Lisa Anne Hendricks

Papers

Total Citations

306

H-Index

About

Lisa Anne Hendricks is a researcher whose work sits at the compelling intersection of robotics, computer vision, and haptic perception. Her research focuses on enabling robots to develop a richer, more human-like understanding of the physical world by bridging visual and tactile sensing modalities. Her most influential contribution, "Deep Learning for Tactile Understanding from Visual and Haptic Data" (2016), has garnered over 250 citations and represents a landmark effort in teaching robots to predict haptic properties of objects and surfaces from visual input alone — a capability critical for real-world manipulation tasks. Complementing this, her work on PROTON, a visuo-haptic data acquisition system, demonstrates her commitment to building the foundational infrastructure needed for robotic learning, enabling the systematic collection of paired visual and tactile datasets across diverse surfaces. Hendricks' research addresses a fundamental challenge in robotics: how machines can anticipate physical interactions before contact occurs. By combining deep learning with multimodal sensory data, she has helped lay the groundwork for more capable, adaptive robotic systems, making her a notable contributor to the growing field of robot perception and embodied artificial intelligence.