Christos Theodoropoulos

Hi, I'm Christos Theodoropoulos — currently employed as AI Solutions Architect at Qity, working alongside the developers and system architects to lay the foundations for AI-driven solutions, helping to strengthen and extend the capabilities of Qity platforms on the intersection of Engineering, Regulatory, Quality, and AI. Previously, I worked as Senior Data Scientist at EarlyTracks, where I used artificial intelligence and natural language processing to turn electronic health records into meaningful formal insights. I'm passionate about applying machine learning and artificial intelligence tools 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!