Kashyap Todi
Papers
1
Total Citations
21
H-Index
1
About
Kashyap Todi is a leading researcher in human-computer interaction (HCI), with a focus on computational interaction, adaptive user interfaces, and design tools. His work bridges machine learning and HCI to understand how people discover and adapt to interactive systems. In his highly cited paper "Rediscovering Affordance: A Reinforcement Learning Perspective" (2022, 21 citations), Todi proposes a novel framework that explains affordance-formation—how users learn and refine their perception of possible actions through interaction. This work integrates reinforcement learning principles to model the dynamic process of discovering interface capabilities, offering a theoretical foundation previously missing in HCI. Beyond this, Todi has made significant contributions to adaptive interfaces and design optimization, developing systems that personalize user experiences in real time. His research has been published at top venues like CHI and UIST, and he has received recognition for advancing our understanding of how humans interact with intelligent systems. With a growing citation impact, Todi’s work continues to shape the future of adaptive, user-aware computing.
Research Focus
Key Achievements
Top Papers
- 1Rediscovering Affordance: A Reinforcement Learning Perspective21 citations · 2022