(Phd Candidate)

Thesis title: Data reduction for complex training data

Supervisor: Ougiaroglou Stefanos

Advisory Committee Members:

Dimitris A. Dervos , Professor, IHU
Geogios Evangelidis, Professor, University of Macedonia

Abstract:

The goal of the dissertation is the development of techniques for reducing the complex training data for instance-based classification. By the term “complex data”, we refer to data with multiple labels, data streams, data in non-Euclidean spaces, distributed data sets, etc. There are many data reduction techniques available in the literature for classification problems. These techniques either select prototypes (representative instances) (Prototype Selection) or generate prototypes by summarizing similar instances (Prototype Generation). The majority of these techniques address classification problems with relatively simple data, i.e., numerical data organized in rows and columns. In contrast, the research aims to the development of new data reduction techniques for complex data.

Postgraduate program (MSc)

Field Of Study:Web Intelligence

Grade:9,41/10

Dates attended:2018 – 2021

Activities and Societies: The program aims to provide high-level education and produce research in Web Intelligence preparing young scientists who are able to professionally contribute to this innovative scientific area. Web Intelligence combines advanced web and Internet technologies with artificial intelligent systems.

1st Semester Courses

M101 Research Methods -9.5
Μ102 Software Engineering for Web Applications -8.5
Μ103 Internet Security -9.3
Μ104 Mobile and Ubiquitous Computing Systems -10
Μ105 Social Networking -7.3

2nd Semester Courses

Μ201 Data Warehousing and Data Mining -9.6
Μ202 Artificial Intelligence Techniques – Agents -9.3
Μ203 Machine Learning -9.2
Μ204 Web Information Retrieval -9.3
Μ205 Semantic Web -9.2

3nd Semester Courses
Msc Thesis -Data reduction techniques for Multilabel Datasets -10

Bachelor’s degree

Field Of Study: Computer Science

Grade: 8.24/10

Dates attended: 2008 – 2015

Activities and Societies: Bachelor’s thesis in “Selection and combination of classifiers for boosting AI(Artificial Intelligence) algorithmic performance: A case study in medical datasets”. Evaluated by: Anagnostopoulos Christos-Nikolaos ( Associate Professor Cultural Technology & Communication Dpt., University of the Aegean ) Plagianakos Basilios (Associate Professor Department of Computer applications Biomedicine, University Thessaly) Kotsiantis Sotirios (Lecturer Department of Mathematics, University Patras).

Courses:
• Introduction to computer science
• Programming techniques
• Data structures
• Programming languages (c,c++)
• Software engineering I
• Operating systems I
• Databases
• Linear algebra
• Single variable calculus
• Elements of probability theory
• Discrete mathematics
• Graph theory
• Mathematical logic
• Digital design I, II
• Computer architecture I
• Microprocessors
• Information theory and coding
• Digital communications
• Computer networks I
• Compilers
• Software engineering II
• Programming languages II – Object oriented programming
• Algorithms and complexity
• Computation Theory
• Automata and formal languages
• Artificial intelligence and expert systems
• Neural networks and applications
• Genetic algorithms and applications
• Telematics
• Internet – Web
• Computers and information society
• Computer Networks II
• New directions in networks and services
• Network design issues
• Java
• Php,HTML,CSS,Javascript
• Operating systems

Bachelor’s degree

Field Of Study: Military Academy

Grade: 88.69/100

Dates attended: 1996 – 1998

MILITARY AND ACADEMIC TRAINING.
Surveillance,identification and Air policing of Flight Region Information (FIR).