| Jan 15, 2024 | Our paper on an interpretable-by-design framework for image classification using Large Language and Vision models integrated with Information Pursuit (a greedy algorithm that makes predictions by sequentially asking informative questions about the input image) accepted as a conference paper at ICLR 2024! |
| Sep 22, 2023 | Our paper on an information theoretic perspective of Orthogonal Matching Pursuit and its applications to explainable AI was accepted at NeurIPS 2023 as a spotlight presentation! (acceptance rate: 3%). |
| Sep 16, 2023 | Presenting a poster at DeepMath 2023. |
| Jan 21, 2023 | Our paper on an information theoretic framework for making interpretable predictions (explainable-AI) was accepted as a journal paper at TPAMI, with a follow-up more efficient version accepted as a conference paper at ICLR 2023! |
| Sep 18, 2022 | Presenting a poster at DeepMath 2022. |
| May 6, 2021 | Honoured to receive the MINDS Fellowship for Spring and Summer semesters in 2021. |
| Sep 9, 2019 | Our work on explainable-AI advocating using causality to interpret neural networks via post-hoc attribution has been featured by Hindustan Times. Check out the article here   . |
