I'm a Computer Science master's student at FAU interested in AI for science and engineering.
I enjoy working on the software side of technical problems: building ML pipelines, simulation workflows, developer tools, and systems that make complex research workflows easier to automate and experiment with.
- AI for Science & Engineering — using ML to accelerate or automate computationally expensive technical workflows.
- Scientific ML — surrogate models, foundation models, optimization, and ML-assisted simulation.
- Software for research — turning research ideas into reproducible, modular, and usable tools.
- HPC & distributed computing — running large simulation and ML workloads efficiently.
- AI agents & developer tools — exploring how LLMs can interact with specialized software and technical workflows.
🐋 ORCA — Open RF Integrated Circuit Automation
An open-source framework for surrogate model creation for radio-frequency integrated circuit (RFIC) components. I work primarily on the software and ML side: automating geometry generation, electromagnetic simulation, dataset generation, surrogate-model training, and distributed execution.
🐍 COBRA — A Circuit-Level Open-Source Based RFIC AI-Assisted Optimizer
A tool built around the ORCA-generated ML surrogate models and circuit simulation to optimize circuit designs towards user-defined goals. It also explores using LLMs as an interface for engineering optimization workflows.
👷♂️ BOB — Bounding-box Oracle for Biomedicine
A tool for automatically generating box prompts for interactive medical image segmentation foundation models, together with a napari 3D-viewer plugin for reviewing the generated prompts.
⚕️ med-seg-fm
A framework for evaluating medical image segmentation foundation models across different datasets and imaging modalities, with an emphasis on making comparisons reproducible and easy to extend.
