I am a PhD student at ETH Zürich where I am advised by Prof. Mrinmaya Sachan and Prof. Thomas Hofmann
Before that, I spent two years as a Research Engineer at Microsoft Research Montréal where I worked with T.J. Hazen. Previously, I was a Master's student at UMass Amherst where I was advised by Prof. Andrew Mccallum.
My work includes building reasoning systems on large knowledge bases and collections of text. I am broadly interested in machine learning and its application in various fields of natural language processing.
I am grateful to be a recipient of the IBM PhD fellowship 2021
Calibration of Machine Reading systems at Scale
Shehzaad Dhuliawala, Leonard Adolphs, Rajarshi Das, and Mrinmaya Sachan.
ACL 2022 findings.
Case-based Reasoning for Better Generalization in Text-Adventure Games
Mattia Atzeni, Shehzaad Dhuliawala, Keerthiram Murugesan, and Mrinmaya Sachan.
International Conference on Learning Representations (ICLR) 2022.
TopiOCQA: Open-domain Conversational Question Answering with Topic Switching
Vaibhav Adlakha, Shehzaad Dhuliawala, Kaheer Suleman, Harm de Vries, and Siva Reddy
How to Query Language Models?
Leonard Adolphs, Shehzaad Dhuliawala, and Thomas Hofmann.
A Simple Approach to Case-Based Reasoning in Knowledge Bases
Rajarshi Das, Ameya Godbole, Shehzaad Dhuliawala, Manzil Zaheer, and Andrew McCallum.
Automated Knowledge Base Construction (AKBC) 2020
Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering
Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, and Andrew McCallum.
International Conference on Learning Representations (ICLR) 2019.
Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning
Shehzaad Dhuliawala*, Rajarshi Das*, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Alex Smola and Andrew McCallum.
International Conference on Learning Representations (ICLR) 2018. Also Won Best Paper at the workshop on Automated Knowledge Base Construction (AKBC) at Neurips 2017. [code]