Professor Steven Euijong Whang visited NYU R/AI on October 30, 2024, and gave a talk on his recent work.

Recent Advances in Data-centric Responsible AI and the NYU-KAIST Collaboration

Abstract: Data-centric Responsible AI is becoming critical as AI is widely used in our everyday lives. In addition to improving a model’s accuracy, it is important to improve other aspects including fairness, robustness, privacy, explainability, value alignment, and more. These objectives not only need to be satisfied during model training, but in all steps of machine learning starting from the data. In this seminar, I will talk about three recent works from our lab towards this goal: (1) Falcon: fair active learning for data labeling (VLDB’24), (2) RC-Mixup: robust data augmentation for regression tasks (KDD’24), and (3) ERBench: an LLM hallucination benchmark using relational databases (NeurIPS’24 Spotlight). I will also introduce our recent Global AI Frontier Lab collaboration with NYU under the project titled “AI Guardians: Development of Robust, Controllable, and Unbiased Trustworthy AI Technology”.

Speaker’s bio: Steven Euijong Whang is an associate professor with tenure at KAIST EE and AI and leads the Data Intelligence Lab. His research interests include Responsible AI and Data-centric AI. He is an Associate Editor of VLDB 2025, IEEE TKDE (2023-25), and IEEE Data Eng. Bulletin (2023-24), and an Area Chair of ICLR 2025. Previously he was a Research Scientist at Google Research and co-developed the data infrastructure of the TensorFlow Extended (TFX) machine learning platform. Steven received his Ph.D. in computer science in 2012 from Stanford University. He was a Kwon Oh-Hyun Endowed Chair Professor (2020-2023) and received a Google AI Focused Research Award (2018, the first in Asia).