About Me

  • Name:Georgios Tzannetos
  • Email:geo.tzannetos@gmail.com

Hi There!

My name is Georgios (you can call me George) and I am a PhD student in the Machine Teaching Group at the Max Planck Institute of Software Systems working under the supervision of Adish Singla.

My current research interests are in the area of reinforcement learning, with emphasis on curriculum learning, and curriculum design for training reinforcement learning agents more efficiently.

My Timeline

  • Education

  • PhD

    Computer Science

    Max Planck Institute of Software Systems
    Sept 2021 - Current
  • Master of Science, M.Sc

    Computational Science and Engineering

    Technical University of Munich, TUM
    Oct 2016 - Dec 2018

    Modules in Computer Science, Applied Mathematics and Scientific Computing
    Application Areas: Data Driven Computing, Big Data, Machine Learning, Deep Learning, Computational Physics
    GPA : 1.6, in German System

  • Diploma of Engineering

    Mechanical Engineering, equivalent to M.Sc

    National Technical University of Athens, NTUA
    Oct 2010 - Feb 2016

    GPA : 8.50
    Major: Mechanical Design, Control Systems & Robotics GPA: 9.05

  • Work Experience

  • Data Scientist

    Fujitsu, Sep 2019 - Sep 2021

    Part of the Delivery team of Fujitsu Connected Services, focusing on solutions in the automotive and manufacturing industry. Main tasks include the use, maintainance and further development of Fujitsu's AutoML system, especially for supporting and automating the visual inspection pipeline. Moreover, custom deep learning and machine learning solutions are developed for extending the AutoML platform. Working on the sandbox development of Fujitsu's Digital Manufacturing Platform. This is a solution towards smart factory, i.e connecting different levels and parts to improve the production performance. Among other tasks, I automated the collection, parsing and communication of factory data from a simulator to a database through MQTT protocol for performing analytics and visualization.

  • Data Scientist / Computer Vision, Intern

    AGT International R&D, Feb 2019 - Jul 2019

    Responsible for the virtual advertising project. Combination of classical computer vision methods, like image registration, developed in OpenCV, with deep learning methods, mainly Mask-RCNN, in Caffe2, to segment and produce highly accurate advertisement masks.

  • Machine Learning for Autonomous Driving

    AUDI Electronics Venture, May 2018 - Oct 2018

    Master Thesis, Automating the generation of a synthetic dataset, by superimposing objects on real images with the use of a computer graphics software, Blender. Image registration, depth completion and 3D road segmentation were implemented in Python. The created dataset was used to train a deep learning model to perform lane detection and performance was compared with real datasets, written in Keras.

  • Data Scientist, Working Student

    Trillr, Nov 2017 - Jan 2018

    Responsible for setting up and maintaining company’s database, deployed in Docker. Migrating existing MySQL database to MongoDB. Responsible for collecting data from various sources and APIs and storing them. Daily, weekly and long term data analysis, regarding different relevant KPIs was performed with Python, Pandas and Tableau to increase productivity and suggest improvements.

  • Undergraduate Research Assistant

    Control Systems Lab @ National Technical University of Athens, Jan 2015 - Feb 2016

    Diploma Thesis, Applications with Robotics software and hardware. For this purpose ROS (Robot Operating System) was used, which is supported by Linux. Theoretical analysis and real-time implementation of game theory to the robotic platforms, Asctec Firefly and Pioneer Mobile Robot. Applied sophisticated controls, such as model predictive control, written in C++.

Past Projects

Virtual advertisement Project

Live segmentation of advertisement during football game

Click to read more

Lane Detection using Synthetic Dataset

Augmented Reality Data Generation for Deep Learning Based Lane Detection

Click to read more

Robotics & Game Theory Project

A non cooperative game between an unmanned aerial vehicle and an unmanned ground vehicle.

Click to read more


Here there is a list of my published papers so far.

A competitive differential game between an unmanned aerial and a ground vehicle using model predictive control

G. Tzannetos, P. Marantos, and K. Kyriakopoulos, in IEEE, on the 24th Mediterranean Conference on Control and Automation, vol. 2016.

June 21-24th 2016

Contact me!

If you find my profile interested and you have anything you want to discuss or ask me, you are welcome to do it by sending me an e-mail or via the contact form below.

My E-Mail