The Team.

The Data Mining and Analytics research group was set up in 2016 by As. Prof. Christos Tjortjis at the School of Science and Technology, International Hellenic University. Currently, it comprises 15 members, including one post-doctoral researcher. 5 PhD students and 9 MSc students.

When a Team is Above All Nothing is Impossible!

Data Science for Law

At present he works as Senior IT Solution Architect in the company he owns, as well as CEO/Co-Founder. He is carrying out his PhD studies in Data Science and is member of Data Mining and Analytics Research Group by investigating and exploring the field of Law. He has about 20 years of experience on development at high-risk projects concerning Telecoms, Banking, and Commercial sectors. He is certified in GDPR and as a Data Scientist he involved in many research cases. He is always ready to act in the most complicated projects. Education: PhD candidate in Data Science for Law at the International Hellenic University (2019-Now), MSC in Data Communication Systems at Brunel University (London 2008), BSc in Computer Science a Brunel University (London 2006). His professional experience has to do with complicated Projects in the financial sector which gives him the advantage of knowledge and skills about security in IT systems. All these years he had the ability to develop his talent and can handle a big number of IT projects. Public Organisations, Eurobank, Alpha Bank, Piraeus Bank, Cosmote, Vodafone, ICAP are some of the companies he collaborated with. He held various positions like Solution Architect, Business Developer Manager, Team Leader, Project Manager and Quality Evaluator of deliverable products in terms of security, speed, and coding. In his research, he is trying to improve and bind the Data Science with the Law Science to deliver results of how both Sciences are possible to detect violation of legislation by using technology.

PhD candidate in Data Science for Business Applications at the International Hellenic University, School of Science and Technology. He holds an MSc in Data Science from International Hellenic University and a BSc in Accounting and Finance from the University of Macedonia. His research interests are primarily in Data Science and its uses in Business, with strong professional skills in SQL, Python, Data Analysis, Machine Learning and Predictive Analytics. George also works for a multinational hospitality group as an E-Commerce Executive conducting data analysis and forecasting to generate data-driven market insights and communicate with partners. In addition, he is involved with the digital performance analysis of web analytics (Google, Meta-Facebook/Instagram, and Microsoft Bing Ads) and the maintenance of digital platforms and websites..

A. Ahmed – Securing IoT Devices in Smart City Environment using Machine Learning
G. Asderis – Sentiment analysis on twitter data
V.-S. Deeksha-Singh – A Hyper-localized Modeling Approach for Recognizing, Supporting and Developing a Smart City as an Antifragile Complex Adaptive System
W.A. Fadilah – Traffic prediction with data mining
E. Kapoteli – Sentiment Analysis Related to COVID-19 Vaccines
M. Karagkiozidou – Sentiment analysis on twitter data
G. Papageorgiou – Sports Analytics algorithms for performance prediction
I. Tourpeslis – Data mining for smart cities
M. Vlachos-Giovanopoulos – Forecasting with predictive social media analytics

O. Nalmpantis – Movie Recommender System
L. Oikonomou – Mining Twitter data to Predict the USA 2016 election winner
I. Papikas – Human Rating System
T.-I. Theodorou – Traffic Prediction Techniques under Abnormal Traffic Conditions
C. Charisiadis – Data Mining on Source Code
D. Kalliantasis – Data mining for evaluating startups and forecasting stock fluctuations
L. Konstantopoulos – An automated tool for evaluating social media influencers
A. Paraskevopoulos – Product recommendation system
F. Touparis – Predicting stocks movement using social media analytics
K. Apostolou – Sports Analytics algorithms for performance prediction
K. Christantonis – Data mining for smart cities
G. Giaglis – Programmatic Automation & Yield Optimization on the Ad Exchange
I. Schoinas – Product Recommendation system
D. Tasios – Mining Traffic Data
V. Tsarapatsanis – Fake news detection
E. Tsiara – Forecasting with predictive social media analytics
D. Beleveslis – Heuristic Approach for Content Based Recommendation System Based on Feature Weighting and LSH
V. Chazan-Pantzalis – Sports Analytics Algorithms for Performance Prediction
I. Nasiara – The Impact of Twitter Sentiment on Ryanair’s Business Performance
V. Tsichli – Predicting Stock Market Movements Using Social Media and Machine Learning)
Y. Al-Dara – Electricity usage recommender system with limited input data
A. Avramidou – Building CO2 emissions prediction using Machine Learning/ Data mining
P. Belogianni – Sentiment analysis applied on a book recommendation system
C. Kaimakamis – Sports Analytics algorithms for NBA Champion Prediction
D. P. Kasseropoulos – Fake news detection in social media
P. Koudoumas – Sports Analytics algorithms for performance prediction
S. Liapis – Traffic Prediction in Smart Cities, Featuring the Impact of COVID-19
B.S.S. Naim – Big Data mining for smart cities
C. Nousi – Stock Market Prediction using Sentiment Analysis
V. Papanikolaou – Data mining for smart cities: Energy prediction for public buildings
O. Trasanidis – Decision making tool for smart cities