Education and Work Experience
I am a Computer Science graduate student in University of Houston under the supervision of Professor Ioannis Pavlidis. Previously, I have worked as a research assistant in Computational Physiology Lab and before that, I was working as research associate for 2 years in the Institute of Informatics and Telecommunications of NCSR Demokritos. I hold a B.Sc. in Informatics and Telematics from Harokopio University of Athens since July 2014.
My interests lie in the intersection of network science and machine learning. More specifically, I research machine learning methods for temporal networks and spreading processes. I am also keen on exploring unsupervised learning, forecasting, and multi-task learning techniques. In terms of applications and modalities, I have worked with a variety of data, ranging from essays (natural language), coauthorship and brain networks (graphs) to wearable sensors and EEG signals (time series). Finally, I am a Brain Computer Interface enthusiast and am eager to run tutorials or experiments and get my hands dirty with BCI data, whenever I have the chance. I tend to use R for most of my analysis and modeling, but I also employ Python and MATLAB depending on the case. For programming tasks, I use mostly Java and occasionally C++.
In my personal life, I play basketball since high school, where I played competitively. I also swim and play acoustic guitar. I enjoy reading philosophy, physics and popular science and listening to progressive/ punk rock, golden age hip hop and of course Greek folk!
August 2016 - May 2018
Masters in Computer ScienceUniversity of Houston
Advisor: Dr. Ioannis Pavlidis
September 2010 - July 2014
Bachelor in Informatics and TelematicsHarokopio University of Athens
Teaching AssistantUniversity of Houston
Statistical Methods in Research
May 2017--August 2017
Research InternNCSR Demokritos, Software Knowledge and Engineering Lab
Prediction of distraction for drivers based on their physiological and driving signals using Hidden Markov Models.
Used: R, Python
August 2016 - May 2017
Research AssistantUniversity of Houston, Computational Physiology Lab
Curated, combined, synchronized and preprocessed data from a driving simulation experiment and an on road driving experiment. The data came from 5 different sensors and consisted of multiple formats.
Used: R, Python
February - March 2016
Research InternUniversity of Houston, Computational Physiology Lab
Quality control of experimental data coming from wearable signals with data visualization
techniques and statistical hypothesis tests.
September 2014 - July 2016
Research AssociateNCSR Demokritos, Software Knowledge and Engineering Lab
Brain Computer Interfaces
Designed and run experiments and tutorials for graduate and undergraduate students, in Demokritos Summer School 2015 & 2016.
Presented an interactive program to familiarize school children age 9 -15 with Brain Computer Interfaces. Overall, 121 schools attended in the span of 7 months, with over 2500 children taking part in it.
Presented ‘MindPong’, a pong game based on Emotiv Epoc+ brain computer interface implemented by our team, in Athens Science Festival 2016.
User Modeling & Natural Language Processing
Implemented computational services as part of a profiling server that retrieves essays and derives creativity profiles for its users based on computational creativity metrics and a matrix factorization technique. It supports three languages.
Used: Java, Wordnet, Weka, MATLAB, Web Services, MySQL [ code ]
Implemented a set of web services that use natural language processing, unsupervised machine learning and semantic engineering to model the creativity in essays written by children. It supports three languages and facilitates android games that enhance creativity of children.
Used: Java, Web Services, MySQL, Web Crawling, Facebook & Twitter API [ code ]
June 2013 - September 2013
Software Engineering InternNCSR Demokritos
Web Crawling and Database Management for Bibliographic Data.
Used: Delphi, Java , MySQL
G. Panagopoulos, G. Tsatsaronis, and I. Varlamis
Journal of Informetrics (2017): 198-222. Impact Factor: 2.920
Short Description: Identify young scientists with high potential, using social network analysis and unsupervised machine learning. [code]
IEEE BioInformatics and BioEngineering (BIBE), 2017
Short Description: Apply and compare conventional and multi-task machine learning algorithms used in Brain Computer Interface literature in two open datasets of mental monitoring experiments which utilized Neurosky EEG device. [pdf] [code] [presentation]
P. Karampiperis, A. Koukourikos G. Panagopoulos
Knowledge, Information and Creativity Support Systems (KICSS), 2014
A Koukourikos, P Karampiperis, G. Panagopoulos
Cognition and Exploratory Learning in Digital Age (CELDA), 2014
G. Panagopoulos, C. Palmer
Workshop on Assistive Technologies for Decision making in Healthcare, PETRA 2017
G. Panagopoulos, P. Karampiperis, A. Koukourikos, S. Konstantinidis
Workshop on Deep Content Analytics Techniques for Personalized and Intelligent Services, UMAP 2015
- Machine Learning from Andrew NG
- Machine Learning from Nando DeFreitas
- Brain Computer Interfaces from Christian Kothe
- Machine learning (more theoritical) from Mathematical Monk
- Neural Networks, from Huggo Larochelle
- Neural Networks from Geoffrey Hinton himself!
- Data Science (computer science-oriented)from University of Washington
- Data Science (statistics-oriented)from Johns Hopkins University
- Computational Neuroscience from University of Washington
- Kevin P Murphy, Machine Learning: a Probabilistic Perspective. MIT press
- David Barber, Bayesian Reasoning and Machine Learning. Cambridge University Press
- Simon Haykin, Neural Networks, A Comprehensive Foundation. Pearson
- Roger Penrose, The Emperor's New Mind. Oxford University Press
- Martin Davis, Engines of Logic: Mathematicians and the Origin of the Computer. Norton
- Doxiadis Apostolos and Christos Papadimitriou, LOGICOMIX: an epic search for truth. Bloomsbury Publishing
- Marvin Minski, The Society of Mind. Simon & Schuster