About me

I am a Postdoctoral Research Fellow at the Technical University of Vienna (TU Wien), working with Prof. Dongheui Lee. My research focuses on advancing safe and efficient human-robot collaboration through robotics and control theory. I apply concepts from nonlinear control and robot learning to various manipulators and grasping systems.

I completed my Ph.D. in Mechanical Engineering at IIT Gandhinagar in 2024, where I worked alongside Prof. Harish PM to develop human-inspired learning controllers and motion planners for robotic manipulators. My academic journey has been enriched by international research experiences, including visiting researcher positions at TU Wien, focusing on shared human-robot autonomy, and at the University of Texas at Austin, where I worked on single-degree-of-freedom gait training devices.

I have been fortunate to receive several recognitions for my work, including a gold medal at IIT Gandhinagar’s 13th convocation. My research has been supported by multiple grants, such as the DST NIDHI PRAYAS grant for developing an adaptive motion controller, the IEEE RAS Student Travel Grant, the SPARC Travel Grant for my work at UT Austin, and the IITGN Overseas Research Fellowship for my research at TU Wien. I also had the honor of winning the regional Boeing BUILD Bootcamp for startups.

News

May 2025: Happy to share that our paper “Demonstrating REASSEMBLE: A Multimodal Dataset for Contact-rich Robotic Assembly and Disassembly” has been accepted to Robotics: Science and Systems (RSS 2025)
May 2024: I completed my Ph.D. at IIT Gandhinagar, earning a gold medal in recognition of outstanding innovation.
May 2024: I presented our paper ‘Shared Autonomy via Variable Impedance Control and Virtual Potential Fields for Encoding Human Demonstrations’ at ICRA 2024 in Yokohama, Japan.

Publications

REASSEMBLE: A Multimodal Dataset for Contact-rich Robotic Assembly and Disassembly
Daniel Sliwowski, Shail Jadav, Sergej Stanovcic, Johannes Heidersberger, Jedrzej Orbik, Dongheui Lee
Robotics: Science and Systems (RSS 2025)
We release a multimodal dataset for long-horizon contact-rich assembly and disassembly tasks.
🔗 Project Page | 📄 PDF | 📝 arXiv

Shared Autonomy via Variable Impedance Control and Virtual Potential Fields for Encoding Human Demonstrations
Shail Jadav, Johannes Heidersberger, Christian Ott, Dongheui Lee
IEEE International Conference on Robotics and Automation (ICRA) 2024
This article introduces a framework for complex human-robot collaboration tasks, such as the co-manufacturing of furniture.
🔗 Project Page | 📄 PDF | 📝 arXiv

Configuration and force-field aware variable impedance control with faster re-learning
Shail Jadav, & Harish J Palanthandalam-Madapusi
Springer Journal of Intelligent & Robotic Systems (2024)
We introduce an innovative VIC algorithm that addresses typical VIC challenges.
📄 PDF | 📝 Link

A Machine-Learning-Based Method to Detect Degradation of Motor Control Stability with Implications to Diagnosis of Presymptomatic Parkinson’s Disease: A Simulation Study
Vrutangkumar V Shah, Shail Jadav, Sachin Goyal, Harish J Palanthandalam-Madapusi
MDPI Applied Sciences (2023)
We introduce an innovative ml & control theory based method for early diagnosis of Parkinson’s disease.
📄 PDF | 📝 Link

Kinematic Performance of a Customizable Single Degree-of-Freedom Gait Trainer for Cost-Effective Therapy Aimed at Neuromuscular Impairments
Shail Jadav , Karthik Subramanya Karvaje, Sujay D. Kadam, Vineet Vashista, James Sulzer, Ashish Deshpande, Harish J. Palanthandalam-Madapusi
ASME Journal of Medical Devices (2024)
We advance the development of a single degree-of-freedom (DOF) gait trainer for gait therapy for individuals with neuromuscular impairments.
📄 PDF | 📝 Link

Utilization of Manipulator Redundancy for Torque Reduction During Force Interaction
Shail Jadav, & Harish J Palanthandalam-Madapusi
ASME Letters in Dynamic Systems and Control (2024)
This paper introduces a novel objective function that responds to all external disturbances at the end-effector, aiming to lower joint torques via redundancy for precise trajectory tracking amidst disturbances.
📄 PDF | 📝 Link