I once believed that - "Anything that could be said meaningfully, can be said mathematically". Now, I am interested in understanding the limits of this idea.

My interests have always been broad and I have found myself finding ways of bridging disparate fields of study. I did the inter-disciplinary course at University of Hyderabad, India which gave me a solid background in Mathematics, Physics, Chemistry and Biology. Since I thought that mathematical modeling was the answer to the ambiguity and confusion, I majored in mathematics for its precision and formalization.

While I found the landscape of mathematics extremely beautiful, my existential dread got to me when I imagined that my life achievement would be solving some obscure theorem (if I was lucky). Searching for meaning, I ended up in philosophy (eg. empiricism and epistemology) and social sciences (eg. game theory) classes in university. Searching for utility, I ended up working for a healthcare analytics startup as a Data Scientist/ Machine Learning Specialist.

I wanted to study something that had some use and also helped us understand ourselves/society better. I discovered cognitive science which asks concrete questions with rigorous methods. I discovered the cognitive science society and the society for mathematical psychology, where I saw how computational methods were being developed to understand how our mind works.

I started my PhD with Jennifer Trueblood at Vanderbilt University and later moved with Indiana University. I was particularly inspired with the sophisticated mathematics that was being used to answer useful questions and further our basic understanding. This is use inspired basic research.

I have presented my work in cognitive science, decision making journals and machine learning venues. Most of my work is in medical decision making. I have also studied decisions ranging from multi-attribute choice, consumer decisions, food decisions and social media decisions. In my research I have used statistical methods, approximate Bayesian inference, evidence accumulation models and machine learning (deep learning) models.

While I have managed to focus my professional interests well enough to produce coherent research directions, my personal hobbies are constantly evolving. These range from windsurfing, karate, theater and music.

Since I can only chase a handful of projects myself, I vicariously experience the research routes that I could not do myself through conversations. Please email me if you'd like to chat!