Biography:Kristen Grauman

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Short description: Computer vision and machine learning researcher
Kristen Grauman
Born
Kristen Lorraine Grauman

1979 (age 44–45)[1]
Alma materBoston College (BS)
Massachusetts Institute of Technology (MS, PhD)
AwardsNational Science Foundation CAREER Award (2015)
Presidential Early Career Award for Scientists and Engineers (2013)
Scientific career
FieldsComputer vision
Machine learning[2]
InstitutionsUniversity of Texas at Austin
Facebook
Intel
Lawrence Berkeley National Laboratory
ThesisMatching sets of features for efficient retrieval and recognition (2006)
Doctoral advisorTrevor Darrell[1]
Websitewww.cs.utexas.edu/~grauman

Kristen Lorraine Grauman is a Professor of Computer Science at the University of Texas at Austin on leave as a research scientist at Facebook AI Research (FAIR).[3] She works on computer vision and machine learning.[2][4]

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. ↑ 1.0 1.1 1.2 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. Free to read
  2. ↑ 2.0 2.1 {{Google Scholar id}} template missing ID and not present in Wikidata.
  3. ↑ 3.0 3.1 "Kristen Grauman Bio". http://www.cs.utexas.edu/~grauman/bio.html. 
  4. ↑ {{DBLP}} template missing ID and not present in Wikidata.
  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. ↑ 6.0 6.1 Grauman, K.; Darrell, T. (2005). "The pyramid match kernel: discriminative classification with sets of image features". Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1. pp. 1458–1465 Vol. 2. doi:10.1109/ICCV.2005.239. ISBN 978-0-7695-2334-7. https://www.cs.utexas.edu/~grauman/papers/grauman_darrell_iccv2005.pdf. 
  7. ↑ "UTCS Welcomes New Faculty" (in en). Department of Computer Science. https://www.cs.utexas.edu/news/2006/utcs-welcomes-new-faculty. 
  8. ↑ "Robotics" (in en). https://robotics.utexas.edu/kristen-grauman. 
  9. ↑ "Robotics Seminar" (in en). Carnegie Mellon School of Computer Science. 2013-09-25. https://www.cs.cmu.edu/calendar/robotics-seminar-117. 
  10. ↑ "Oct 18: Kristen Grauman: Capturing Human Insight for Large-Scale Visual Learning" (in en-US). Machine Learning @ Johns Hopkins University. 2011-10-11. https://ml.jhu.edu/2011/10/oct-18-kristen-grauman-capturing-human-insight-for-large-scale-visual-learning/. 
  11. ↑ "Alumni Announcements". 2012. https://www.bc.edu/content/dam/files/centers/psp/pdf/ExLibris%2005.12S.pdf. 
  12. ↑ "Topic: Alfred P. Sloan Research Fellowship | Department of Computer Science" (in en). https://www.cs.utexas.edu/news-tags/alfred-p-sloan-research-fellowship. 
  13. ↑ "Grauman Wins Young Investigator Research Award" (in en). Department of Computer Science. https://www.cs.utexas.edu/news/2012/grauman-wins-young-investigator-research-award. 
  14. ↑ "Kristen Grauman Wins 2013 PAMI Young Researcher Award" (in en). Department of Computer Science. https://www.cs.utexas.edu/news/2013/kristen-grauman-wins-2013-pami-young-researcher-award. 
  15. ↑ Akst, Daniel (2013-09-21). "Stop, Rewind, Summarize" (in en-US). Wall Street Journal. ISSN 0099-9660. https://www.wsj.com/articles/stop-rewind-summarize-1379724728. 
  16. ↑ "Professor continues research on video summarization technology | Department of Computer Science" (in en). https://www.cs.utexas.edu/news/2013/professor-continues-research-video-summarization-technology. 
  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. doi:10.1007/s11263-014-0794-5. ISSN 0920-5691. Bibcode: 2015arXiv150504803L. 
  18. ↑ "The Pyramid Match Grauman and Darrell". http://www.cs.utexas.edu/~grauman/research/projects/pmk/pmk_projectpage.htm. 
  19. ↑ Efficiently identifying images, videos, songs or documents most relevant to the user using binary search trees on attributes for guiding relevance feedback, https://patents.google.com/patent/US9176993B2/en, 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, https://patents.google.com/patent/US20140188901A1/en, retrieved 2018-09-17 
  21. ↑ "About TPAMI • IEEE Computer Society" (in en-US). https://www.computer.org/web/tpami/about. 
  22. ↑ "Kristen Grauman". http://www.cs.utexas.edu/users/grauman/. 
  23. ↑ "About the IEEE Fellow Program". https://www.ieee.org/membership/fellows/index.html. 
  24. ↑ "Elected AAAI Fellows" (in en-US). https://aaai.org/about-aaai/aaai-awards/the-aaai-fellows-program/elected-aaai-fellows/. 
  25. ↑ "Kristen Grauman Awarded J.K. Aggarwal Prize for Image Matching Research | Department of Computer Science" (in en). https://www.cs.utexas.edu/news/2018/kristen-grauman-awarded-jk-aggarwal-prize-image-matching-research. 
  26. ↑ "Kristen Grauman Named to UT Austin's Academy of Distinguished Teachers | Department of Computer Science" (in en). https://www.cs.utexas.edu/news/2017/kristen-grauman-named-ut-austins-academy-distinguished-teachers. 
  27. ↑ "Kristen Grauman Wins Award for Influential Computer Vision Paper | Department of Computer Science" (in en). https://www.cs.utexas.edu/news/2017/kristen-grauman-wins-award-influential-computer-vision-paper. 
  28. ↑ "NSF Award Search: Award#0747356 - CAREER: Scalable Image Search and Recognition: Learning to Efficiently Leverage Incomplete Information". https://www.nsf.gov/awardsearch/showAward?AWD_ID=0747356. 
  29. ↑ "Kristen Grauman to Receive Presidential Early Career Award for Scientists and Engineers | Department of Computer Science" (in en). https://www.cs.utexas.edu/news/2014/kristen-grauman-receive-presidential-early-career-award-scientists-and-engineers. 
  30. ↑ "Kristen Grauman Wins Major Teaching Award | Department of Computer Science" (in en). https://www.cs.utexas.edu/news/2012/kristen-grauman-wins-major-teaching-award. 
  31. ↑ "AI's 10 to Watch" (in en). IEEE Intelligent Systems 26 (1): 5–15. 2011. doi:10.1109/MIS.2011.7. ISSN 1541-1672. https://www.computer.org/csdl/mags/ex/2011/01/mex2011010005-abs.html. 



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