Plan-SOFAI: A Neuro-Symbolic Planning Architecture
- Francesco Fabiano
- Vishal Pallagani
- et al.
- 2024
- AAAI 2024
Dr. Keerthiram Murugesan is a Research Staff Member at IBM Research AI specializing in Artificial Intelligence (AI), Machine Learning, and Natural Language Understanding. His research focuses on building reliable models and agents capable of adapting to changes and uncertainties in real-time scenarios. He earned his Ph.D. in Language Technologies and Machine Learning from Carnegie Mellon University in Pittsburgh, USA, in 2018. Dr. Murugesan has authored over 50 papers on various topics in machine learning at top-tier AI conferences and journals such as ICML, ICLR, NeurIPS, ACL, AAAI, IJCAI, and KDD. His current research includes Neuro-symbolic AI based on Thinking Fast and Slow, trustworthy foundational models with an emphasis on mitigating risks in Large Language Models (LLM), reasoning and planning in LLMs to advance their reliability and interpretability. His contributions have been integrated into IBM business products and are utilized by several enterprise clients. Additionally, he collaborates with government offices on policies related to the trustworthiness of foundational models and serves as a principal investigator or co-principal investigator of ongoing projects with universities.