Hashem Haghbayan
PhD
hashem.haghbayan@utu.fi Työhuone: 456G ORCID-tunniste: https://orcid.org/ https://orcid.org/ 0000-0001-6583-4418 |
Embodied Intelligence, Cognitive Robotics, Energy Management in Robotics, Embedded Systems Design
Dr. Hashem Haghbayan is a senior researcher affiliated with the Autonomous Systems Laboratory (ASL) research group at the Department of Computing, University of Turku (UTU). He holds a Master's degree in computer architecture from the University of Tehran, awarded in 2009, and earned his Ph.D. with honors from the University of Turku in 2018. His doctoral research concentrated on resource management for computing platforms, specifically addressing chip-level constraints such as power and reliability. Post-Ph.D., Dr. Haghbayan has contributed to various research projects as a postdoctoral researcher at UTU. Notably, he spent six months, from January 2021 to June 2021, as a visiting researcher at the SAFARI research group in ETH Zürich. Additionally, he undertakes several visits to Politecnico di Milano University, supported by the Nokia Jorma Ollila Grant, which he has received for two consecutive years. Dr. Haghbayan has actively contributed to the academic community by serving as a reviewer for reputable international journals, including IEEE Transactions on Computers (TC), IEEE Transactions on Very Large Scale Integration Systems (TVLSI), IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), and ACM Transactions on Embedded Computing Systems.
Dr. Haghbayan's research interests span three main branches: 1) Computing Resource Management for Embedded Intelligent Systems: Focuses on the development of resource management algorithms to ensure the efficient execution of various applications in autonomous systems. Encompasses the creation of computing platforms tailored for AI and robotic applications, leveraging cutting-edge computer architectures.
Includes exploration of emerging computing platforms such as AI specialized architectures, processing in memory (PIM), memristors, and networked cloud-fog-edge. 2) Multi-Agent System Design and Programming: Concentrates on the development of efficient swarm intelligence, cognitive agent design, and agent-oriented programming. Aims to enhance the design and programming paradigms of multi-agent systems. 3) Artificial Intelligence for Autonomous Systems: Focuses on developing AI solutions for both computational and organizational management aspects of embedded intelligent systems. Aims to contribute to the advancement of artificial intelligence in the context of autonomous systems. Dr. Haghbayan's comprehensive research portfolio reflects a commitment to advancing computing resource management, multi-agent systems, and artificial intelligence, with implications for the efficient operation of embedded intelligent systems.
Multi-processor Architectures, Fall 2018, 5 ECTS (University of Turku); Autonomous Systems Architectures, Fall 2019, 5 ECTS (University of Turku); Autonomous Systems Architectures, Fall 2020, 5 ECTS (University of Turku); Autonomous Systems Architectures, Fall 2021, 5 ECTS (University of Turku); Autonomous Systems Architectures, Spring 2023, 5 ECTS (University of Turku); Autonomous Systems Architectures, Spring 2024, 5 ECTS (University of Turku); Hardware Accelerators for AI, Spring 2024, 5 ECTS (University of Turku)
- A Coordinated Approach to Control Mechanical and Computing Resources in Mobile Robots (2025)
- IEEE Transactions on RoboticsProceedings of the IEEE International Symposium on Industrial Electronics
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - A Novel Approach for Battery State-of-Health Estimation Using Convolutional Auto-Encoders (2025)
- European Control Conference
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - A Structural Simulation Framework for Cognitive Systems (2025) 2025 10th International Conference on Control and Robotics Engineering (ICCRE) Saukkio, Teemu; Plosila, Juha; Haghbayan, Hashem
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Co-Management of Computational and Mechanical Energy in Mobile Robots Using Reinforcement LearningDCP-SLAM: Distributed Collaborative Partial Swarm SLAM for Efficient Navigation of Autonomous Robots (2025)
- European Control ConferenceSensors
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Energy-Efficient Path Planning in Uneven Terrains Using Adaptive Reinforcement Learning (2025) 2025 10th International Conference on Control and Robotics Engineering (ICCRE) Warnakulasuriya, Diluna A.; Plosila, Juha; Haghbayan, Hashem
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Optimizing Energy Efficiency in Mobile Robots: A Battery-Aware Dynamic Path Planning Approach (2025) 2025 10th International Conference on Control and Robotics Engineering (ICCRE) Wu, Chen; Haghbayan, Hashem; Heydarzadeh, Mohsen; Immonen, Eero; Plosila, Juha
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Towards Optimizing Communication Cost in Energy Efficient IoT Devices for Swarm Robotics (2025)
- Procedia Computer Science
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Analysis of ECM Battery Modeling Techniques for Different Battery TypesHow to run a world record? A Reinforcement Learning approach (2024) 2024 13th International Workshop on Robot Motion and Control (RoMoCo) Heydarzadeh, Mohsen; Tehrani, Mohammad Gerami; Tahir, Anam; Immonen, Eero; Haghbayan, Hashem; Plosila, Juha
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - The Mountain Car Problem with a Dynamical and Finite Energy SystemPartial Swarm SLAM for Intelligent Navigation (2024) 2024 10th International Conference on Mechatronics and Robotics Engineering (ICMRE 2024) Immonen Eero, Haghbayan Hashem
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - A Coupled Battery State-of-Charge and Voltage Model for Optimal Control ApplicationsThread-level Parallelism in Fault Simulation of Deep Neural Networks on Multi-Processor Systems (2023)
- Proceedings : Design, Automation, and Test in Europe Conference and Exhibition
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - A Light-weight Model for Run-time Battery SOC-SOH Estimation While Considering Aging (2023)
- Proceedings: European Conference for Modelling and Simulation
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - An Extension of the Kinetic Battery Model for Optimal Control Applications (2023)
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - (2023)
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Run-time Resource Management in CMPs Handling Multiple Aging Mechanisms (2023)
- IEEE Transactions on Computers
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - An AI-in-Loop Fuzzy-Control Technique for UAV’s Stabilization and Landing (2022)
- IEEE Access
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Energy-efficient Post-failure Reconfiguration of Swarms of Unmanned Aerial Vehicles (2022)
- IEEE Access
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - (2022)
- Proceedings: European Conference for Modelling and Simulation
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - (2022)
- Lecture Notes in Computer Science
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - (2022) 2022 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT) Karami Masoomeh, Haghbayan Mohammad-Hashem, Ebrahimi Masoumeh, Miele Antonio, Plosila Juha
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Capacity loss estimation for li-ion batteries based on a semi-empirical model (2021)
- Proceedings: European Conference for Modelling and Simulation
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)



