Thoracic Oncology Laboratory »  Alumni »  Specialists »  Ruchira Datta, Ph.D.
Ruchira Datta, Ph.D.

Ruchira Datta, Ph.D.

Specialist

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Dr. Ruchira S. Datta brings expertise in applied mathematics, evolutionary analysis, game theory, machine learning, and big data to the Maley Lab. Dr. Datta is interested in cooperation and conflict at the cellular level, specifically in cancer, the human microbiome, and inflammatory processes.

After receiving a B.S. in mathematics from Caltech, Ruchira S. Datta obtained an M.S. in computer science and a Ph.D in mathematics from UC Berkeley (Ph.D dissertation: "Algebraic Methods in Game Theory"). Dr. Datta briefly lectured in mathematics at UC Davis before joining Google as a software engineer, working on computational linguistics in International Search Quality and web analytics in Google Book Search. Dr. Datta then worked in the Berkeley Phylogenomics Group as a postdoctoral scholar, using gene family trees to predict the structure and function of proteins and interactions between them. Dr. Datta joined the Maley Lab of the Center for Evolution and Cancer in October 2011, and is working on both the evolution of therapeutic resistance in AML (acute myeloid leukemia) and neoplastic progression in Barrett's esophagus.

Selected Innovations

  • Created the PHOG algorithm for ortholog inference, incorporating branch lengths to combine the advantages of tree-based and graph-based methods and allow tuning of sensitivity-specificity based on evolutionary distance (first author with four co-authors)
  • Created algorithms for augmenting queries with synonyms selected using language statistics US Patent 7,475,063 (with a single co-inventor) and simplifying query terms with transliteration US Patent 7,835,903 (sole inventor)
  • Created a new model for groups of interacting agents with both shared and competing interests within noncooperative game theory. (sole author)
  • Developed practical methods for finding all Nash equilibria of a finite game with multiple players. The Nash equilibria constitute the landmarks for mapping the dynamical behavior of interacting agents. (sole author)
  • Proved the universality of Nash equilibria. This implies that interactions among three agents are inherently strictly more complex than interactions between two. Models must usually incorporate multiple agents to have a chance of describing systems well. (sole author)

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