Chris Brown

North Carolina State University, University of Rochester

Papers

Total Citations

H-Index

About

Chris Brown’s research bridges the gap between human developers and automated systems, with a primary focus on software engineering bots and robot skill learning. His most cited work, “Sorry to Bother You Again” (2020, 11 citations), investigates the challenges developers face when interacting with software bots—automated tools that streamline programming tasks—and proposes improvements to make these interactions more effective. Earlier, Brown made foundational contributions to robotics through his 2002 paper “Robot skill learning, basis functions, and control regimes” (10 citations), which introduced a computational theory for tunable, open-loop trajectory skills. This work defined skills as controllers capable of handling families of tasks parameterized by multiple variables, with learning framed as a search for optimal output generation. His 1992 PhD thesis, “Robot Skill Learning and the Effects of Basis Function Choice” (4 citations), further explored how the selection of basis functions impacts skill acquisition, drawing on reinforcement learning concepts. Though his citation counts are modest, Brown’s research offers practical insights into human-robot interaction and automated development tools, making his work valuable for engineers and researchers seeking to improve collaboration between humans and intelligent systems.