Mentorship

I have been fortunate to work with many talented interns and pre-doctoral researchers over the years.

Pre-doctoral researchers

• Jacob Morrison → PhD student, University of Washington
• Lj Miranda → PhD student, University of Cambridge
• Xinxi Lyu → PhD student, University of Illinois Urbana-Champaign

Interns

• Shakti Senthil, Senior, University of Washington (2025)
• Clara Na, PhD student, Carnegie Mellon University (2023)
  • Scalable Data Ablation Approximations for Language Models through Modular Training and Merging (EMNLP 2024)
• Arkil Patel, Masters student, McGill University (2023)
  • Evaluating In-Context Learning of Libraries for Code Generation (NAACL 2024)
• Tom Sherborne, PhD student, University of Edinburgh (2023)
  • TRAM: Bridging Trust Regions and Sharpness Aware Minimization (ICLR 2024 Spotlight)
• Kalpesh Krishna, PhD student, University of Massachusetts, Amherst (2022)
  • LongEval: Guidelines for Human Evaluation of Faithfulness in Long-form Summarization (EACL 2023 Outstanding Paper)
• Revanth Gangi Reddy, PhD student, University of Illinois Urbana-Champaign (2022)
  • A Large-Scale Study of Reranker Relevance Feedback at Inference
• Bhargavi Paranjape, PhD student, University of Washington (2022)
  • AGRO: Adversarial Discovery of Error-prone groups for Robust Optimization (ICLR 2023)
• Vidhisha Balachandran, PhD student, Carnegie Mellon University (2021)
• Yuxiang Wu, PhD student, University College London (2021)
  • Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets (ACL 2022)
• Ansong Ni, Masters student, Carnegie Mellon University (2020)
  • Mitigating False-Negative Contexts in Multi-document Question Answering with Retrieval Marginalization (EMNLP 2021)
• James Ferguson, PhD student, University of Washington (2020)
  • IIRC: A Dataset of Incomplete Information Reading Comprehension Questions (EMNLP 2020)
• Zhanming Allan Jie, PhD student, Singapore University of Technology and Design (2019)