Joana Tirana
PhD student in Computer Science
Dublin, Ireland
joana.tirana@ucdconnect.ie
GitHub ,Google Scholar, Linkedin
Small Bio
Full CV: CV-pdf
Programming Skills
- Languages: Python, C, C++, Java, SQL, Matlab
- Cloud Tools: Docker, Kubernetes, AWS CLI, Ansible
- Parallel Programming: CUDA, OpenMP
- Operating systems: Linux, MacOS, Android
- Optimization: Gurobi, cvxpy
- Other: GIT, Buildbot
NEWS
- 12.July.2025: Site is up! I am actively searching for a new role!
Education
Phd in Computer Science
University College Dublin, Ireland
January 2022 - Current (expected: December 2025)
Topic: Decentralized and distributed learning Machine Learning (ML) for resource-constrained devices, such are mobile and IoT devices. Throughout my PhD, I have studied the challenges of Federated and Split Learning, built frameworks for supporting such operations, developed optimization algorithms that improve the performance of the system, and training. In general, my interests are in building systems for distributed ML and optimizing ML training under challenges.
Supervisor: Ass. Profesor Dimitris Chatzopoulos
Integrated Master in Electrical and Computer Engineering
University of Thessaly, Greece
September 2016 - September 2021
Bachelor's and Master's in Electrical and Computer Engineering. Main focus on Computer Engineering with core knowledge of Software and Hardware.
Indicative subjects: Programming I&II, Concurrent Programming, Computer Organization and Design, Distributed Systems, Networking, High Performance Computing Systems, Database Systems, Machine Learning, NeuroFuzzy Programming.
Total Mark: 8.9/10, Graduated with Honors
Thesis Tittle: Support for Parallel Drone-based Task Execution at Multiple Edge Points thesis link (english version)
Experience
Research Intern at Telefónica Innovación Diginal, Barcelona Spain
July - December 2024
This work is part of my PhD journey. Studying the effect of Catastrophic Forgetting in Parallel Split Learning for cases of high data heterogeneity. By the end of the internship we managed to write a paper (currently under review -- more details TBA)
supervisors: Dimitra Tsigkari, David Solans Noguero, Nicolas Kourtellis
PhD Visit, TU Delft , The Netherlands
April - August 2024
This research visit is part of the PhD. We studied Parallel Split Learning from a more theoretical perspective. In detail, inspired by the parallel machine problem, we built a new model that fully describes the system. Furthermore, we managed to formalize two optimization problems that minimize the training delay while considering key system parameters. The publications [C2] and [J1] are the outcome of this visit.
supervisors: George Iosifidis, Dimitra Tsigkari, Dimitris Chatzopoulos
Software Engineer Intern, 3DEXCITE -- Dassault Systems, Munich Germany
June 2010 - Mar 2012
Topic of the project: Deployment of DStellar in Outscale and Analyze Performance.
Automatic deployment in cloud using AWS and Ansible. Also, I built and gathered results using Buildbot. Learnt working in an Agile scrum team.
List of publications
Conferences/Workshops
[C1]: Tirana, J., Pappas, C., Chatzopoulos, D., Lalis, S., & Vavalis, M. (2022, July). The role of compute nodes in privacy-aware decentralized ai. In Proceedings of the 6th International Workshop on Embedded and Mobile Deep Learning (pp. 19-24).
[C2]: Tirana, J., Tsigkari, D., Iosifidis, G., & Chatzopoulos, D. (2024, May). Workflow optimization for parallel split learning. In IEEE INFOCOM 2024-IEEE Conference on Computer Communications (pp. 1331-1340). IEEE.
[C3]: Tirana, J. Lalis, S., & Chatzopoulos, D. (2025, March). Estimating the Training Time in Single-and Multi-Hop Split Federated Learning. In Proceedings of the 8th International Workshop on Edge Systems, Analytics and Networking (pp. 37-42).
Journals
[J1]: Tirana, J., Tsigkari, D., Iosifidis, G., & Chatzopoulos, D. (2025). Minimization of the Training Makespan in Hybrid Federated Split Learning. IEEE Transactions on Mobile Computing, (01), 1-18.
Pre-prints
[P1]: Tirana, J., Lalis, S., & Chatzopoulos, D. (2024). MP-SL: Multihop Parallel Split Learning. arXiv e-prints, arXiv-2402.
Book Chapters
[B1]: Tirana, J., & Chatzopoulos, D. (2025). Split learning and synergetic inference: When IoT collaborates with the cloud-edge continuum. In Advances in the Internet of Things (pp. 203-227). CRC Press.