Prof. Atlas Wang of Texas ECE has received several grants for his work on artificial intelligence. 

Prof. Wang is part of a research team that has received a DARPA grant for research on In Pixel Intelligent Processing. In addition, Prof. Wang and fellow researchers received a grant from the National Science Foundation (NSF) for work on Stimulating Collaborative Advances Leveraging Expertise in the Mathematical and Scientific Foundations of Deep Learning (SCALE MoDL).

Finally, Prof. Wang received a 2021 JP Morgan Faculty Award for his work on “Learning Optimizers Made Adaptable and Applicable to Multi-Agent Systems." It concerns the technological field of “learning to optimize”, and investigates its applications in financial AI.

Professor Zhangyang "Atlas" Wang is currently an Assistant Professor and Fellow of the Jack Kilby/Texas Instruments Endowed Faculty Fellowship in Computer Engineering in the Department of Electrical and Computer Engineering at The University of Texas at Austin. Prof. Wang is broadly interested in the fields of machine learning, computer vision, optimization, and their interdisciplinary applications. His latest interests focus on automated machine learning (AutoML), learning-based optimization, machine learning robustness, and efficient deep learning. 

He has received many research awards and scholarships, including most recently an ARO Young Investigator award, an IBM faculty research award, an Amazon research award, a Young Faculty Fellow of TAMU, and four research competition prizes from CVPR/ICCV/ECCV.