Dipankar Bhattacharya
Imperial College London, Centre for Transformative Garment Production, University of Auckland, IIT Roorkee, Hong Kong University, North Eastern Regional Institute of Science and Technology
About
I am a Marie Skłodowska-Curie Fellow at Imperial College London, developing AI-driven soft robotic exosuits for upper-limb rehabilitation. My work focuses on adaptive assistive technologies for people with Parkinson’s, combining human experiments, EMG, digital twins, and reinforcement learning. I was awarded the Horizon Europe Marie Skłodowska-Curie Fellowship for my research in rehabilitation robotics.
I am motivated by the opportunity to translate robotics and AI into clinically meaningful rehabilitation technologies. My goal is to build intelligent, human-centered systems that improve movement, recovery, and quality of care.
My background includes soft robotics, cable-driven systems, AI-based deformable-object robotic manipulation, and control. I have developed robotic systems for fabric manipulation, cable-driven robot modelling and control, and a soft robotic oesophagus for stent testing, applying modelling, perception, and learning-based methods across healthcare and automation.
My academic and research journey has taken me across four countries — from an M.Tech. in India, to a PhD in New Zealand, to research and engineering roles in Hong Kong, and now to London as a Marie Skłodowska-Curie Fellow — giving me a global and interdisciplinary perspective on robotics research. My work is supported by a strong record of competitive funding, peer-reviewed research, and international professional recognition. I was awarded several fellowships and grants, and my research has led to publications in leading journals including IEEE Transactions on Control Systems and Technology, IEEE Transactions on Industrial Electronics, and Soft Robotics. I have also shared this work through invited talks at Imperial College London and the World Robotics Conference, with recent work selected for oral presentation at ICRA 2026, and I serve as a reviewer for IEEE Robotics and Automation Letters, ICRA, and the ASME Journal of Mechanisms and Robotics. Earlier in my academic journey, I ranked in the 99.12 percentile in India’s GATE examination and 31st in the All India Junior Mathematics Olympiad.
I value collaboration, mentorship, and translational research, and I am always happy to connect with researchers, clinicians, engineers, and industry partners working in robotics, AI, rehabilitation, and healthcare technologies.
Employment
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Imperial College London Marie Skłodowska-Curie Fellow2025 - Present
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Centre for Transformative Garment Production Senior Research Engineer-Control Systems2024 - 2025
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Hong Kong University Visiting Research Associate2024 - 2025
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The Chinese University of Hong Kong Post Doctoral Research Fellow2021 - 2024
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Laboratoire des Sciences du Numérique de Nantes Visiting Postdoctoral Fellow2021 - 2022
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The University of Auckland Graduate Teaching Assistant2017 - 2020
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The University of Auckland Graduate Teaching Assistant2017 - 2020
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Galgotias University Lecturer2013 - 2015
Education
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University of Auckland Doctor of Philosophy2016 - 2020
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IIT Roorkee M.Tech2011 - 2013
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North Eastern Regional Institute of Science and Technology Bachelors of Technology2004 - 2010
Projects & Funding
Projects & funding information is unavailable.
Publications (21)
- RTFF: Random-to-Target Fabric Flattening Policy Using Dual-Arm Manipulator Save
- Robotic Fabric Alignment System for Sewing Using Global-Local Weighted ICP Save
- Robotic fabric alignment system for sewing using global local weighted ICP Save
- RTFF: random-to-target fabric flattening policy using dual-arm manipulator Save
- Kinematic and dynamic modeling of cable-object interference and wrapping in complex geometrical-shaped cable-driven parallel robots Save
- A Novel Fabric Alignment System for Sewing Save
- Precise top-layer fabric segmentation for fabric destacking with edge- and shape-aware deep networks Save
- Automated Straight-Line Sewing of Stretchable Fabrics With Different Lengths Save
- Precise Top-layer Fabric Segmentation for Fabric Destacking with Edge- and Shape-Aware Deep Networks Save
- Kinematic Modeling of Cable Wrapping in Complex Geometrical-Shaped Cable-Driven Parallel Robots Save