s11263-014-0794-5. ISSN 0920-5691.
  18. "The Pyramid Match Grauman and Darrell". www.cs.utexas.edu. Retrieved 2018-09-17.
  19. Efficiently identifying images, videos, songs or documents most relevant to the user using binary search trees on attributes for guiding relevance feedback, retrieved 2018-09-17
  20. Efficiently identifying images, videos, songs or documents most relevant to the user using binary search trees on attributes for guiding relevance feedback, retrieved 2018-09-17
  21. "About TPAMI • IEEE Computer Society". www.computer.org. Retrieved 2018-09-17.
  22. "Kristen Grauman". www.cs.utexas.edu. Retrieved 2018-09-17.
  23. "About the IEEE Fellow Program". www.ieee.org. Retrieved 2019-12-09.
  24. "Kristen Grauman Awarded J.K. Aggarwal Prize for Image Matching Research | Department of Computer Science". www.cs.utexas.edu. Retrieved 2018-09-17.
  25. "Kristen Grauman Named to UT Austin's Academy of Distinguished Teachers | Department of Computer Science". www.cs.utexas.edu. Retrieved 2018-09-17.
  26. "Kristen Grauman Wins Award for Influential Computer Vision Paper | Department of Computer Science". www.cs.utexas.edu. Retrieved 2018-09-17.
  27. "NSF Award Search: Award#0747356 - CAREER: Scalable Image Search and Recognition: Learning to Efficiently Leverage Incomplete Information". www.nsf.gov. Retrieved 2018-09-17.
  28. "Kristen Grauman to Receive Presidential Early Career Award for Scientists and Engineers | Department of Computer Science". www.cs.utexas.edu. Retrieved 2018-09-17.
  29. "Kristen Grauman Wins Major Teaching Award | Department of Computer Science". www.cs.utexas.edu. Retrieved 2018-09-17.
  30. "AI's 10 to Watch". IEEE Intelligent Systems. 26 (1): 5–15. 2011. doi:10.1109/MIS.2011.7. ISSN 1541-1672.
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