“If we knew what it was we were doing, it would not be called research, would it?”— Albert Einstein
Hello! I am currently a second year master’s student supervised by Eric Nalisnick. Previously, I studied Electrical Engineering at the Indian Institute of Technology Patna (IITP). I was also affiliated with the AI-NLP-ML lab while at IITP.
My general research interests are in AI Safety and Responsible AI, and aim to build systems that are transparent, reliable, trustworthy, etc. To this end, I am excited about uncertainty quantification, Human-in-the-loop and Interactive Machine Learning, etc. In my free time, I also take keen interest in the state of peer-review system, and research on improving the quality of peer-review process by addressing problems like biasedness, arbitrariness, inconsistency, etc. I also organise a Statistics Reading Group.
|Jun 13, 2022||New paper: On the Calibration of Learning to Defer to Multiple Experts accepted to the ICML’22 HMCaT Workshop. Work done with Daniel Barrejón and Eric Nalisnick.|
|May 15, 2022||Calibrated Learning to Defer with One-vs-All Classifiers will be presented at ICML’22.|
|Feb 8, 2022||New paper on the Calibration of Learning to Defer (L2D) systems: Calibrated Learning to Defer with One-vs-All Classifiers. We propose a new surrogate loss for L2D that is provably consistent and provides well-calibrated confidence estimates.|
|Nov 1, 2021||Started as ML/NLP researcher at CACTUS Communications.|
|Apr 1, 2021||Our MLRC reproducibility report was accepted to appear in ReScience Journal. Check it here.|
ACLDeepsentipeer: Harnessing sentiment in review texts to recommend peer review decisionsIn Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics 2019
ICMLCalibrated Learning to Defer with One-vs-All ClassifiersIn Proceedings of the 39th International Conference on Machine Learning (ICML) 2022