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.