Greetings!

I am a third year PhD candidate in the Computer Science department at the University of Virginia advised by Dr. Aidong Zhang.

NEWS

MAY 2024: 2 papers accepted to KDD 2024 (Acceptance Rate: ~20%)

April 2024: Paper accepted to IJCAI 2024 (Acceptance Rate: ~15%)

April 2024: Awarded a $1000 Cohere Research Grant! Thanks Cohere

May 2023: Paper accepted to Interspeech 2023 (Acceptance Rate: ~48%)

April 2023: I passed my Qualification Exam. Officially a PhD Candidate now.

November 2022: Paper accepted to AAAI 2023 (Acceptance Rate: ~19.6%)

August 2021: Paper accepted to EMNLP’21 BlackBox Workshop.

May 2021: Started PhD at UVA CS.

Research Areas

I am broadly interested in interpretability and robustness of Machine Learning models. I explore all 3 verticals of explainability - local, instance and global.

Previously, I have been involved around biometric research in facial recognition on human-like faces at IAB Lab.

Industry Experience

In Summer, 2023 I interned at Alexa NLU, Cambridge, MA as an Applied Scientist Intern working on meta-learning based training approaches for LLMs.

In Summer, 2022 I interned at AWS Lex, Sunnyvale, CA as an Applied Scientist Intern working on domain adaptation of large speech models.

In Summer, 2020 I was a Machine Learning (Perception) Engineering intern at Unity, Seattle, WA in the AI@Unity division where I worked with image tracking and segmentation models for synthetic data.

Services

Reviewer:

AAAI, KDD, IJCAI, ICML (Invited) - 2024

ICDM, NeurIPS (Invited), NeurIPS XAIA - 2023

EMNLP - 2022

EMNLP Blackbox - 2022, 2023, 2024

EMNLP GenBench - 2023, 2024