Himabindu Lakkaraju



Contact

hlakkaraju@hbs.edu
428 Morgan Hall
@hima_lakkaraju
lvhimabindu


Starting January 2020, I will be an Assistant Professor at Harvard University with appointments in Business School and Department of Computer Science. I am currently a postdoctoral fellow at Harvard University.

I develop machine learning tools and techniques which are not only accurate but also fair and interpretable so that human decision makers can leverage them to make better decisions. More specifically, my research addresses the following fundamental questions pertaining to human and algorithmic decision-making:

  1. How do we build interpretable models that can aid human decision-making?
  2. How do we evaluate the effectiveness of algorithmic predictions and compare them with human decisions?
  3. How do we detect and correct underlying biases in human decisions and algorithmic predictions?

These questions have far-reaching implications in domains involving high-stakes decisions such as criminal justice, health care, public policy, business, and education.

Prior to my stint at Harvard, I received my PhD in Computer Science from Stanford University, during which I collaborated with Prof. Jure Leskovec, Prof. Cynthia Rudin, Prof. Jon Kleinberg, Prof. Sendhil Mullainathan, and Dr. Eric Horvitz. My PhD research was generously supported by a Stanford Graduate Fellowship, a Microsoft Research Dissertation Grant, and a Google Anita Borg Scholarship.

For more details, please refer my CV.
  • I am incredibly honored and humbled to be named one of the 35 innovators under 35 by MIT Tech Review. Here is the article featuring my work.
  • I am looking for motivated students who are broadly interested in machine learning and its applications to health care and criminal justice. If you are excited about this line of research and would like to work with me, please drop me an email with a brief description of your research interests and your CV.
  • I am co-organizing a session on Fairness in Machine Learning at INFORMS Annual Meeting 2019.
  • I am serving as an Area Chair for ICML and NeurIPS 2019
  • I co-organized a workshop on Debugging Machine Learning Models at ICLR 2019. More details at: https://debug-ml-iclr2019.github.io/

Publications

Patents