Tanya Goyal is an assistant professor in the Computer Science department at Cornell University. Her research interests include building reliable and sustainable evaluation frameworks for large language models (LLMs) as well as understanding LLM behaviors as a function of training data and alignment strategies. Previously, she was a postdoctoral scholar at Princeton Language and Intelligence Center (2023-2024). Tanya completed her Ph.D. in Computer Science at UT Austin in 2023, advised by Dr. Greg Durrett. Her dissertation on fine-grained evaluation of summarization models received UT CS department's Bert Key dissertation award (2023).

Nancy F. Chen is an A*STAR fellow, who leads the Multimodal Generative AI group, heads the Artificial Intelligence for Education (AI4EDU) programme at I2R (Institute for Infocomm Research) and is a principal investigator at CFAR (Centre for Frontier AI Research), A*STAR. Dr. Chen’s recent work in large language models have won honors at ACL 2024, including Area Chair Award and Best Paper Award for Cross-Cultural Considerations in Natural Language Processing. Dr. Chen consistently garners best paper awards for her AI research applied to diverse applications. Examples include IEEE ICASSP 2011 (forensics), APSIPA 2016 (education), SIGDIAL 2021 (social media), MICCAI 2021 (neuroscience), and EMNLP 2023 (healthcare). Multilingual spoken technology from her team has led to commercial spin-offs and has been deployed at Singapore’s Ministry of Education to support home-based learning. Dr. Chen has supervised 100+ students and staff. She has won professional awards from USA National Institute of Health, IEEE, Microsoft, P&G, UNESCO, and L’Oréal. 

She servers as Program Chair of NeurIPS 2025, APSIPA Board of Governors (2024-2026), IEEE SPS Distinguished Lecturer (2023-2024), Program Chair of ICLR 2023, Board Member of ISCA (2021-2024), and is honoured as Singapore 100 Women in Tech (2021). Prior to A*STAR, she worked at MIT Lincoln Lab while pursuing a PhD at MIT and Harvard.