I am a Research Fellow at Microsoft Research India, where I work with Prateek Jain and Harsha Simhadri in the Machine Learning and Optimisation (MLO) group and Intelligent Devices Expedition group. I do research on bringing state-of-the-art machine learning to severely resource-constrained devices. I am slated to finish my research fellowship at Microsoft Research in Spring 2019 after which I hope to work towards a PhD.
My current research focuses on designing theoretically sound and practical ML algorithms and systems. For instance,
- With my EMI-RNN work (accepted at NeurIPS '18), we speed-up RNN inference by up to 72x while simultaneously gaining on performance. As a concrete application, EMI-RNN brought real-time key-word spotting to devices like Raspberry Pi0 and MXChip. A demonstration was accepted at the MLPCD workshop at NeurIPS '18.
- The ProtoNN (prototypes + kNN) based machine learning pipeline I developed for GesturePod (in submission, CHI '19) does robust, accurate and real-time gesture recognition on 32kB of RAM and a 48MHz processor. GesturePod has been widely covered by the media and was Microsoft's official demonstration at NIPS '18.
My current focus is primarily academic, but I strongly feel about the impact cutting-edge technology can have for social good.
During our undergraduate years, Rito, Karan, Prashant and I started a venture - Weave, focused on creating micro-entrepreneurs in a marginalized weaver community. Although the start-up itself failed to gain much traction, it was an important lesson in building products with empathy.
It also set the ball rolling for our future endeavours: the journey somewhere along the line transformed into a new venture, rooting for healthcare access and affordability, using deep learning for diagnostics at ChironX. I continue to actively collaborate with Rito and Prashant at ChironX on designing their deep learning solutions and architectures.