Projects per year
Personal profile
Personal profile
Matteo Rubagotti earned his BSc and MSc in Computer Engineering, as well as his PhD in Electronics, Computer Science, and Electrical Engineering (track in Control Systems) from the University of Pavia, Italy. During his PhD studies, he spent research periods at the Center for Automotive Research at The Ohio State University, USA, and the Automatic Control Laboratory at ETH Zurich, Switzerland. He then held postdoctoral positions at the University of Trento and the IMT Institute for Advanced Studies, both in Italy.
In 2012, he joined Nazarbayev University as an Assistant Professor of Robotics. In 2015, he moved to the University of Leicester, UK, as a Lecturer in Control Engineering before returning to Nazarbayev University in 2018 as an Associate Professor of Robotics. He was promoted to Professor in 2024 after serving as Director of Graduate Studies at the School of Engineering and Digital Sciences from 2022 to 2024. Since 2024, he has been Acting Chair of the Robotics Department.
Dr. Rubagotti is a Senior Member of IEEE, a Fellow of the Higher Education Academy (HEA), and a recipient of the 2024 Control Engineering Practice (Elsevier) Best Paper Award. From 2020 to 2024, he was a Subject Editor for the International Journal of Robust and Nonlinear Control (Wiley), a Q1 journal in the field of control systems. Since 2013, he has also served as an Associate Editor for leading conferences in the field of control systems (CDC, ACC and ECC).
Research interests
His research interests include model predictive control, sliding mode control, and the application of control and optimization algorithms to solve research problems in robotics (variable-impedance-actuated robots, parallel manipulators, tensegrity robots, and physical human-robot interaction).
Teaching
At Nazarbayev University, Dr Rubagotti has been teaching a number of courses at undergraduate and graduate level in the fields of signal processing, applied mechanics, system dynamics, linear control theory, optimal control and robot motion planning.
External positions
Fingerprint
- 1 Similar Profiles
Collaborations and top research areas from the last five years
-
Safe and proactive motion planning for collaborative robots
Rubagotti, M. (PI), Folgheraiter, M. (Co-PI), Shintemirov, A. (Other Faculty/Researcher) & Bemporad, A. (Other Faculty/Researcher)
1/1/24 → 12/31/26
Project: FDCRGP
-
Designing an Energy-efficient Full-sized Humanoid Robot with Fast Adaptive Model-based Neuromorphic Control Architecture.
Folgheraiter, M. (PI), Rubagotti, M. (Co-PI) & Gini, G. (Other participant)
1/1/24 → 12/31/26
Project: FDCRGP
-
Development of Shared Autonomy Human–Machine Control Interfaces for Intelligent Wheelchair Mounted Robot Arm Systems
Sandygulova, A. (PI), Takhanov, R. (Co-PI), Yessenbayev, Z. (Co-PI), Daribayev, Z. (Co-PI) & Rubagotti, M. (Other Faculty/Researcher)
1/1/22 → 12/31/25
Project: CRP
-
E-skin: Neuromorphic Tactile Skin for Intelligent Robot – Environment and Robot - Human Physical Interaction
Kappassov, Z. (PI) & Rubagotti, M. (Co-PI)
1/1/22 → 12/31/24
Project: FDCRGP
-
Development of an Intrinsically Safe Actuation System with Adaptive Neuromorphic Control for Humanoid Robotics Application
Folgheraiter, M. (PI), Gini, G. (Other Faculty/Researcher) & Rubagotti, M. (Other Faculty/Researcher)
1/1/21 → 12/31/23
Project: FDCRGP
-
E-BTS: Event-Based Tactile Sensor for Haptic Teleoperation in Augmented Reality
Mukashev, D., Seitzhan, S., Chumakov, J., Khajikhanov, S., Yergibay, M., Zhaniyar, N., Chibar, R., Mazhitov, A., Rubagotti, M. & Kappassov, Z., 2025, In: IEEE Transactions on Robotics. 41, p. 450-463 14 p.Research output: Contribution to journal › Article › peer-review
-
Nonlinear model predictive control with set terminal constraint for safe robot motion planning via speed and separation monitoring
Nurbayeva, A. & Rubagotti, M., Jan 2025, In: Control Engineering Practice. 154, 106155.Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus) -
Safely Imitating Predictive Control Policies for Real-Time Human-Aware Manipulator Motion Planning: A Dataset Aggregation Approach
Nurbayeva, A. & Rubagotti, M., 2025, In: IEEE Access. 13, p. 3204-3214 11 p.Research output: Contribution to journal › Article › peer-review
Open Access -
A Discrete-Time Integral Sliding Mode Control Law for Systems With Matched and Unmatched Disturbances
Rubagotti, M., Incremona, G. P. & Ferrara, A., Apr 26 2024, In: IEEE Control Systems Letters. 8, p. 448-453 6 p., 3394001.Research output: Contribution to journal › Article › peer-review
Open Access3 Citations (Scopus) -
Deep reinforcement learning for PMSG wind turbine control via twin delayed deep deterministic policy gradient (TD3)
Zholtayev, D., Rubagotti, M. & Do, T. D., Jul 1 2024, In: Optimal Control Applications and Methods. 45, p. 1889-1906Research output: Contribution to journal › Article › peer-review
2 Citations (Scopus)