Li Ang Zhang is an associate information scientist at the RAND Corporation and a professor at Pardee RAND Graduate School. His research interests include applying machine learning, optimization, and mathematical modeling towards the policy areas of defense and technology. He is particularly interested in adversarial artificial intelligence and how it will affect the pathway towards an AI-enabled society. Recently, he has been developing machine learning applications for satellite imagery and mission planning.
Prior to joining RAND, he focused on creating model-based decision support systems to tackle clinical problems in sepsis, a severe inflammatory syndrome. He made contributions towards sepsis evaluation and developing optimization tools. He received his Ph.D. in chemical engineering from the University of Pittsburgh.
Selected Publications
DR Kievlan, LA Zhang, CCH Chang, DC Angus, and CW Seymour, "Evaluation of repeated quick sepsis-related organ failure assessment measurements among patients with suspected infection," Critical Care Medicine, 46(12), 2018
LA Zhang, A Urbano, G Clermont, D Swigon, I Banerjee, RS Parker, "APT-MCMC, a C++/Python Implementation of Markov Chain Monte Carlo for Parameter Identification," Computers & Chemical Engineering, 110, 2017
LA Zhang, RS Parker, D Swigon, I Banerjee, S Bahrami, H Redl, G Clermont, "A One-Nearest-Neighbor Approach to Identify the Original Time of Infection using Censored Baboon Sepsis Data," Critical Care Medicine, 44(6), 2016
