Mr. Alexandros Kouris received his M.Eng degree in Computer Engineering and Informatics from University of Patras in Greece. He is currently a Ph.D. Candidate with the Department of Electrical and Electronic Engineering at Imperial College London, under the supervision of Dr. Christos-Savvas Bouganis in the Intelligent Digital Systems Lab (iDSL).
His current research focuses on high performance (hardware & software) Machine Learning systems, with particular interest on applications related to intelligent mobile robots and Unmanned Aerial Vehicles. From a systems perspective, he is interested on custom hardware implementations on FPGAs, and efficient mappings of algorithms to embedded GPUs.
Alexandros is funded by EPSRC, within "High Performance Embedded and Distributed Systems (HiPEDS)" CDT programme.
Venieris SI, Kouris A, Bouganis C-S, 2018, Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions., Acm Comput. Surv., Vol:51, ISSN:0360-0300, Pages:56:1-56:1
Kouris A, Dimeas F, Aspragathos N, 2018, A Frequency Domain Approach for Contact Type Distinction in Human–Robot Collaboration, Ieee Robotics and Automation Letters, Vol:3, Pages:720-727
Kouris A, Bouganis C, 2019, Learning to fly by myself: a self-supervised CNN-based approach for autonomous navigation, Intelligent Robots and Systems (IROS 2018), 2018 IEEE/RSJ International Conference on, IEEE
Kouris A, Venieris SI, Bouganis C-S, 2018, CascadeC(NN): pushing the performance limits of quantisation in convolutional neural networks, 28th International Conference on Field Programmable Logic and Applications (FPL), IEEE, Pages:155-162, ISSN:1946-1488
et al., 2018, Approximate FPGA-based LSTMs under computation time constraints, ARC 2018: 14th International Symposium on Applied Reconfigurable Computing, Springer, Pages:3-15, ISSN:0302-9743