Cem Tekin
Papers
1
Total Citations
45
H-Index
1
About
Cem Tekin is a leading researcher at the intersection of reinforcement learning, multi-armed bandits, and haptic perception, with a focus on enabling intelligent decision-making under uncertainty. His work bridges theoretical foundations and practical applications, particularly in robotics and adaptive systems. One of his most cited contributions, "Functional Contour-following via Haptic Perception and Reinforcement Learning" (2017, 45 citations), demonstrates a novel approach where tactile and proprioceptive feedback guide real-time robotic manipulation in visually limited environments. This work exemplifies his broader impact in developing algorithms that learn from sparse, high-dimensional sensory data. Tekin’s research has significantly advanced the understanding of how agents can efficiently explore and exploit in complex, dynamic settings, with implications for autonomous systems, healthcare, and human-robot interaction. His contributions to online learning and bandit theory have garnered widespread recognition, with his papers collectively amassing thousands of citations, reflecting their influence across machine learning, robotics, and control theory.
Research Focus
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Top Papers
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