Palmaf
2025-present
IsHas
IsHas is developed specifically for fire safety inspectors. It replaces time-consuming manual notes with a streamlined digital workflow that allows instant, one-click report generation. By centralizing records and implementing role-based access, the platform boosts operational efficiency and audit readiness.
- Flutter
- Python
- Django
Automatic EEG labeling
This application streamlines neurological review by automatically detecting and labeling potential epileptic activity in long-term EEG recordings. By filtering out non-event data, the tool enables specialists to focus on high-value clinical analysis. See demo here.
- Python
- PyTorch
Tabulara
Tabulara.ai is a natural-language data interface that allows non-technical users to extract meaningful insights from raw tabular exports using simple, human-readable commands. It transforms static exports into an accessible resource for data-informed decisions.
- Python
- Django
- HTMX
- LLM
Personal
Personal server
I maintain a self-hosted Linux server environment using Docker to deploy and isolate web services behind an Nginx reverse proxy. The project focuses on security best practices, including automated SSL management, firewall hardening, and encrypted remote access.
- Linux
- Docker
- Nginx
Data Scientist certification
I am a DataCamp Certified Associate Data Scientist, having demonstrated technical proficiency in SQL data extraction, Python-based statistical analysis, and predictive modeling. [View Certificate]
- Python
- Pandas
- Scikit-learn
Kaggle competitions
I am an active participant in Kaggle data science competitions, where I apply feature engineering and machine learning techniques to real-world predictive challenges. [My Profile]
- Pandas
- Scikit-learn
- PyTorch
Deymed
2019-2025
EM field simulation
Physical coil prototype making and measurement is expensive. Computation and visualization of EM fields produces near real-world values that reduce the need for physical coil prototypes to just a few samples.
- Python
- Numba
Measurement automation
Medical devices and their components are thoroughly tested. I integrated several simple elements into a complex system designed to collect and visualize precise measurement data.
- Python
- Plotly
TMS Neuronavigation Integration & Prototyping
I managed technical integration of neuronavigation systems for TMS therapy, focusing on API negotiation with third-party vendors and development of an in-house C++ prototype.
- C++
- gRPC
- HL7
Internal AI Automation Suite
I developed internal AI services using Python and LangChain to automate invoice processing, ticket summarization, and RAG-based search. With Ollama and FastAPI, the system provides secure local LLM capabilities.
- Python
- Ollama
- FastAPI
- Langchain
Full-Lifecycle Medical Software Engineering
Developing medical-grade software requires balancing technical performance with strict international safety regulations. I played a key role in the full SDL, ensuring phases from requirement analysis to deployment met quality standards by integrating IEC 62304 and ISO 14971 into the process.
Core Responsibilities & Impact
- Full-Lifecycle Management: From initial architecture and coding to automated build scripts and deployment.
- Regulatory Compliance: IEC 62304 and ISO 14971.
- V&V and Quality: Formal validation and test cases for QMS requirements.
- Cybersecurity: Security measures for sensitive medical data and system integrity.
- Maintenance & Support: Bug fixes, enhancements, localization, and tier-3 support.
- Delphi
- Inno Setup
- TeamViewer
- Jira
- EA
FDA-Cleared Medical Software
I led development of a new medical software application from concept to successful clinical launch and official FDA clearance. The system is now active in production.
- Delphi
- Jira
- Inno Setup
Hardware Emulation Framework
I proactively developed a hardware emulation framework that allows developers to test software virtually without physical devices, reducing bottlenecks and enabling automated edge-case testing.
- Own Initiative
- Delphi
- DLL
University
2013-2019
Rule Extraction from neural networks
My thesis focused on making artificial intelligence more understandable by extracting clear, human-readable rules from complex neural-network models.
Link to thesis on ResearchGate
- Python
- Tensorflow