Himabindu Lakkaraju


452 Gates Computer Science

I am a PhD student in Computer Science at Stanford University, advised by Prof. Jure Leskovec. I also frequently collaborate with Prof. Cynthia Rudin, Prof. Jon Kleinberg, Prof. Sendhil Mullainathan, and Dr. Eric Horvitz.

I develop computational methods to make the practice of machine learning more transparent, reliable, fair, and socially relevant. My research finds applications in domains involving high-stakes decisions such as law, health care, public policy, business, and education.

My research combines techniques from machine learning, data mining, econometrics, and computational social science to address various 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 the underlying biases in human decisions and algorithmic predictions?
My research proposes novel computational frameworks which address the above questions by effectively handling the core underlying challenges such as missing counterfactuals and presence of unmeasured confounders.

My research is supported by a Stanford Graduate Fellowship, a Microsoft Research Dissertation Grant, and a Google Anita Borg Scholarship.

I am on the academic job market. Here is my CV.