Research areas of interest

Big Code

... AKA mining software repositories (MSR) and software related data, software analytics etc. with the goal of improving the various facets the software lifecycle.


Software Quality

Research on assessing the quality of a software project and quantifying the various (ISO 25010) quality characteristics: Functional Suitability, Performance Efficiency, Maintainability, Usability, Security, Portability, Reliability, Compatibility.


Web Services and APIs

Research on web services and APIs


Machine Learning on Source Code

Applying machine learning and deep learning representations on source code for various problems.


Continuous Implicit Authentication

Research on behavioral biometrics for continuous implicit authentication taking into account keyboard strokes, taps and swipes for Desktop and Mobile applications.



The making of an automated/autonomous data scientist.


Funded Research Projects

European, national and privately funded projects I worked as a researcher

  • eeRIS: electric energy Residential Informational System(National, ΕΠΑνΕΚ, 2018-2021). eeRIS will be able to offer detailed information to an electric energy consumer, correlating his/her consumption to the use of specific household appliances. At the same time, is will create a personal demand profile for the consumer, assisting him/her thus to obtain an optimized personalized tariff from the respective producer. Moreover, eeRIS will also be able to detect contingencies in the power distribution network, and notify accordingly the respective network operator. To that end, eeRIS will be based on the Non-Intrusive Load Monitoring paradigm. Within this context, eeRIS will comprise a single panel meter, and will utilize powerful algorithms to provide the expected results by the respective measurements.
  • VITAL: Versatile Internet of Things in AgricuLture (National, ΕΠΑνΕΚ, 2018-2020). The aim of the project is to create an innovative system that exploits the Internet of Things (IoT) technology in applications requiring low installation, use and maintenance costs while allowing for the interconnection and integration of a large number of different types of devices, covering a range of up to 1 km radius (capable of covering larger areas with increased power consumption)
  • CIA: Continuous Implicit Authentication (Privatelly funded, 2018-2019) is a project that aims to do continuous implicity authentication through gestures in mobile devices and kiosks.
  • SEAF (European, H2020, 2017-2019)
  • Mobile-Age (European, H2020, 2017-2019)
  • S-CASE: Scaffolding Scallable Software Services (European, FP7-ICT, 610717, 2013-2016). The goal of S-CASE is to accelerate the software development lifecycle for cloud services by introducing a new agile prototyping paradigm that automates the process of mapping user requirements to concrete software specifications and generates operational code (RESTful services). S-CASE aspires to support software developers in identifying software requirements and business processes in various formats, including textual (requirements/use case documents), formal (UML diagrams), and visual (images of UML diagrams or storyboards) content. In order to realise this vision, S-CASE employs appropriate multimodal information processing techniques, such as natural language and image processing. S-CASE also aims to provide the appropriate mechanisms for synthesising composite executable workflows of resources (software solutions, services, and devices), both proprietary and open source. For more information check thiswebsite.
  • Cassandra: A multivariate platform for assessing the impact of strategic decisions in electrical power systems (European, FP7-ICT, 2011-2014) aims to build a platform for the realistic modeling of the energy market stakeholders, also involving small-scale consumers
  • eTHMMY (National, ΕΠΕΑΕΚ ΙΙ, 2003-2008) is an integrated educational platform for the deparment of Electrical and Computer Engineering.
  • Agent Academy (European, FP5-IST, IST-2000-31050, 2001-2004) is an integrated environment for embedding intelligence in newly created agents through the use of Data Mining techniques.


Past research


My PhD dissertation! NeuroEvolution of Augmenting Reservoirs, or for short NEAR, is an algorithm that combines Neuroevolution and Learning in order to optimize and train Echo State Networks for solving reinforcement learning and time series forecasting problems.



Our agent for the Trading Agent Competition, Ad Auctions (1st place 2012, 3rd place 2010) and Supply Chain Management (3rd place 2005) games.


Older Research Projects

Older research projects I was able to maintain in a publishable format.