PhD in Biophysics · Image Analysis · Quantitative Microscopy · Scientific Software · AI-Assisted Workflows
I build tools that turn complex scientific images into reliable, measurable data.
My background is in biophysics and quantitative imaging, where I worked on extracting mechanical and morphological information from microscopy experiments. Over time, I became increasingly interested in the engineering side of science: building robust pipelines, automating analysis workflows, validating results, and turning research methods into reusable software.
Today, I work mainly at the intersection of:
- 🤖 Applied AI & automation
- 🔬 Scientific imaging
- 👁️ Computer vision
- 📊 Quantitative analysis
- 🛠 Reproducible software engineering
| Category | Badges |
|---|---|
| Languages | |
| Image Analysis & ML | |
| Engineering & Tools |
📦 imgclean
Image dataset quality-control toolkit for computer vision workflows.
Detects duplicates, blur, corruption, exposure issues, and train/validation leakage. Exports HTML, JSON, and CSV reports.
PythonOpenCVData Quality ControlReports
Scientific imaging package for extracting mechanical information from microscopy images.
Includes topology extraction, Bayesian force inference, curvature analysis, and stress summaries.
PythonScientific-ComputingMicroscopyBayesian
Android computational photography prototype combining depth estimation with bokeh rendering.
Combines monocular depth estimation with GPU-based bokeh rendering.
AndroidKotlinGPU ShadersComputational Photography
Configurable PyTorch U-Net pipeline for biological image segmentation.
Streamlined training, inference, and validation pipelines for microscopy and biological image datasets.
PyTorchU-NetImage SegmentationDeep Learning
"Good scientific software should not only work once. It should be understandable, testable, reusable, and useful to someone else."
- Current Focus: Scientific imaging and quantitative microscopy, computer vision for biological/medical images, dataset quality control prior to ML training, inverse problems, and physics-informed image analysis.



