Prof. Zhangyang “Atlas” Wang is a tenured associate professor and holds the Temple Foundation Endowed Faculty Fellowship #7 in the Chandra Family Department of Electrical and Computer Engineering at The University of Texas at Austin. He is also a faculty member of UT Computer Science, and the Oden Institute CSEM program. Since May 2024, Dr. Wang has been on leave from UT Austin to serve as the full-time Research Director for XTX Markets in New York City, leading groundbreaking efforts at the intersection of algorithmic trading and deep learning.

Previously, he was the Jack Kilby/Texas Instruments Endowed Assistant Professor in the same department from 2020 to 2023; and an Assistant Professor of Computer Science and Engineering at Texas A&M University from 2017 to 2020. Alongside his academic career, he has also explored multiple exciting opportunities in the industry. He was a visiting scholar at Amazon Search from 2021 to 2022, leveraging geometric deep learning for recommendation systems. Later, he took on the (part-time) role of Director of AI Research & Technology for Picsart from 2022 to 2024, where he led the company’s ambitious initiative in video generative AI. He earned his Ph.D. in Electrical and Computer Engineering from UIUC in 2016, under the guidance of Professor Thomas S. Huang, and his B.E. in EEIS from USTC in 2012.

Prof. Wang has broad research interests in machine learning (ML) and optimization. Currently, his research passion centers on establishing the theoretical and algorithmic foundations of generative AI and neurosymbolic AI. His primary goal is developing structured, modular representations that enable efficient and robust learning within overparameterized model spaces, seamlessly connecting to symbolic knowledge and reasoning. This central vision guides his focused pursuit of enhancing efficiency, trustworthiness, and reasoning capabilities in large language models (LLMs), as well as driving innovation in 3D/4D computer vision. His research is gratefully supported by NSF, DARPA, ARL, ARO, IARPA, DOE, as well as dozens of industry and university grants. Prof. Wang co-founded the new Conference on Parsimony and Learning (CPAL) and served as its inaugural Program Chair. He regularly serves as conference (senior) area chairs, journal editors, invited speakers, tutorial/workshop organizers, various panelist positions and reviewers. He is an ACM Distinguished Speaker and an IEEE senior member.

Prof. Wang has received many research awards, including an NSF CAREER Award, an ARO Young Investigator Award, an IEEE AI's 10 To Watch Award, an AI 100 Top Thought Leader Award, an INNS Aharon Katzir Young Investigator Award, a Google Research Scholar award, an IBM Faculty Research Award, a J. P. Morgan Faculty Research Award, an Amazon Research Award, a Sony Faculty Research Award, an Adobe Data Science Research Award, a Meta Reality Labs Research Award, and two Google TensorFlow Model Garden Awards. His team has won three best paper awards (NeuS 2025, IEEE SPS 2024, LoG 2022) and two honorable mentions (MLSys 2025, VLDB 2024), as well as five competition prizes at CVPR/ICCV/ECCV. He feels most proud of being surrounded by some of the world's most brilliant students: his Ph.D. students include winners of nine prestigious fellowships (NSF GRFP, Apple, NVIDIA, Adobe, IBM ×2, Amazon, Qualcomm, and Snap), among many other honors.