ModEling and uNdersTanding human behaviOR (MENTOR)

Our training program on ModEling and uNdersTanding human behaviOR (MENTOR): harnessing data from genes to social networks, draws upon a core group of interdisciplinary faculty researchers and teachers across the UCLA School of Engineering and Applied Sciences, the Department of Mathematics, the Department of Statistics, the College of Social Sciences, and the School of Medicine, to create an interdisciplineary team for this Harnessing the Data Revolution for 21st Century Science and Engineering (HDR) program. The following faculty are involved in the program:

  • Wei Wang, PI, Professor of Computer Science, Co-Director of Scalable Analytics Institute, UCLA
  • Andrea Bertozzi, CoPI, Professor of Mathematics and Mechanical and Aerospace Engineering and Director of Applied Mathematics, UCLA
  • John Cho, Co-PI Professor of Computer Science, UCLA
  • Weizhe Hong, Co-PI, Asst. Prof. of Biological Chemistry, UCLA
  • Sean Young, Co-PI, Associate Professor of Family Medicine, Director of UC Institute for Prediction Technology and UCLA Center for Digital Behavior
  • Katherine Narr, Associate Professor of Neurology, Psychiatry and Biobehavioral Sciences
  • Rafail Ostrovsky, Professor of Computer Science and Mathematics, Director of Center for Information and Computation Security, UCLA
  • Jeff Brantingham, Professor of Anthropology
  • Ani Nahapetian, Associate Professor of Computer Science and Graduate coordinator CSUN
  • Jessica Li, Asst. Prof. Statistics and Dept. Human Genetics
  • Steven Cole, Professor of Medicine / Psychiatry / Biobehavioral Science
  • Chee Wei Wong, Professor of Electrical and Computer Engineering
  • Hannah Landecker, Director, Institute for Society and Genetics, Professor of Sociology
  • Yizhou Sun, Asst. Prof., Computer Science
  • Phil Kellman, Prof. Psychology
  • Kai-Wei Chang, Asst. Prof. Computer Science

    A confluence of technologies is tranforming the biological, environmental, and social sciences into data-intensive sciences. Our MENTOR program offers unique opportunities to train future scientists to develop and deploy new mathematical models, analytical methods, and application tools that directly address the challenges in managing, analyzing and integrating new and diverse types of data and knowledge across scientific and engineering disciplines.

    The program consists of four research thrust layers:

    1) genomics and genetics, 2) brain imaging and multi-modal prediction, 3) mobile sensing and individual behaviors, 4) social networks.

    These layers are interconnected through three core areas:

    A) mathematical modeling and network analysis, B) scalable machine learning and big data analytics, and C) biomedical applications and social outcomes.

    Courses associated with the layers and cores can be found here. The overall program structure is listed in the diagram below.


    Application requirements:

    1. Transcript or DPR 2. One reference letter from the primary mentor and a second reference letter for a secondary mentor who must be from a different research layer and core area than the primary mentor 3. CV/resume of the applicant 4. Research statement about what the student will work on with primary and secondary mentors 5. list of courses taken at UCLA and planned courses to be taken to satisfy program course requirements

    Incoming PHD students can request the advisor to submit their graduate application package to the program.

    Apply here .