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About

Francesco Tassi has received his BSc and MSc in Mechanical Engineering at Politecnico di Milano, with a focus on Robotics and Mechatronics Engineering. He has received his PhD in 2023 from Politecnico di Milano, working at Istituto Italiano di Tecnologia (IIT) in the department of Human-Robot Interfaces and Interaction (HRI2), where he is currently a PostDoctoral researcher, in the field of advanced robotics and control. Previous to the PhD, he has worked as a research fellow at Consiglio Nazionale delle Ricerche (CNR) in the automation and robotics division. He developed his MSc thesis at the Jet Propulsion Laboratory (JPL) California, where he worked on the application of Model Predictive Control for the realization of a distributed space-based observatory.

Education

Title: PhD
Institute: Politecnico di Milano
Location: Milan
Country: Italy
From: 2020 To: 2023

Title: MSc in Robotics and Mechatronics Engineering
Institute: Politecnico di Milano
Location: Milan
Country: Italy
From: 2015 To: 2017

Title: BSc in Mechanical Engineering
Institute: Politecnico di Milano
Location: Milan
Country: Italy
From: 2012 To: 2015

All Publications
2025
Zhao J., Tassi F., Huang Y., De Momi E., Ajoudani A.
A combined learning and optimization framework to transfer human whole-body loco-manipulation skills to mobile manipulators
Robotics and Autonomous Systems, vol. 189
2025
Lahr G., Sirintuna D., Tassi F., Ben Mor H., Ajoudani A.
A Non-parametric Approach to Exploring and Quantifying the Information Flow in Human-Robot Collaboration
ACM Transactions on Human-Robot Interaction
Article in Press Journal
2025
Lagomarsino M., Arbaud R., Tassi F., Ajoudani A.
Mitigating Compensatory Movements in Prosthesis Users via Adaptive Collaborative Robotics
IEEE-RAS-EMBS International Conference on Rehabilitation Robotics (ICORR
Conference Paper Conference
2025
Liao Z., Tassi F., Gong C., Leonori M., Zhao F., Jiang G., Ajoudani A.
Simultaneously Learning of Motion, Stiffness, and Force From Human Demonstration Based on Riemannian DMP and QP Optimization
IEEE Transactions on Automation Science and Engineering, vol. 22, pp. 7773-7785
Article Journal
2024
Tassi F., Ajoudani A.
A Distributed Processing Approach for Smooth Task Transitioning in Strict Hierarchical Control
Proceedings - IEEE International Conference on Robotics and Automation, pp. 9830-9836
Conference Paper Conference
Oral presentations
2022
Tassi F., De Momi E., Ajoudani A.
An adaptive compliance Hierarchical Quadratic Programming controller for ergonomic human–robot collaboration
Robotics and Computer-Integrated Manufacturing, vol. 78
Journal
2021
Tassi F., de Momi E., Ajoudani A.
Augmented Hierarchical Quadratic Programming for Adaptive Compliance Robot Control
Proceedings - IEEE International Conference on Robotics and Automation, vol. 2021-May, pp. 3568-3574
Conference