Summary
Benjamin Kane is an applied research scientist specializing in neuro-symbolic AI, combining deep learning with logical reasoning and hierarchical planning to build explainable, predictable systems for high-stakes domains. With 11 years of experience and a PhD from the University of Rochester, he has designed dialogue management frameworks used in virtual patients and conversational tutors (SOPHIE, LISSA, DAVID) and published work on Bayesian models of communicative mental states. His internships bridged research and application—enabling robot concept learning via interactive dialogue and creating low-code BPMN tools that translate graphical flows into plan-based dialogue managers. Based in Rochester, NY, he brings a rare blend of cognitive robotics, formal planning, and applied dialogue systems expertise aimed at making AI both capable and accountable.
11 years of coding experience
2 years of employment as a software developer
High School, High School at Pittsford Mendon High School
Dual-Degree, Bachelor of Science (B.S.) Computer Science, Bachelor of Arts (B.A.) Economics, Dual-Degree, Bachelor of Science (B.S.) Computer Science, Bachelor of Arts (B.A.) Economics at University of Rochester
Computer Science, Computer Science at University of Bristol
English, Spanish