Christos Theodoropoulos

Senior Data Scientist @ EarlyTracks

Hello, world!


Hi, I’m Christos Theodoropoulos—a Senior Data Scientist at EarlyTracks, where I use artificial intelligence and natural language processing to turn electronic health records into meaningful formal insights. I’m passionate about applying machine learning to real-world problems, especially in life sciences and human-centered technologies.

I studied Electrical and Computer Engineering at the National Technical University of Athens (NTUA), where I focused on computer science and graduated with great distinction. My thesis explored how deep learning can be used for human emotion recognition from facial expressions in real-time video conversations, uncovering the nuanced interplay of emotions in dynamic interactions.—think of it as teaching machines to read the room. After that, I worked on eye-tracking and gaze localization in driving scenarios at the I-SENSE Group, before moving to Belgium to pursue an advanced Master's in Artificial Intelligence at KU Leuven. There, I dug into fMRI data and used deep neural networks to clean up brain scans—work that was later published in a signal processing conference (EUSIPCO).

In my last academic journey, starting at 2020, I pursued my PhD in Computer Science at KU Leuven, focusing on natural language processing and knowledge extraction. I spearheaded the creation of an end‑to‑end open‑source knowledge extraction system from the ground up. This endeavor, potentially incorporated the expert-in-the-loop paradigm, seamlessly aligns with the tenets of lifelong learning. Recognizing the challenge of navigating vast volumes of research text daily, my unwavering focus has centered on the realm of biomedical text. Within this domain, I've embarked on a mission with far-reaching implications by tackling the intricate complexities of two formidable yet unresolved diseases: Alzheimer's disease and Rett syndrome.

However, my aspirations don't stop at disease comprehension through seamless knowledge extraction. During my PhD, my research extended to the frontier of personalized medicine, where I harnessed the potential of person-centric knowledge graphs to create a holistic view of patients. A notable accomplishment that adorns my research journey is the creation of a contrastive learning framework, ingeniously integrating both graph and text modalities to instill relation-oriented structure into Language Models like BERT and RoBERTa. This novel approach has empowered me to transcend the constraints of traditional text encoders, ushering in a new era of possibilities. By translating the acquired embedding spaces into tangible solutions, I've ventured into the realms of relation extraction and named entity recognition, solving these intricate tasks using deceptively simple yet effective classifiers like KNN. At the later stage of my PhD, I’ve had the chance to conduct a short research visit in the Idiap Research Institute in Switzerland. I've also attended two OxML summer schools organized by AI for Global Goals in collaboration with CIFAR and the University of Oxford diving deeper into health AI, representation learning, and generative models. Along the way, I’ve served as a reviewer for top journals and conferences like ACL Rolling Review and IEEE TPAMI.

Beyond academia, my expedition led me to the vanguard of innovation as a research scientist intern at IBM Research. Here, I had the privilege of immersing myself in projects that not only stoked the flames of my curiosity but also enriched my repertoire of skills. A significant chapter in this journey involved insights from Electronic Health Records (EHR) to construct person-centric knowledge graphs. This endeavor saw me wield the power of the HSPO ontology and harness the prowess of Graph Neural Networks (GNNs) to tackle the formidable task of predicting intensive care unit readmissions. Embracing the spirit of versatility, my explorations expanded to encompass the fascinating domain of embedding learning for heterogeneous graphs. These explorations are on the brink of yielding results in the shape of upcoming research publications. The team's influence also extends into the realm of open-source collaboration. I've been instrumental in fortifying IBM's commitment to knowledge dissemination, playing a pivotal role in bolstering their open-source initiative, exemplified by the repository. In a testament to my innovation, and inventiveness, I proudly stand as the primary inventor in a patent filing.

As for my roots, I hail from Tripolis, the capital of Arcadia, steeped in history and surrounded by beautiful nature. My formative years were then shaped in Athens, where seven years of studying, working, and immersing myself in the city's energy left an indelible mark. Today, I'm nestled in Brussels, a cosmopolitan hub pulsating at the heart of Europe, characterized by its multicultural essence and lively spirit.

For deeper insights into my journey and potential collaborations, I invite you to explore my CV or reach out to me directly. And if the allure of Greece beckons, I stand ready to offer recommendations. Here's to embracing the journey of knowledge, discovery, and shared experiences!



Education

2020-2025
KU Leuven

PhD in Computer Science

2019-2020
KU Leuven

Advanced MSc in Artificial Intelligence

2012-2018
National Technical University of Athens

BSc & MSc in Electrical and Computer Engineering

Professional Experience

2025-now
EarlyTracks

Senior Data Scientist

2022
IBM Research (ACCELERATED DISCOVERY TEAM)

Research Scientist Intern

2019
I-SENSE Group, ICCS

Researcher, Deep Learning Engineer

2018
Feel Therapeutics

Data Scientist




For more details, please see my full CV (PDF).

News



04/2025
Released the pre-print of our publication "Reduction of Supervision for Biomedical Knowledge Discovery" with Andrei Cătălin Coman, dr. James Henderson, and prof. Marie-Francine Moens.

03/2025
Officially defended my PhD publically.

01/2025
Successfully defended my PhD privately.

01/2025
Accepted an offer to join EarlyTracks as Senior Data Scientist, aiming to improve the quality of Electronic Health Records.

11/2024
Our paper "Enhancing Biomedical Knowledge Discovery for Diseases: An End-To-End Open-Source Framework" with Andrei Cătălin Coman, dr. James Henderson, and prof. Marie-Francine Moens got accepted into the IEEE Access journal.

07/2024
Participated in OxML summer schools on health and bio AI and representation learning and generative AI, organized by AI for Global Goals in collaboration with CIFAR and the University of Oxford.

06/2024
Our follow-up paper "Evaluating the Predictive Features of Person-Centric Knowledge Graph Embeddings: Unfolding Ablation Studies" with Natasha Mulligan and dr. Joao Bettencourt-Silva that unfolds the ablation study based on the framework presented in "Representation Learning for Person or Entity-Centric Knowledge Graphs: An Application in Healthcare" got accepted into MIE '24.

06/2024
Our paper "GADePo: Graph-Assisted Declarative Pooling Transformers for Document-Level Relation Extraction" with with Andrei Cătălin Coman, prof. Marie-Francine Moens and dr. James Henderson got accepted into KnowledgeNLP-ACL '24.

04/2024
Conducted a short research visit at Idiap Research Institute and gave a talk on knowledge discovery.

10/2023
Our paper "Representation Learning for Person or Entity-Centric Knowledge Graphs: An Application in Healthcare" with Natasha Mulligan, prof. Thaddeus Stappenbeck, dr. Joao Bettencourt-Silva got accepted into K-CAP '23.


03/2023
Our paper "An Information Extraction Study: Take In Mind the Tokenization!" with prof. Marie-Francine Moens got accepted into EUSFLAT '23.

11/2022
Gave a talk on Person-Centric Knowledge Graph Extraction from Electronic Health Records to solve downstream tasks in "Show & Tell" session of IBM Research.

10/2022
Submitted my first patent as the primary inventor, working in IBM research.

10/2022
Heavily contributed to IBM's open-source project (HSPO ontology).

01/2022
Accepted an offer to join IBM Research (Human-centric AI team) for a research scientist internship.



09/2021
Our paper "Imposing Relation Structure in Language-Model Embeddings Using Contrastive Learning" with dr. James Henderson, Andrei Cătălin Coman and prof. Marie-Francine Moens got accepted into CoNLL '21.


07/2021
Became member of ContinualAI organization.

04/2021
Our work with dr. Christos Chatzichristos and prof. Sabine Van Huffel on automatic denoising of resting-state fMRI using deep learning got accepted into EUSIPCO '21.

09/2020
Received FWO Ph.D. fellowship.

08/2020
Graduated from KU Leuven, M.Sc. in Artificial Intelligence, with Magna Cum Laude.

07/2019
Received scholarship for postgraduate studies by Eugenides Foundation for the academic year of 2019-2020.

06/2019
Received scholarship for postgraduate studies by Bodossaki Foundation for the academic year of 2019-2020.

10/2018
Graduated from National and Technical University of Athens, M.Eng. in Electrical and Computer Engineering, with great distinction.


Publications




2025


Reduction of Supervision for Biomedical Knowledge Discovery

Christos Theodoropoulos, Andrei Catalin Coman, James Henderson, Marie-Francine Moens


Deep Learning Models for the Extraction of Knowledge from Text

Christos Theodoropoulos, Marie-Francine Moens (Supervisor), Matthew Blaschko (Supervisor)
PhD Dissertation


Learning relations in multi-relational graphs in graph neural networks

Christos Theodoropoulos, Marco Luca Sbodio, Natalia Mulligan, Joao H Bettencourt-Silva
U.S. Patent Office
[PDF]


2024


Enhancing Biomedical Knowledge Discovery for Diseases: An End-To-End Open-Source Framework

Christos Theodoropoulos, Andrei Cătălin Coman, James Henderson, Marie-Francine Moens
IEEE Access


Fast-and-Frugal Text-Graph Transformers are Effective Link Predictors

Andrei Cătălin Coman, Christos Theodoropoulos, James Henderson, Marie-Francine Moens


Evaluating the Predictive Features of Person-Centric Knowledge Graph Embeddings: Unfolding Ablation Studies

Christos Theodoropoulos, Natasha Mulligan, Joao Bettencourt-Silva
MIE 2024, 34th Medical Informatics Europe Conference


GADePo: Graph-Assisted Declarative Pooling Transformers for Document-Level Relation Extraction

Andrei Cătălin Coman, Christos Theodoropoulos, Marie-Francine Moens, James Henderson
ACL 2024, 3rd Workshop on Knowledge Augmented Methods for NLP


2023

Representation Learning for Person or Entity-Centric Knowledge Graphs: An Application in Healthcare

Christos Theodoropoulos, Natasha Mulligan, Thaddeus Stappenbeck, Joao Bettencourt-Silva
K-CAP 2023, 12th Knowledge Capture Conference

An Information Extraction Study: Take In Mind the Tokenization!

Christos Theodoropoulos, Marie-Francine Moens
EUSFLAT 2023, 13th Conference of the European Society for Fuzzy Logic and Technology

2021


Imposing Relation Structure in Language-Model Embeddings Using Contrastive Learning

Christos Theodoropoulos, James Henderson, Andrei Cătălin Coman, Marie-Francine Moens
CoNLL 2021, SIGNLL Conference on Computational Natural Language Learning

Automatic artifact removal of resting-state fMRI with Deep Neural Networks

Christos Theodoropoulos, Christos Chatzichristos, Sabine Van Huffel
EUSIPCO 2021, 29th European Signal Processing Conference

Contact


Χρήστος Θεοδωρόπουλος
E-mail: <x>@earlytracks.com, where x=christos.theodoropoulos
Office: Av. des Nerviens 123, 1040 Brussels, Belgium(map).
E-mail: <y>@outlook.com, where y=christostheodoropoulos


Extra: My first name (Christos) is pronounced as: