Hi, I’m Theja

I’m a researcher and a machine learning engineer. I have a PhD in ML from CSAIL/EECS at MIT.



I build value-driven machine learning and optimization solutions in applications that typically interface with people. I focus on bringing the best out of data and enabling large gains in key business metrics.

In addition to various consulting engagements, my work experiences include working with/at: the University of Illinois at Chicago, Xerox Research, Massachusetts Institute of Technology, Citadel Investments, Apple, State Street Global Advisors, Indian Institutes of Technology at Kharagpur and Bombay, and Texas Instruments to name a few.

I am broadly interested in pursuing practical solutions to applied problems, which make use of carefully chosen statistical models and data driven decision making methods, and have a significant impact on business and societal outcomes. Some specific interests include:

  • Modeling human behavior and enhancing their decision making prowess quantitatively
  • Developing application specific machine learning/statistical methods
  • Developing special-purpose optimization and reinforcement learning methods for real life deployment
  • Tech entrepreneurship (e.g., ML Ops, scalable data pipelines, online experimentation, personalization)


I have had the opportunity to work with a variety of teams and businesses on deploying data driven solutions across multiple domains. If you are interested in discussing a specific problem, I am available for an initial online meeting.

More generally, if my skillset interests you, or you would like to learn more about what value I can add to your team, please get in touch!


I have a PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology, Cambridge, USA. My thesis topic area was Machine Learning and Optimization. I also have a Dual Degree in Electrical Engineering from the Indian Institute of Technology Kharagpur, India. While there, I was awarded the Prime Minister’s Gold Medal for being ranked 1 GPA-wise across the university. I have also been a Fulbright Science and Technology Scholar.


I am fortunate to have had an excellent set of collaborators in my research pursuits. To see the 40+ research threads I have pursued, broadly in the areas of machine learning (including supervised, online and reinforcement learning variants) and optimization (both continuous and discrete), you can use the links below:

Archive Scholar | DBLP | Arxiv | SSRN | Google Scholar

Here is a very-short biased sample of research topics that I have looked at:
  • Optimizing and personalizing recommendations, assortments as well as prices under realistic user behavior models.
  • Pricing new products and doing machine learning in competitive settings (e.g., accounting for strategic behavior and loyalty).
  • Designing well-behaved online and reinforcement learning methods for personalization by exploiting the underlying domain specific structure.
  • Enhancing supervised machine learning in the presence of operational information.
  • Solving hard decision problems in transportation such as scheduling, crowd-shipping and enabling fair ride-shares.

Some videos related to my research are on Youtube. On a related note, some threads/projects have also culminated into a few patents.


Get in touch with me via my email address. I will try to respond back in 1-2 business days.

My current local time is .