Tanjulee Siddique
Papers
6
Total Citations
24
H-Index
3
About
Tanjulee Siddique is an emerging researcher specializing in rehabilitation robotics, intelligent control systems, and reinforcement learning-based approaches for assistive technologies. Her work sits at the intersection of artificial intelligence and biomedical engineering, with a particular focus on developing autonomous systems to support upper extremity rehabilitation for stroke survivors and elderly patients with motor disabilities. Siddique's most influential contribution — an autonomous fuzzy-logic-based exercise generator for upper limb rehabilitation (2022, 9 citations) — addresses a critical gap in fully autonomous robotic therapy by enabling personalized exercise recommendations derived from patient-specific range-of-motion data. Complementing this, her research into actor-critic deep reinforcement learning controllers (2023, 5 citations) advances intelligent, adaptive robotic therapy with reduced reliance on human supervision. Her exploration of physics-informed reward shaping (2025, 4 citations) further demonstrates her commitment to bridging classical control theory with modern machine learning techniques. Beyond rehabilitation, Siddique has investigated tracking control for multi-degree-of-freedom robot manipulators using DDPG agents and Active Disturbance Rejection Controllers tuned via reinforcement learning, broadening the applicability of her methods. With a growing body of work accumulating over 24 citations, she represents a promising voice in intelligent rehabilitation robotics research.
Research Focus
Key Achievements
Top Papers
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- 4Evaluation of UE Exercises using NAO Robot for Poststroke Disabilities3 citations · 2022
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