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I am a PhD student in CSEE at University of Maryland, Baltimore County (UMBC), where I am currently working on Machine Learning and Deep Reinforcement Learning. I am co-advised by Dr Tinoosh Mohsenin and Dr Tim Oates I did my MS also at UMBC and BE at University of Pune. And then, I spent time at eBay/PayPal as a software enginner where I worked on PayPal Credit and PayPal Working Capital. Email / CV / LinkedIn / GitHub / Google Scholar |
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My research interests include machine learning and deep reinforcement learning (RL). Currently I am working on Safe RL and human in the loop RL, Multi-agent RL. |
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A framework to train RL agents conditioned on constraints that are in the form of structured language, thus reducing effort to design and integrate specialized rewards into the environment. In our experiments, we show that this method can be used to ground the language to behaviors and enable the agent to solve tasks while following the constraints. We also show how the agent can transfer these skills to other tasks. |
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A hybrid method for reducing the human intervention time by combining model-based and model-free approaches and training a supervised blocker to improve sample efficiency while also ensuring safety. We evaluate these methods on various grid-world environments using both standard and visual representations and show that our approach achieves better performance in terms of sample efficiency, number of catastrophic states reached as well as overall task performance compared to traditional model-free approaches. |
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Learning image representations on unannotated Chest Xray images using the method described in Noroozi and Favaro to gain improvements in classification tasks. Here we they use the pretext task of solving jigsaw puzzles to pre-train the convolutional neural network. Chest x-ray images from the x-ray14 database were used. |
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We propose a multitask learning (MTL) approach to design a grammatical error correction system that uses minimal parallel text for training by adding auxiliary tasks that aid the main GEC training objective. The proposed experiments include adding part of speech tagging and language modeling as these additional auxiliary tasks. |
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Using deep neural networks to colorize monochrome photos. Course project, Data Science. |
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Facebook chatbot to answer basic questions about the university. Natural language understanding, NER, information retrieval. |
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Developed an IVR system to process payments using PayPal APIs, Asterisk on Raspberry Pi. Internal hackathon at PayPal. |
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