Pheiron

Designing genomic evidence systems that support clinical translation and drug discovery. My work spans integration of the largest human genetic cohorts, development of scalable analytical pipelines, and platform design — combining AI and statistical genetics to extract causal insight from population-scale multi-omic data.

Helmholtz Institute of Computational Biology

Joined the Computational Neurobiology Group at Helmholtz Computational Health Center to integrate large-scale omics data into the Alzheimer’s Disease Atlas using the Neo4j database. I develop unified scoring schemas to harmonize multi-omics and phenotypic data, enabling the prioritization of candidate drugs through advanced network-based and AI-driven methodologies.

Helmholtz Pioneer Campus

As a graduate student at the Munich School of Data Science (MUDS) , I joined the Institute of Translational Genetics to research the genetic basis of mental health disorders. I designed architectures, trained models, and conducted statistical analyses on genetic data to understand human health and disease. Additionally, I co-organized two retreats at MUDS, overseeing speaker invitations and agenda management.

Maximilian University of Munich

I was awarded a fellowship from the Data Science for Social Good Foundation (DSSG), during which I collaborated with Munich's Machine Learning Center (MCML), the statistical department of LMU, and Bavaria's state Ministry of the Interior (BMI). Our collaboration aimed to develop a web application for identifying optimal water extraction points for firefighting purposes. The project involved integrating statistical mapping, machine learning techniques, and interactive maps. Additionally, we implemented routing algorithms, containerized the application using Docker, deployed it on AWS, and presented our findings to Germany's federal parliament.

Technical University of Munich

I developed and configured educational material for TUM's Medicine department's Human Genetics of Complex Traits course (ME 1660-P). In addition, as part of our team, I served as a tutor in lectures and workshops, where we covered a diverse range of topics including UNIX, quality control, association testing, meta-analysis, and polygenic risk scores. These roles, helped me facilitate a comprehensive learning experience for students, which later inspired me to pursue a professional certificate in Teaching in Higher Education from TUM ProLehre Media & Didactics.

Helmholtz Munich

Implemented my master thesis at the Institute of Translational Genomics (ITG), where I developed a quality control pipeline to analyze pre-processed data. The pipeline ensured accuracy during merging, corrected for population structure, imputed missing data, and identified biases. Focused on improving the quality of genome-wide association studies (GWAS) data, I processed peripheral whole blood samples collected from 250 patients across four cohorts undergoing total joint replacement surgery. The project involved merging cohorts from different array versions, necessitating specialized handling of genetic data assumptions.

Technical University of Munich, DE

During my doctoral program in experimental medicine and health sciences, I developed a computational pipeline to analyze mtDNA-nucDNA interactions across 48 tissues, identifying discrepancies related to psychiatric conditions. Leveraging machine learning approaches, we revealed regulatory relationships between mitochondria and the nucleus, pinpointing causal genomic variations, particularly in the central nervous system tissues. This research sheds light on tissue-specific mito-nuclear interactions, crucial for understanding health and disease.

Thessaly University, GR

Joined the department of computer science and biomedical informatics, where I took focused courses on applied machine learning, ontology engineering, biosensors and digital imaging. My master's thesis centered around identifying biased individuals and SNPs, statistical imputation and concatenating cohorts from different Illumina genotyping arrays.

Piraeus University, GR

During my 4-year degree in statistics and actuarial mathematics, I gained a solid educational background in probability theory, linear algebra, bayesian statistics, biostatistics, risk management and stochastic processes. In my bachelor thesis, I explored the application of fitting probability distributions to empirical data, where I analyzed various techniques to optimize model selection and enhance the accuracy of predictive systems.