About
Hello and welcome to my page! I'm Chrysovalantis Constantinou, an Associate Research Scientist at The Science and Technology in Archaeology and Culture Research Center of The Cyprus Institute. My PI is Associate Professor Efthymia Nikita, and together we're using agent-based modeling to study the migration patterns of ancient populations and machine learning to predict the age and sex of skeletons. I also held the position of a Computational Scientist at the Department of Computation-based Science and Technology Research Center, also at The Cyprus Institute, until 2022.
My research focuses on using agent-based modeling to study the migration patterns of ancient populations that lived around the Mediterranean Sea, with a particular focus on the Roman period. Together with my PI, we also employ machine learning to create models that predict the age and sex of skeletons. More specifically, we're using machine learning techniques on bone datasets to build models that predict the age, sex, and other properties of skeletons based on metric or ordinal measurements. The constructed models are then used in web applications to help make predictions on unknown skeletons. An example of such an application is SexEst, a web application we developed that uses machine learning to predict the sex of skeletal remains based on metric measurements.
I'm also responsible for work package 6 (training and demonstrators) of the NI4OS-Europe project, an infrastructure project funded by the European Commission under the Horizon 2020 grant agreement no. 857645. The project aims to help researchers in South-Eastern Europe onboard their services, such as repositories and web applications, onto the European Open Science cloud. This will make the services readily available for citizens and researchers in Europe. NI4OS-Europe is a critical infrastructure project that aims to accelerate the uptake of open science in the region. My role in work package 6 involves developing training material, designing and implementing use-cases, helping researchers effectively onboard their services onto the cloud, and organizing workshops that cover topics such as data management, open science principles, and FAIR data principles.
Additionally, I'm a code contributor to clowder, an open-source data curation platform designed to help researchers manage and share their data. The platform offers a wide range of tools and features, including 3D model previewers, which are essential for researchers working with 3D models. My main contribution to the project is in creating 3D model previewers, which allow researchers to easily visualize their models.
Finally, I am also interested in theoretical physics which was the subject of my doctorate studies and my first post-doctoral appointment, under Professor Mark Caprio at the University of Notre Dame, and Professor Francesco Iachello at Yale University respectively. Specifically, I am interested in using high-performance computing to study the structure of nuclei such as 6He, 7Li, and 7Be, which are important in stellar burning processes but also in low-energy nuclear reactions. Due to my recent exposure to machine learning, I am also interested in using machine learning in nuclear physics.
In summary, my research interests include the application of theoretical and computational techniques to solve problems related to nuclear physics and physics in general, as well as the use of machine learning techniques on diverse datasets. In addition, I am fascinated by the use of 3D models and their applications in various contexts, including websites and games. You can see an example of this in the Three.js car physics demo web app. Finally, I'm also fascinated by the use of agent-based modeling to study the migration patterns of ancient populations.
Thank you for visiting my page, and please feel free to reach out if you have any questions or if you're interested in collaborating on any of my ongoing research projects.