Vinay K. Chaudhri Email: vchaudhri@acm.org

About

I am passionate about Artificial Intelligence, knowledge engineering and their application to a variety of domains including finance, education and law. My journey on this path is characterized by leadership roles, groundbreaking research and successful implementation of innovative technologies.

I am currently the principal scientist at Knowledge Systems Research LLC. The primary activity is to support an NSF initiative on knowledge axiomatization. The goal is to formulate a research program in knowledge representation and reasoning that best complements deep learning and generative AI.

In my prior role at JPMorgan Chase, my team leveraged large language models for a banker note classification task with a potential to increase the business by $500M. I undertook a careful technical comparison of graph database systems to help inform firm's graph database strategy.

At Stanford University, I helped launch a highly successful initiative to bring logic education to high schools across America, undertook education research necessary to for an intelligent textbook product, and contributed to formation of computational contracts initiative.

At SRI International, I formed and led a team that undertook groundbreaking work in knowledge engineering creating the largest axiomatization for a biology book that was incorporated into an intelligent textbook. I also led the development of an ontology and query manager for an intelligent assistant that was the precursor to the Siri spinoff.



Opinion Pieces

• Kids Should be Taught to Think Logically (Scientific American)
• The time has come to reimagine college textbooks for the modern digital era (Hechinger Report)
• AI Must Be Taught Concepts, Not Just Patterns in the Raw Data (Nature)
• Truly Intelligent AI Could Play by the Rules, No matter How Strange! (Scientific American)
• When Rules Can be Code, They Should Be! (The Fulcrum)
• Should the AI Race Be About Bigger Models, or the Search for Meaning? (Tech.Policy)
• We need a new Turing test to assess AI’s real-world knowledge pdf (Nature)
• Commonsense Knowledge and Reasoning: A Grand Challenge for AI (Under Review)

• A Community-driven Vision for a new Knowledge Infrastructure for AI (Forthcoming)
• Knowledge Graphs: Introduction, History and Perspectives (AI Magazine)
• Achieving Intelligence using Prototypes, Composition, and Analogy (In Proceedings of the Conference for the Advancement of Artificial Intelligence
• A Case Study in Engineering a Knowledge Base for an Intelligent Personal Assistant (In the Proceedings of the Semantic Desktop Workshop)
• A Collaborative Environment for Authoring Large Knowledge Bases (In Journal of Ingelligent Information Systems
• Efficient Algorithms and Performance Results for Multi-User Knowledge Bases.(In International Joint Conference on Artificial Intelligence)

Textbooks

• Knowledge Graphs
• Logic Programming