About me

I am a Senior AI Research Scientist at Zoom, where I work on foundation models, multimodal AI, and agentic AI, with a focus on building systems that deliver strong real world performance.

My work centers on advancing Zoom’s federated AI systems. I lead system design and execution in close collaboration with researchers and engineers across teams, contributing to work that achieved state of the art results on both Humanity’s Last Exam and DeepSearchQA, two challenging benchmarks for evaluating frontier AI reasoning, retrieval, and generalization. [HLE blog] [Federated AI blog]

I am particularly interested in hard problems at the system level, where modeling choices, infrastructure design, and team execution intersect. I enjoy turning complex research ideas into robust, scalable systems, and translating them into results that matter in practice.

I developed this interest during my doctoral training at Yale University. My journey at Yale began under the mentorship of the late Prof. Dragomir Radev, who recognized and nurtured my interest in NLP research and brought me into the PhD program. During my early years at Yale, he provided invaluable guidance and support that shaped my academic direction and growth. In my final year, I was fortunate to be advised by Prof. Arman Cohan, who stepped into this role during a period of transition with thoughtfulness and dedication. His insightful feedback, patience, and commitment to research and mentorship were instrumental in helping me navigate challenges and complete my doctoral work.

Before Yale, I received my MS in Computer Science from Columbia University SEAS, where I was advised by Prof. Michael Collins. I completed my undergraduate studies at the College of William and Mary, graduating Summa cum laude in 2018 with double majors in Mathematics and Computer Science. These earlier experiences laid a strong foundation for my later work in machine learning and natural language processing.

Recent News

[03/2024] Area Chair for ACL Rolling Review (ARR), 2023-Present
[10/2023] 3 papers accepted to EMNLP 2023.

Selected Work

For a full list, please refer to my Google Scholar.

• On Evaluating the Integration of Reasoning and Action in LLM Agents with Database Question Answering
  Linyong Nan, Ellen Zhang, Weijin Zou, Yilun Zhao, Wenfei Zhou, Arman Cohan.
  Findings of the Association for Computational Linguistics: NAACL 2024

• Enhancing Few-shot Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies
  Linyong Nan, Yilun Zhao, Weijin Zou, Narutatsu Ri, Jaesung Tae, Ellen Zhang, Arman Cohan, Dragomir Radev.
  Findings of the Association for Computational Linguistics: EMNLP 2023.

• R2D2: Robust Data-to-Text with Replacement Detection [code]
  Linyong Nan, Lorenzo Jaime Flores, Yilun Zhao, Yixin Liu, Luke Benson, Weijin Zou, Dragomir Radev.
  Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022.

• FeTaQA: Free-form Table Question Answering [dataset]
  Linyong Nan, Chiachun Hsieh, Ziming Mao, Xi Victoria Lin, Neha Verma, Rui Zhang, Wojciech Kryściński, Nick Schoelkopf, Riley Kong, Xiangru Tang, Murori Mutuma, Ben Rosand, Isabel Trindade, Renusree Bandaru, Jacob Cunningham, Caiming Xiong, Dragomir Radev.
  Transactions of the Association for Computational Linguistics (TACL), 2022.

• DART: Open-Domain Structured Data Record to Text Generation [dataset]
  Linyong Nan, Dragomir Radev, Rui Zhang, Amrit Rau, Abhinand Sivaprasad, Chiachun Hsieh, Xiangru Tang, Aadit Vyas, Neha Verma, Pranav Krishna, Yangxiaokang Liu, Nadia Irwanto, Jessica Pan, Faiaz Rahman, Ahmad Zaidi, Mutethia Mutuma, Yasin Tarabar, Ankit Gupta, Tao Yu, Yi Chern Tan, Xi Victoria Lin, Caiming Xiong, Richard Socher, Nazneen Fatema Rajani.
  Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), 2021.

• Detecting Urgency Status of Crisis Tweets: A Transfer Learning Approach for Low Resource Languages
  Efsun Sarioglu Kayi, Linyong Nan, Bohan Qu, Mona Diab, Kathleen McKeown.
  Proceedings of the 28th International Conference on Computational Linguistics (COLING), 2020.

Work Experience

• Microsoft Research, Redmond, WA, Summer 2023
  Research Intern
• Amazon.com, Inc., New York, NY, Summer 2022
  Research Intern
• Microsoft Research Asia, Beijing, China, Summer 2021
  Research Intern
• Yale University, New Haven, CT, 2021-2022
  Teaching Fellow
• Harvard University, Boston, MA, Summer 2019
  Research Assistant
• Columbia University, New York, NY, 2018-2020
  Research Assistant

Miscellaneous

When I’m not immersed in research, I find joy in various hobbies. I’m an avid reader and love exploring new places through travel. Music is another passion of mine, and I enjoy playing the piano, especially classical and jazz pieces.

I grew up bilingual, speaking both Mandarin Chinese and Korean.

Hackathons are another area where I love to engage and challenge myself:

• At PennApps XVIII in Philadelphia, PA, 2018, our team won the Best VR/AR Hack. We developed ARound, an iOS app that enhances city exploration through a phone camera with Augmented Reality (AR) features.
• We were the First Runner-up at TribeHacks IV in Williamsburg, VA, 2018, with our innovative project Cockpit. This program enables real-time drone control using hand gestures.