Hello everyone! I am Disha Shrivastava, a Research Scientist at Google DeepMind, London. My research focuses on enhancing the coding capability of large-scale generative models. In particular, I am interested in improving the ability of the model to iteratively refine its predictions and effectively leverage relevant context from execution, API usage and local repository.

I completed my PhD in Machine Learning at Mila, working with Hugo Larochelle and Danny Tarlow. As part of my thesis, I developed methods to identify relevant contextual cues and effectively leverage the selected cues for aiding deep learning models of code. During my PhD, I also worked as a Student Researcher at Google Brain, as a Research Scientist Intern at DeepMind, and as a Visiting Researcher at ServiceNow Research.

Prior to starting my PhD, I worked at IBM Research, India as a Research Software Engineer. My work focussed on unsupervised construction of knowledge graphs, metrics for computational creativity and topical coherence, and reasoning for maths question-answering. I graduated from IIT Delhi with a Masters in Computer Technology where I developed a data and model-parallel framework for training of deep networks in Apache Spark. I hold a Bachelors degree in Electronics and Communication Engineering from BIT Mesra.

I co-organized the Deep Learning for Code Workshops at ICLR 2022-23, AIPLANS Workshop at NeurIPS 2021 and Neurosymbolic Generative Models at ICLR 2023. When I am not teaching machines how to code, I like travelling to explore nature, cooking, reading books, singing and blogging!

Publications

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