Wikipedia

Tamara Broderick

Tamara Ann Broderick is an American computer scientist at the Massachusetts Institute of Technology. She works on machine learning and Bayesian inference.[1]

Tamara Broderick
Born
Tamara Ann Broderick
Alma materPrinceton University (BS)
University of Cambridge (MAS)
University of California, Berkeley (PhD)
AwardsNational Science Foundation CAREER Award
Scientific career
FieldsMachine Learning
Statistics
Bayesian Inference[1]
InstitutionsMassachusetts Institute of Technology
ThesisClusters and features from combinatorial stochastic processes (2014)
Doctoral advisorMichael I. Jordan[2]
Websitetamarabroderick.com

Education and early career edit

Broderick is from Parma Heights, Ohio.[3] She attended Laurel School and graduated in 2003.[4] Whilst at high school she took part in the inaugural Massachusetts Institute of Technology Women's Technology Program.[5] She studied mathematics at Princeton University, earning a bachelor's degree in 2007.[3] She was a Marshall scholar, allowing her to pursue graduate research at the University of Cambridge.[3] She was a runner-up in the Association for Women in Mathematics Alice T. Shafer Prize for Excellence in Mathematics.[3][6] She was co-president of the Princeton Math Club and organised a competition for high school maths teams.[3] She won the Phi Beta Kappa Prize for the highest academic average at Princeton University.[7] During her undergraduate degree, Broderick worked on dark matter haloes with Rachel Mandelbaum.[8] Broderick moved to the United Kingdom for her graduate studies, earning a Master of Advanced Studies for completing Part III of the Mathematical Tripos at the University of Cambridge in 2009.[9][10] Her Master's thesis looked at the Nomon selection method, improving the efficiency of communications.[11][12] She returned to America in 2009, joining University of California, Berkeley for her Master's and PhD.[10] Her graduate research was supported by the Berkeley Fellowship and a National Science Foundation Fellowship.[7] Her PhD thesis Clusters and features from combinatorial stochastic processes looked at clustering and speeding up the analysis of large, streaming data sets.[13][2] In 2013 she was selected for the Berkeley EECS Rising Stars conference.[14]

Research and career edit

Broderick joined Massachusetts Institute of Technology as an Assistant Professor in 2015.[14] She is interested in Bayesian statistics and Graphical models.[15] She was the recipient of a Google Faculty Research Grant and International Society for Bayesian Analysis Lifetime Members Junior Researcher Award.[16] She was awarded an Army Research Office young investigator program award to investigate machine-learning to quantify uncertainty in data analysis.[17] Broderick is also Alfred P. Sloan Foundation scholar.[18][19][20][21]

Academic service edit

In 2018, Broderick spoke at the Harvard University Institute for Applied Computational Science Women in Data Science conference.[22] She spoke about Bayesian inference at the 2018 International Conference on Machine Learning.[23] She led a three-day Masterclass on machine learning at University College London in June 2018.[24][25] Broderick is a scientific advisor for AI.Reverie and WiML (Women in Machine Learning).[26][27] She has developed a high-school level introduction to machine learning with the Women's Technology Program (WTP).[28] Software she has developed is available on her website.[29]

Awards and honors edit

Broderick was awarded the Evelyn Fix Memorial Medal and Citation and the International Society for Bayesian Analysis Savage Award for her doctoral thesis.[30][31] She was awarded a National Science Foundation CAREER Award to scale her machine learning techniques.[32][28] She was a 2021 Leadership Academy winner of the Committee of Presidents of Statistical Societies.[33]

References edit

  1. ^ a b Tamara Broderick publications indexed by Google Scholar  
  2. ^ a b Tamara Broderick at the Mathematics Genealogy Project  
  3. ^ a b c d e "Alumni Profile: Tamara Broderick" (PDF). princeton.edu. Retrieved 2018-12-27.
  4. ^ "Laurel School | Alumnae | Distinguished Alumna Award Recipients". laurelschool.org. Retrieved 2018-12-27.
  5. ^ "Woman in technology". news.mit.edu. Retrieved 2018-12-27.
  6. ^ "January 2007 Prizes and Awards" (PDF). MAA. Retrieved 2018-12-27.
  7. ^ a b "MIT School of Engineering | » Tamara Broderick". engineering.mit.edu. MIT Engineering. Retrieved 2018-12-27.
  8. ^ Brinkmann, Jonathan; Seljak, Uroš; Broderick, Tamara; Hirata, Christopher M.; Mandelbaum, Rachel (2006). "Ellipticity of dark matter haloes with galaxy–galaxy weak lensing". Monthly Notices of the Royal Astronomical Society. 370 (2): 1008–1024. arXiv:astro-ph/0507108. Bibcode:2006MNRAS.370.1008M. doi:10.1111/j.1365-2966.2006.10539.x. ISSN 0035-8711. S2CID 238069.
  9. ^ Cambridge, research in physics from the University of; California, an MS in computer science from the University of; uncertainty, Berkeley Sessions Bayesian machine learning: Quantifying; Learning, robustness at scale Machine; star, Data Science Location: 1A 06/07 Level: Intermediate Secondary topics: Hardcore Data Science Tamara BroderickAverage. "Speaker: Tamara Broderick: Big data conference: Strata Data Conference, September 25 - 28, 2017, New York, NY". conferences.oreilly.com. Retrieved 2018-12-27.{{cite web}}: CS1 maint: numeric names: authors list (link)
  10. ^ a b "Speaker: Tamara Broderick: Big data conference: Strata Data Conference, September 25 - 28, 2017, New York, NY". conferences.oreilly.com. Retrieved 2018-12-27.
  11. ^ "Nomon: Efficient communication with a single switch" (PDF). MIT. Retrieved 2018-12-27.
  12. ^ "Tamara Broderick". tamarabroderick.com. Retrieved 2018-12-27.
  13. ^ Broderick, Tamara Ann (2014). Clusters and Features from Combinatorial Stochastic Processes (PhD thesis). University of California, Berkeley. OCLC 919405382.
  14. ^ a b "Rising Stars in EECS | UC Berkeley". eecs.berkeley.edu. Retrieved 2018-12-27.
  15. ^ "Speakers". machine-intelligence-summit.com. Machine Intelligence Summit. Retrieved 2018-12-27.
  16. ^ "Google Faculty Research Awards 2016" (PDF). services.google.com. Retrieved 2018-12-27.
  17. ^ "Tamara Broderick receives prestigious Army Research Office award | MIT EECS". eecs.mit.edu. Retrieved 2018-12-27.
  18. ^ "Two EECS faculty members receive 2018 Sloan Research Fellowships | MIT EECS". eecs.mit.edu. Retrieved 2018-12-27.
  19. ^ "2018 Fellows". sloan.org. Archived from the original on 2018-11-01. Retrieved 2018-12-27.
  20. ^ "American Mathematical Society". ams.org. Retrieved 2018-12-27.
  21. ^ "Massachusetts Institute of Technology". sloan.org. Retrieved 2018-12-27.
  22. ^ Harvard Institute for Applied Computational Science, Women in Data Science (2018): Tamara Broderick, MIT, retrieved 2018-12-27
  23. ^ Steven Van Vaerenbergh, Tamara Broderick: Variational Bayes and Beyond: Bayesian Inference for Big Data (ICML 2018 tutorial), retrieved 2018-12-27
  24. ^ "CSML Masterclass with Tamara Broderick". cs.ucl.ac.uk. Retrieved 2018-12-27.
  25. ^ "CSML Masterclass". tamarabroderick.com. Retrieved 2018-12-27.
  26. ^ "AI.Reverie". AI. Reverie. Retrieved 2018-12-27.
  27. ^ "Tamara Broderick, PhD". Retrieved 2018-12-27.
  28. ^ a b "NSF Award Search: Award#1750286 - CAREER: Robust, scalable, reliable machine learning". nsf.gov. Retrieved 2018-12-27.
  29. ^ "Tamara Broderick". tamarabroderick.com. Retrieved 2018-12-27.
  30. ^ "Student Departmental Awards | Department of Statistics". statistics.berkeley.edu. Retrieved 2018-12-27.
  31. ^ "Savage Award | International Society for Bayesian Analysis". Retrieved 2018-12-27.
  32. ^ "News | Tamara Broderick receives 2018 NSF CAREER Award". stat.mit.edu. Retrieved 2018-12-27.
  33. ^ "2021 COPSS Award Winners". AmStat News. May 1, 2021.
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