Maria Tsouchnika

Maria Tsouchnika (Area: Computational Physics), Physics Department, A.U.Th.

Email: mtsou@auth.gr

Maria Tsouchnika currently serves as a postdoctoral researcher at the Physics Department of Aristotle University of Thessaloniki (A.U.Th.). She embarked on her academic journey at A.U.Th., earning her degree in Physics in 2003 with a focus on Computational Physics. Her deep engagement with Complex Systems, Chaos Theory, and Numerical Analysis during her undergraduate studies spurred her to pursue a Master’s degree in Computational Physics, also from A.U.Th., which she completed in 2007. Her Master’s Thesis on “Neural networks and applications” explored the construction, training, and application of neural networks for time-series prediction.

In 2013, she shifted her focus to Network Science and Social Network Analysis (SNA), concentrating on the study of complex systems through applying statistical physics and network theory methods, to network representations built from real-world data. Her research primarily investigated the structure, temporal evolution and dynamics of systems related to research, innovation, and economic activities. She earned her PhD in 2020 from A.U.Th., with a dissertation entitled “Uncovering structural, evolutionary, and spreading phenomena characteristics of complex networks and systems, using statistical mechanics methods on real-word data.” Her doctoral research was supported by the FP7 European program MULTIPLEX from 2013 to 2016.

Maria also has extensive professional experience as a software engineer, having spent five years (2016-2021) with Intracom-Telecom. Passionate about education, she has consistently engaged in teaching, both as a private tutor and as a teaching assistant at undergraduate and graduate levels. Currently, she is involved in the Erasmus+ project LEAP: unLocking carEer potentiAl with complex systems, data analytics, and machine learning.

As a data enthusiast, she excels in Java, C++, Python, and R, among other programming languages. She is also highly proficient in both spoken and written English.

Role in GRADIENCE: Maria Tsouchnika is engaged in the Part-of-Speech (PoS) annotation of HelexKids and the extraction of noun stress frequences, contributes to the development of the Wordlist tool tailored for educators, and actively contributes to the development and testing of both the Machine Learning (ML) and Gradient Harmonic Grammar (GHG) algorithms.She also participates in the publication process of the anticipated research outcomes.