STR Technical Talk
Hybrid - in person or on Zoom
Content
STR representatives will give a technical talk that describes STR’s work in machine learning and reinforcement learning. The talk will give short, technical overviews of a few sample research efforts: (1) an RL project that is developing AI adversaries for combat pilots, (2) an alternative to supervised learning called in-context learning, which STR has applied to pattern-of-life learning, and (3) a new technique for identifying out-of-distribution data. Some familiarity with ML/RL will be assumed.
The speakers will be:
Zhongheng Li (Heng) is a Senior Machine Learning Engineer at STR, architecting research and production ML solutions for various DoD agencies with publications across multiple domains, from big-data and computer visions to geospatial representation learning with LLM. For the past four years, Heng spearheaded multiple reinforcement learning (RL) initiatives and served as team lead on multiple applied deep RL programs, driving the research and development efforts on large-scale multi-agent Competitive & Collaborative tasks. Heng also organizes the STR RL Reading Group and a series of internal STR Deep RL Classes. Heng earned his M.S. in Computer Science from New York University and conducted research on explainable AI at NYU Game Innovation Lab and carbon footprint estimation using near real-time crowdsourced transportation data at NYU Urban Intelligence Lab. He received a B.S. from Stony Brook University in applied mathematics & statistics and Information Systems. Heng is also a certified SCRUM Master and AWS Solution Architect.
Alex George is a principal researcher at STR where he focuses on developing AI/ML solutions to complex problems. Particular areas of interest include reinforcement learning for large-scale simulation, automatic target recognition, and physics-based machine learning. Alex earned his PhD in experimental particle physics from the University of California, Santa Barbara where he worked on the CERN-based experiments that discovered the Higgs Boson, and his BS in physics and mathematics from the University of Pittsburgh.