About Me
I am a student of Technology, AI and Economics at Carnegie Mellon University. Prior to joining CMU, I spent five years as a quantitative data strategist for Goldman Sachs. I completed my undergraduate in Electrical Engineering from IIT Delhi in 2011.
Affiliated with Carnegie Mellon BT Research Group, Tepper Blockchain Initiative
My current research interests include,
- Economics of Machine Learning
- Behavioral and Algorithmic Biases
- Marketing and Financial Technology
Dissertation: Economics of Machine Learning and Blockchain Technologies
- When does beauty pay? An ML based measurement of beauty bias.
- Why Bitcoin will fail to scale? Economics of collusion on Blockchain.
- Can ML amplify pricing errors in housing market? Economics of ML Feedback Loops.
Other Research
Deep Learning in Computer Vision: Methods, Interpretation, Causation and Fairness
Can Banks survive the next financial crisis?: A GAN model for Bank Stress Testing.
Disruptive Technologies in Global Payments - Winners and Losers
Role of naïve consumers in Initial Coin Offerings (ICO)
Bayesian Finger: A Variational Bayes EM method for customer feedback attribution in Web Scale Data Analytics Stack
Awards and Fellowships
Dipankar and Sharmila Chakravarti Doctoral Fellowship Award 2020.
AMA-Sheth Foundation Doctoral Consortium Fellow, 2020.
PNC Presidential Fellowship, 2019-20.
Henry J. Gailliot Presidential Fellowship, CMU 2019-20.
Ripple Foundation Fellow, 2019-20.
ISMS Doctoral Consortium Fellow, 2019.
Litzenberger Family Fund Award, CMU, 2018-19.
Best Conference Paper nomination, CIST INFORMS 2018.
Best Student Paper, CIST INFORMS 2017.
William Larimer Mellon Fellowship, CMU 2016.
Best Electrical Engineering Undergraduate Thesis, IIT Delhi 2011.
