1. Design and implementation of embedded systems based on reconfigurable circuits (FPGAs and System-on-Chips)
2. Designing embedded neuro-processors applied in preprocessed biological signal classification
3. Mobile robot control applications implemented on embedded systems based on FPGAs
4. Design of embedded electronic systems with applications in the automotive industry
5. Design and development of automated control systems with embedded microcontrollers and processor based microsystems
6. Design and development of SCADA systems based on industrial communication systems
7. Implementation of motion detection and extraction algorithms from video sequences, on System-on-Chip devices

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Main research and innovation topics

• Reconfigurable digital system based design - FPGA, SoC
• Artificial intelligence
• Resource and power efficient embedded computation design and development

In the last 20 years, members of our staff have published approximately 100 scientific papers related to the topics listed above, yielding more than 120 independent citations.

Further research areas

Embedded systems, Digital reconfigurable devices, Processor architectures, Hardware-software co-design, Artificial intelligence, Neuromorphic neural networks, Hardware Neural Networks, Multi-core systems, SoC, VLSI systems, RISC microprocessor design using FPGA circuits, Real-time control systems, Industrial & automotive communication systems.

Most important publications

• Bakó L., “Real-time classification of datasets with hardware embedded neuromorphic neural networks”, Briefings in Bioinformatics, Special Issue: Parallel and Ubiquitous Methods and Tools in Systems Biology: May 2010; Vol. 11, No. 3, p348-363, doi: 10.1093/bib/bbp066, Oxford University Press (Impact Factor: 7.329, 12 independent citations)
• Bakó L., Brassai, S.T., “Embedded neural controllers based on spiking neuron models,”, Pollack Periodica, An International Journal for Engineering and Information Sciences, DOI: 10.1556/Pollack.4.2009.3.13, Vol. 4, No. 3, pp. 143-154, Akadémiai Kiadó, Budapest, Hungary, ISSN 1788-3911, SJR-SCImago Journal & Country Rank:0,031.
• Brassai, S.T., Bakó L., “Visual Trajectory Control of a Mobile Robot Using FPGA Implemented Neural Network”, Pollack Periodica, An International Journal for Engineering and Information Sciences, Pollack.4.2009.3.12, Vol. 4, No. 3, pp. 129–142 (December 2009), Akadémiai Kiadó, Budapest, Hungary, ISSN 1788-3911, SJR 0,031.
• Bakó L., Székely I., Brassai S.T., “Development of Advanced Neural Models. Software And Hardware Implementation”, Timişoara, Transaction on Electronics and communication, Scientific buletin of the „Politehnica” University of Timişoara, 2004, p214-219, ISSN 15833380 (Cat. B+)
• Brassai S.T., Dávid L., Bakó L., Hardware Implementation of CMAC based artificial network with process control application, Timişoara, Transaction on Electronics and communication, Scientific buletin of the „Politehnica” University of Timisoara, 2004, p209-213, ISSN 1583-3380 (Cat. B+)
• Bakó, L., „Real-time clustering of datasets with hardware embedded neuromorphic neural networks”, HiBi 2009 (High performance computational systems Biology) Workshop, COSBi (Microsoft Research - University of Trento Centre for Computational and Systems Biology), Trento, Italy, October 14-16, 2009, Published by IEEE Computer Society, ISBN 978-0-7695-3809-9, pp 13-22, DOI: 10.1109/HiBi.2009.24, ISI proceedings, (2 independent citation).
• Bakó, L., Brassai, S.T., Székely, I., Baczó, M., Hardware Implementation of Delay-coded Spiking-RBF Neural Network for Unsupervised Clustering, Proceedings of the 11th International Conference on Optimization of Electrical and Electronic Equipment, ISBN9789731310329, pp51-56, Transilvania Univ. of Brasov, 2008, Brasov, ISI proc. (1 independent citation)
• Brassai, S.T., Bakó, L., Székely, I., Dan, Ş., ”Neural Control Based on RBF Network implemented on FPGA” Proceedings of the 11th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM ’08), ISBN 978-973-131-032-9, pp41-46, Transilvania University of Brasov, Braşov, 2008, ISI proceedings. 9. (3 independent citations)
• Brassai S.T., Bakó L., Dan Ş., FPGA Parallel Implementation of CMAC Type Neural Network with on Chip Learning, SACI 2007, Budapest Tech, Hungary, 2007, 111-115, ISBN: 142441234X, ISI proceedings, (1 independent citation).
• Bakó L., Brassai S.T., Székely I., Fully Parallel Implementation of Spiking Neural Networks on FPGA, Proceedings of the 10th International Conference on Optimization of Electrical and Electronic Equipment, Braşov (Moeciu), Volume III, pp135-142, ISBN 973-635-705-8, Trasilvania University Press, 2006, ISI proceedings.
• Bakó L., Brassai S.T., Hardware spiking neural networks: parallel implementations using FPGAs, Proceedings of the 8th WSEAS Int. Conference on Automatic Control, Modeling and Simulation, Prague, Czech Republic, March 12-14, 2006 (pp. 261-266), ISBN 960-8457-42-4, ISSN 1790-5117, (1 independent citation).
• Bakó, L., Székely, I., „Challenges for implementations of delay-coded neuromorphic neural networks on embedded digital hardware”, 2nd INCF Congress of Neuroinformatics, Pilsen, Czech Republic, September 6-8, 2009, Abstract book, p132-133.
• Bakó L., Fülöp P.I., „Evolving Advanced Neural Networks on Run-Time Reconfigurable Digital Hardware Platform”, Sixth International PhD, DLA Symposium, University of Pécs, Hungary, Pollack Mihály Faculty of Engineering, 25-26 October, 2010, Edited by Prof. Miklós Iványi, Rotari Press, Komló, Hungary.
• Bakó L., “Hardware Implementations of Artificial Neuromorphic Neural Network Systems using Reconfigurable Digital Devices”, Poster, 2011 EDAA / ACM SIGDA PhD Forum at Design, Automation & Test in Europe (DATE) in Grenoble, France, March 14-18, 2011.
• L. Losonczi, L. Bakó, S.T. Brassai, L. Katona, L.F. Márton, Portable EEG Signal Measuring and Processing Network, TOBI Workshop III, Bringing BCIs to End-Users: Facing the Challenge: Evaluation, User Perspectives, User Needs, and Ethical Questions, Würzburg, Germany, March 20-22, 2012, pp.37-38.
• L. Losonczi, L. Katona, T.J. Viney, L. Bakó, S.T. Brassai, L.F. Márton, “Neurobiological, smart signal acquisition and improved information extraction methods”, 2012, 8th Forum of Neuroscience (FENS), July 14-18, 2012, Barcelona, Spain.
• Bako, L.; Brassai, S.; Kolcsar, A.; Losonczi, L.; Marton, L., „Neuromorphic Neural Network Parallelization on CUDA Compatible GPU for EEG Signal Classification”, IEEE Computer Modeling and Simulation (EMS), 2012 Sixth UKSim/AMSS European Symposium on, Valetta, Malta, 14-16 Nov. 2012, pp.359-364, ISBN 978-1-4673-4977-2, DOI 10.1109/EMS.2012.87. (IEEExplore)
• Bakó, L., Brassai, S.T., Losonczi L. and Márton, L.F., “Multiple processor core systems on FPGA circuits implementing bio-inspired neural networks for classification tasks”, 8th International Conference on High-Performance and Embedded Architectures and Compilers (HiPEAC), 2nd Workshop on Design Tools and Architectures for Multi-Core Embedded Computing Platforms (DITAM’13), January 21-23, 2013, Berlin, Germany.
• Brassai, S.T., Bakó, L., Losonczi L. and Márton, L.F., “Parallel pipeline solution for hardware implementation of artificial neural networks with in circuit real time weight update”, 8th International Conference on High-Performance and Embedded Architectures and Compilers (HiPEAC), 2nd Workshop on Design Tools and Architectures for Multi-Core Embedded Computing Platforms (DITAM’13), January 21-23, 2013, Berlin, Germany.
• Bakó, L., Brassai, S.T., Losonczi L. and Márton, L.F., “Evolving advanced neural networks on run-time reconfigurable digital hardware platform.”, In Proceedings of the 3rd International Workshop on Adaptive Self-Tuning Computing Systems (ADAPT'13 - January 21-23, 2013, Berlin, Germany), ACM, New York, NY, USA, 2013, Article 3, http://doi.acm.org/10.1145/2484904.2484907
• L. Bakó, F. Morgan, Sz. Hajdú, S.-T. Brassai, R. Moni, C. Enăchescu, Development and Embedded Implementations of a Hardware-Efficient Optical Flow Detection Method, Acta Universitatis Sapientiae, Electrical and Mechanical Engineering, 6 (2014) 5−19.
• Róbert Moni, László Bakó, Szabolcs Hajdú, Fearghal Morgan and Sándor Tihamér Brassai, “Embedded Real-time Implementation of a Computational Efficient Optical Flow Extraction Method for Intelligent Robot Control Applications”, 24th Irish Conference on Artificial Intelligence and Cognitive Science, University College Dublin, September 20-21 2016. (PDF)
• A. Boyd, F. Callaly, D. Canavan, D. O'loughlin, J. Audiger, Y. Boyer, N. Timlin-Canning, L. Bakó, Sz. Hajdú, F. Morgan, “ICCapt: Online design capture and HDL generation, with PYNQ SoC prototyping in the cloud”, 29th Irish Signals and Systems Conference (ISSC 2018), Belfast, 21st - 22nd June, 2018.
• Fearghal Morgan, Declan O’Loughlin, Jeremy Audiger, Yohan Boyer, Niall Timlin-Canning, Krzysztof Kępa, Ian Gallivan, Frank Callaly, László Bakó, “viciLogic 2.0: Online learning and prototyping of digital systems using PYNQ-Z1/-Z2 SoCs”, 29th International Symposium on Rapid System Prototyping (RSP), October 4-5, 2018, Torino, Italy.
• Fearghal Morgan, Arthur Beretta, Ian Gallivan, Joseph Clancy, Frédéric Rousseau, Roshan George, László Bakó, Frank Callaly, “RISC-V Online Tutor”, in Proceedings of the International Conference on Remote Engineering and Virtual Instrumentation (REV2021), Hong Kong (Virtual Conference), Feb 2021, pp 316-328.