Christos Kyrkou, PhD

EDUCATION

PhD in Computer Engineering (September 2010-June 2014)

PhD Thesis: Real-Time Hardware Acceleration of Object Detection for Intelligent Embedded Vision Systems
Electrical and Computer Engineering Department, University of Cyprus - PDF
Notable Technical Reports and Projects
- Image Processing on FPGAs: A Survey, ECE 664 - Advance FPGA Design, University of Cyprus
- Face Detection using Hierarchical SVM, ECE 795 - Pattern Recognition, University of Cyprus

M.Sc. in Computer Engineering (September 2008-January 2011)

M.Sc. Thesis: Embedded Hardware Architectures for Object Detection
Electrical and Computer Engineering Department, University of Cyprus
Received Full Scholarship by the ECE Department, University of Cyprus
Notable Technical Reports and Projects
- Survey on GPUs and Stream Image Processing, ECE 656 - Advanced Computer Architecture, University of Cyprus
- Event-driven scheduling for multi-core processors, ECE 658 - Performance Evaluation, University of Cyprus

B.Sc. in Computer Engineering (September 2004-June 2008)

B.Sc. Thesis: Neural-Network-based Face Detector Implementation on a Virtex II Pro FPGA Platform
Electrical and Computer Engineering Department, University of Cyprus
Graduated Top of the Class
Notable Technical Reports and Projects
- Implementation of a real-rime image rotation system on an FPGA platform, ECE 417, - Digital Design with FPGAs, University of Cyprus
- VHDL Implementation of the MIPS32 RISC Processor, ECE 312 - Computer Architecture, University of Cyprus

PROFESSIONAL DEVELOPMENT

Fundamentals of AI at the Edge (January 2020 - March 2020)

Online Course – UDACITY (Curriculum developed in collaboration with Intel)

Template Foundation course on optimizing deep learning for edge applications using the Intel OpenVINO toolkit.
Developed high-performance computer vision and deep learning inference applications using the Intel Distribution of OpenVINO toolkit to deploy computer vision capabilities inside a range of edge applications.
Received scholarship from Intel

Fundamentals of Deep Learning for Computer Vision (April2019)

Online Course – NVIDIA Deep Learning Institute

Implemented common deep learning workflows, such as image classification and object detection using the DIGITS framework.
Experimented with data, training parameters, network structure, and other strategies to increase performance and capability
Deployed neural networks to start solving real-world problems

Self-Driving Car Engineer Nanodegree (13 December 2016 - 17 November 2017)

Online Course – UDACITY (Curriculum developed by Sebastian Thrun | Partners: Mercedes Benz, NVIDIA, Uber)

Term 1 (Completed): Computer Vision, Deep Learning, and Supervised Classification and Machine Learning

Projects: Lane Detection, Traffic Sign Classification, Driving Behaviour Cloning, Vehicle Detection and Tracking

Term 2 (Completed): Sensor Fusion, Localization, and Control

Projects: Sensor Fusion and tracking with Extended Kalman FIlter and Unscented Kalman Filter, Particle Filters, Vehicle control with PID and Model Predictive Controllers

Term 3 (Completed): Deep Learning and Path Planning

Projects: Path Planning, Semantic Segmentation using Deep Learning, and Capstone Project (System Integration - Run Code on real self-driving car)

Took part in the tutorial session at CVPR2019 for “OpenCV 4.x and more new tools for Computer Vision R&D” organized by Intel. LIVE DEMO💻
- How to run deep networks in browser with OpenCV 4.0; Open Model Zoo. New models and performance. Trainable models.
- CNN compression. Int8 models and performance. Int1 models and performance.
- OpenCV Computer Vision Annotation Tool
Fundamentals of Deep Learning for Computer Vision – NVIDIA Deep Learning Institute, April 2019
- - Implemented common deep learning workflows, such as image classification and object detection using the DIGITS framework.
  - Experimented with data, training parameters, network structure, and other strategies to increase performance and capability
  - Deployed neural networks to start solving real-world problems
Participated in the Industrial Tutorial “Computer Vision for Automated Driving in MATLAB” at DATE2018, March 2018
Attended Intel Hardware Accelerator Research Program (HARP) February workshop, 2017.
Attended the DAC Young Faculty Workshop 2016 (Austin, Texas, USA).
Attended a full-day seminar on "Introduction to Databases and MySQL" organized by the IEEE Cyprus Student Branch.
Participated in seminar series "Scheme for improving the competitiveness of SMEs with 1-4 employees", 21/05/2014-04/08/2014, organized by Human Resource Development Authority, Cyprus Ministry of Energy, Commerce, Industry and Tourism, 2014.
Attended training day for fire-fighting and prevention, 2014.

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