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Tamara Broderick | |
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Born | Tamara Ann Broderick |
Alma mater | Princeton University (BS) University of Cambridge (MAS) University of California, Berkeley (PhD) |
Awards | National Science Foundation CAREER Award |
Scientific career | |
Fields | Machine Learning Statistics Bayesian Inference [1] |
Institutions | Massachusetts Institute of Technology |
Thesis | Clusters and features from combinatorial stochastic processes (2014) |
Doctoral advisor | Michael I. Jordan [2] |
Website | tamarabroderick |
Tamara Ann Broderick is an American computer scientist at the Massachusetts Institute of Technology. She works on machine learning and Bayesian inference. [1]
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]
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]
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]
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]
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