Dr. Li joined as an assistant professor of computer science in the fall of 2023. Prior to this, he served as a Postdoctoral Researcher and earned his Ph.D. from the Department of Computer Science at UCLA, under the guidance of Prof. Judea Pearl, a distinguished recipient of the A.M. Turing Award. Dr. Li’s primary research interests encompass causal inference, artificial intelligence, and causality-based decision-making. His work centers on constructing causal models to estimate treatment effects (interventions) and assessing hypothetical scenarios, specifically, the outcomes if an individual had undergone a particular treatment (counterfactuals). Dr. Li has an impressive publication record, with over 10 papers featured in prestigious conferences such as AAAI, IJCAI, and AISTATS. His research extends beyond the realm of artificial intelligence, offering potential applications in diverse fields. Dr Li. collaborated with Toyota Research Institute on a project aimed at analyzing the demographics of potential charging station locations, demonstrating the practical utility of his research in real-world scenarios.
This Fall, Dr. Wu, holding a Ph.D. from Dartmouth College, will join the Department of Computer Science as an Assistant Professor. Renowned for his impactful research in Human Computer Interaction, Dr. Wu has published 18 papers at prestigious venues and earned notable awards, including a Best Paper Award at UIST 2019 and an Honorable Mention at CHI 2020. His research has received extensive coverage in media outlets such as NFCW, Engadget, and Times. Dr. Wu’s Ph.D. thesis focused on sensing through smart materials to facilitate natural and contextual interactions in various environments. He has since built on this foundation to develop scalable, sustainable, and intelligent ubiquitous computing by utilizing smart materials along with AI and sensing technologies. His work is notably interdisciplinary, spanning fields such as HCI/CS, ECE, Materials Science, and extending into Fashion and Arts. Additionally, he consistently contributes as a reviewer and chair, assessing papers for top venues including Nature Communications, CHI, and UIST.
Kai joined the department in August 2023 as an assistant professor. He received his Ph.D. from University of California, Riverside in 2022 and his B.S. from Peking University in 2014. He received the Dean’s Distinguished Fellowship (2017), the Dissertation Year Program Fellowship (2021), and the Laxmi N. Bhuyan Fellowship (2021) from University of California, Riverside. His research interests include scientific data management, reduction, and analytics, and fault-tolerant computing. He works closely with federal laboratories (Argonne National Laboratory, Oak Ridge National Laboratory) and industrial institutes (the EXPEC Advanced Research Center of Saudi Aramco) on data reduction techniques. He is the key developer and researcher of the SZ lossy compression software which won the 2021 R&D 100 Award. He has published more than 20 papers in prestigious conferences and journals, including SC, HPDC, PPoPP, VLDB, ICDE, ACM ICS, PACT, and TPDS. He has served as a technical program committee member or reviewer for conferences and journals such as TPDS, HPCC, CCGrid, and ICMLA. He has three-year professional experience (2014 – 2017) at Morgan Stanley, Alibaba, and MicroStrategy.