Projects
- Automation of nuclear material cladding coating measurement process
- Nanoindent growth measurements + web app
- Library - segmentation-lightning-base
Automation of nuclear material cladding coating measurement process
Nuclear Research Institute • Bachelor's thesis work
This project began as a solution to the time-intensive manual labeling of microscopy images during my work at the Nuclear Research Institute in Řež. I later expanded it into the focus of my bachelor's thesis. The core objective was to semi-automate the institute's coating analysis workflow by integrating a trained U-Net model into their existing process.
A major part of the work involved building a custom dataset from scratch, as no suitable dataset previously existed. The training process, model architecture, and dataset creation are all thoroughly documented in the thesis.
Through this work, I learned how to collect and process data in close collaboration with domain experts, train deep learning models for image segmentation, and integrate them into practical workflows. I gained hands-on experience with Python, OpenCV, PyTorch, Docker, and a range of machine learning tools and libraries.
Nanoindent growth measurements + web app
Measurement process automation • web app
This Python-based project focuses on processing image pairs—typically "before" and "after" shots—to analyze changes in a grid-like structure. It calculates the elongation and width differences of grid elements between the two images, providing insights into material deformation. The final work was integrated into a web-app.
Library - segmentation-lightning-base
Řež Computer Vision
During my work in Řež, I contributed to the library for training segmentation models. I add integration of Optuna for hyperparameter tuning.
Open Source
- RDMO
- Ilastik
RDMO
First open-source contribution • Darmstadt Sprints
My first open-source contribution. I solved this issue at the sprints in Darmstadt
Ilastik
Merged PR • Object Classification workflow
Fixed issue #2421 in ilastik, an interactive machine learning tool for bioimage analysis. The prediction toggle in the Object Classification workflow was getting out of sync, so I replaced it with two buttons in the same style as the Pixel Classification workflow, making the two workflows consistent.
Hackathons
- ETHGlobal Hackathon - Cannes
- ETHGlobal Hackathon - Buenos Aires
- Ethereum Foundation Research Challenge x TUM Blockchain Conference
- AIProHealth Summer School
ETHGlobal Hackathon - Cannes
Blockchain Flare TEE Smart Accounts
TBD
ETHGlobal Hackathon - Buenos Aires
Blockchain Data analysis Ethereum
I helped build WiFi-Radar, a decentralized “public good” platform that makes it easy to find and verify real Wi-Fi hotspots. Our system uses cryptographic verification and real-time testing so that every listed hotspot is accurate and trustworthy, and contributors can add new locations through a simple interactive map.
Ethereum Foundation Research Challenge x TUM Blockchain Conference
Blockchain Data analysis MEV Analysis Ethereum
Explored the characteristics of **sandwich attacks** on the Ethereum blockchain. Gained hands-on experience with blockchain data analysis, understanding MEV concepts, the mempool, gas fees, and transaction ordering.
AIProHealth Summer School
Healthcare AI EU Regulation
Participated in the AIProHealth summer school focused on advancing AI solutions in healthcare. As part of an interdisciplinary team, we developed a prototype of a digital medical device aimed at helping doctors predict early onset preeclampsia in pregnant women, potentially reducing healthcare costs and saving lives. I was responsible for the technical aspects of the machine learning model.
Academic & Other
- Research project – PLM reduction
- Student Scientific Conference
- EMBL Lautenschläger Summer School – Visualising Life
- Racemization of n-Helicenes
Research project – PLM reduction
TBD
TBD
Student Scientific Conference
Scientific Presentation Bachelor Thesis
Presented my bachelor thesis research at the annual Student Scientific Conference alongside top student projects from across the university in my field.
EMBL Lautenschläger Summer School – Visualising Life
Heidelberg, Germany 🇩🇪 • 2026
Focus practical
Worked on a focus practical with Jess Ewald's group, training small models (XGBoost and neural networks) on CellProfiler morphological features from compound-treated cell images to predict cell toxicity.
Racemization of n-Helicenes
Computational chemistry: transition states, IR spectra
I worked on the racemization properties of several helicenes, including pentahelicene, hexahelicene, heptahelicene, and dinaphtho[5]helicene. My research focused on calculating racemization barriers, identifying transition states, and analyzing IR spectra.
Along the way, I gained experience with tools like Gaussian, VMD, Avogadro and QuantumATK for molecular modeling and simulation.