Juha Plosila
Head of the Robotics and Autonomous Systems Unit
juplos@utu.fi +358 29 450 2621 +358 50 383 9453 Vesilinnantie 5 Turku ORCID identifier: https://orcid.org/0000-0003-4018-5495 |
autonomous systems; robotics; unmanned vehicles; drones; embedded systems; cyber physical systems; internet of things; smart systems; fog/edge computing; multi-agent systems; multiprocessors; network on chip; system on chip; multiprocessor system on chip; chip multiprocessors; heterogeneous systems; reconfigurable computing; digital circuits and systems; formal methods
Autonomous Systems Laboratory (ASL): https://asl.utu.fi/
Dr. Juha Plosila (born 1965) is Professor (full) in robotics and autonomous systems, Head of the Robotics and Autonomous Systems unit (cost centre), and Co-Lead of the Autonomous Systems Laboratory (ASL) research group (https://asl.utu.fi/) at the Department of Computing, Universitity of Turku. He received his PhD in electronics and communication technology from UTU in 1999 and his Adjunct Professor (Docent) title in digital systems design in 2006. He held a 5-year position of Academy Research Fellow (Academy of Finland) in 2006-2011 and served as a senior University Lecturer in embedded computing at UTU in 2011-2018. During his tenure at UTU since 2000, he has led many externally funded research projects, supervised more than 20 PhD theses, and served in the management committees of several master's programmes. Plosila has been an active participant in the European Institute of Innovation and Technology (EIT) knowledge and innovation community EIT Digital since 2011, leading the EIT Digital Master Programme in Embedded Systems (a European double-degree programme with 6 partner universities) and representing UTU in the EIT Digital Finland Node Strategy Committee.
Plosila's current research focuses on methodologies for the analysis, design, and control of networked autonomous systems, including different types of intelligent robotic systems as well as adaptive AI systems for runtime resource management in embedded and distributed computing. This combines expertise in the areas of robotics, multi-agent systems, optimisation, machine learning, computer vision, and computing systems design. He also has a strong background in network-on-chip design as well as in formal mehods for system design and verification.
Google Scholar statistics: https://scholar.google.com/citations?user=em4kCrUAAAAJ&hl=en
Lecturer for 18 different courses since 1999 in the fields of digital circuit and system design, multiprocessor architectures, computer architectures, reconfigurable computing, embedded systems, modelling and verification, as well as autonomous systems:
Autonomous Systems Architectures, MSc-level, 5 ECTS (2019- ); Regonfigurable Computing, MSc-level, 5 ECTS (at Fudan University, China, 2013- ); Processor Architectures, BSc-level, 5 ECTS (2020); Computer Architectures and Operating Systems, BSc-level, 4 ECTS (2017-2019), Multiprocessor Architectures, MSc-level, 5 ECTS, (2006, -08, -10, 2012-2018); System on Chip Design, MSc-level, 5 ECTS (2015-2016); Seminar on Embedded Computing, MSc/PhD-level, 5 ECTS (2012-2014); Modelling Parallel Systems, MSc-level (2011); Formal System Modelling and Verification, MSc-level, 5 ECTS, (2008, -10); Post Graduate Course on Digital Circuit & System Design, PhD-level; 5 ECTS (2009); Advanced Multiprocessor Systems, MSc-level, 5 ECTS (2009); System Verification, MSc-level, 5 ECTS (2007); Computer Architectures, BSc-level, 7 ECTS (2006-2007); Asynchronous System Design, MSc-level, 5 ECTS (2003, -05, -07); Formal System Specification and Design, MSc-level; 10 ECTS (2004, -06); Digital Integrated Circuit Design, BSc-level, 7 ECTS (2000-2005); Digital Systems Engineering, MSc-level, 10 ECTS (2001, -02, -04); Principles of Digital Design, BSc-level, 5 ECTS (1999-2000, -04).
- Development of a Fault-Tolerant Control System for a Swarm of Drones (2020)
- Proceedings ELMAR: International Symposium Electronics in Marine
(A4 Refereed article in a conference publication ) - Energy-Efficient Formation Morphing for Collision Avoidance in a Swarm of Drones (2020)
- IEEE Access
(A1 Refereed original research article in a scientific journal) - Enhancing Smart Grids via Advanced Metering Infrastructure and Fog Computing Fusion (2020)
- IEEE World Forum on Internet of Things
(A4 Refereed article in a conference publication ) - GeFeS: A generalized wrapper feature selection approach for optimizing classification performance (2020)
- Computers in Biology and Medicine
(A1 Refereed original research article in a scientific journal) - Heterogeneous Parallelization for Object Detection and Tracking in UAVs (2020)
- IEEE Access
(A1 Refereed original research article in a scientific journal) - Implementation of K-nearest Neighbor on Field Programmable Gate Arrays for Appliance Classification (2020)
- IEEE international conference on smart energy grid engineering
(A4 Refereed article in a conference publication ) - Implementation of non-intrusive appliances load monitoring (NIALM) on k-nearest neighbors (k-NN) classifier (2020)
- AIMS Electronics and Electrical Engineering
(A1 Refereed original research article in a scientific journal) - IoT Protocol Selection for Smart Grid Applications: Merging Qualitative and Quantitative Metrics (2020)
- International Convention on Information and Communication Technology, Electronics and Microelectronics
(A4 Refereed article in a conference publication ) - Monocular visual odometry based on hybrid parameterization (2020)
- International Conference on Machine Vision
(A4 Refereed article in a conference publication ) - Navigation of Autonomous Swarm of Drones Using Translational Coordinates (2020)
- Lecture Notes in Computer Science
(A4 Refereed article in a conference publication )



