I am currently a PhD student at Harvard, working in the EconCS group with Yiling Chen. Prior to this, I was a machine learning engineer at Cerebras Systems, where I built Tensorflow support for running very large models on our custom accelerator. I completed my Master’s degree in computer science at the University of Toronto where I was supervised by Nisarg Shah, and my bachelors degree in electrical and computer engineering from the same institution.

I am generally interested in questions related to strategic behaviour, fairness, and incentives in learning settings. I am currently interested in studying multi-agent scenarios in online learing. I am always happy to chat about these topics!

Recent

• 2023
  • Our paper Proportionally Fair Online Allocation of Public Goods with Predictions was accepted at IJCAI 2023! paper
• 2022
  • I joined the EconCS group at Harvard to start my PhD, and working with Yiling Chen.
• 2021
  • Our paper, Fair Algorithms for Multi-Agent Multi-Armed Bandits, was accepted at NeurIPS 2021! paper
• 2020
  • Our paper, The Effect of Strategic Noise on Linear Regression, was accepted at AAMAS 2020! paper
  • Our paper, Designing Fairly Fair Classifiers via Economic Fairness Notions, was accepted at WWW 2020 with Oral! paper
  • Our paper, Analyzing Text Specific vs Blackbox Fairness Algorithms in Multimodal Clinical NLP, was accepted at the 3rd Clinical Natural Language Processing Workshop at EMNLP paper! UPDATE: This paper was selected as the best short paper at the 3rd Clinical Natural Language Processing Workshop at EMNLP!
  • I have joined Cerebras Systems as a Machine Learning Engineer! Cerebras builds the world’s most powerful chip using wafer-scale integration to accelerate artificial intelligence by orders of magnitude. I will be initially working on the ML Frameworks team to provide integration with libraries like pyTorch and Tensorflow.
• 2019
  • Our paper, JacNet: Learning Functions with Structured Jacobians was accepted at the Invertible Neural Nets and Normalizing Flows workshop at ICML 2019!
  • Our paper, Generative Adversarial Networks for text using word2vec intermediaries was accepted at the 4th Workshop on Representation Learning at ACL 2019!
  • Our paper, The surprising power of hiding information in facility location, was accepted at AAAI 2020! paper
  • Began my internship at Xanadu, a quantum computing research firm, as part of a Mitacs internship. I am investigating the potential of multiple quantum circuits connected classically for machine learning applications