Dr. Susmit Jha
Title: Challenges and Opportunities in Generative AI for Automated Synthesis
Abstract: In this talk, we will review the recent progress on automated synthesis of software, hardware and cyberphysical system designs using large language models (LLMs) and neuro-symbolic AI that combine LLMs with formal methods. We will highlight the key challenges and opportunities presented by this transformative technology. We will then discuss avenues of using these synthesis methods to help co-design hardware-software for neuro-symbolic AI.
Dr. Susmit Jha is a Technical Director in the Computer Science Laboratory at SRI, where he leads the research group on Neuro-Symbolic Computing and Intelligence. Dr. Jha completed his Ph.D. in Computer Science from UC Berkeley in 2011, where his thesis work on “Automated Synthesis Using Structurally Constrained Induction and Deduction” was supported by Berkeley Fellowship and was awarded the Leon O Chua Award. His program synthesis work influenced the development of the FlashFill feature in Excel. Before joining SRI, Dr. Jha was at Intel Labs and Raytheon Technologies Research Center at Berkeley. At Intel, Dr. Jha’s research received a Division Recognition Award in 2012 and Research Technology Scoping Award in 2014. He received the 10-year Most Influential Paper award at IEEE/ACM ICSE 2020. He has published over 90 peer-reviewed publications with over 3700 citations in AI, ML, Formal Methods, and Automated Reasoning venues such as NeurIPS, ICLR, ICML, CVPR, AAAI, IJCAI, JAR, PLDI, and CAV. Dr. Jha has been a Principal Investigator on DoD and US Govt. programs on trustworthy, resilient, and neuro-symbolic AI, including DARPA Assured Autonomy, DARPA Neuro-symbolic Learning and Reasoning, DARPA Symbiotic Design of Cyber-physical Systems, IARPA TrojAI, NSF Self-Improving Cyber-Physical Systems, and Army Research Laboratory’s Internet of Battlefield Things REIGN CRA. He also serves on the technical advisory board of Confidencial Inc.