I am a Ph.D. candidate at IIIT Delhi supervised by Dr. Rajiv Ratn Shah at MIDAS Lab and a joint Ph.D. candidate with Microsoft Research India, supervised by Dr. Amit Deshpande. I received my B. Tech in Computer Science and Engineering from BML Munjal University.

My work broadly deals with investigating the effects of changing data distributions in Machine Learning, and their implications on Fairness in ML. I am interested in both the theoretical and practical aspects of such phenomena. One of our works investigated the effects of under-representation and labeling biases on some commonly used fair classifiers, and contained some almost obvious theoretical observations. Another work (in review) looks at investigating the phenomena of recovering Bayes optimal classifiers with biased data using fairness constraints, which is an extension of this work by Blum et al. Currently, we are also working on investigating the effects of noisy or uncertain protected attributes on fair classifiers, which started as an internship project with Prof. Shin’ichi Satoh at the National Institute of Informatics at Tokyo, Japan.

Earlier, I worked with large-scale noisy multi-labeled data and methods to efficiently learn from such data. In a not-so-distant past, I have worked with Speech Recognition, Emotion Detection and dabbled a little bit into Fake News Detection and Community Detection. Please have a look at my publications for more details.

Please get in touch if you want to collaborate with me on some interesting research projects. I am very interested in working in areas involving Long Term Decision Making, Statistical Learning Theory and Optimization.