Research & AI
- Machine Learning
- Federated Learning
- Asynchronous Federated Learning
- Client Selection
- Privacy-preserving ML
- Large Language Models
- Decision Models
- Machine Unlearning
- Energy-aware AI
Skills & expertise
The tools behind the work.
Research methods, languages, and systems I use to turn ideas into working AI.
Applied AI
- Regression
- Classification
- Recommender Systems
- NLP
- Time-series Forecasting
- Explainable AI
- Anomaly Detection
Privacy & security
- Differential Privacy
- Secure Aggregation
- Homomorphic Encryption
- Membership Inference Attacks
- Opacus
- SEAL / TenSEAL
Programming languages
- Python
- C++
- C#
- Java
- Kotlin
- SQL
- JavaScript
- TypeScript
Machine learning & data
- PyTorch
- Scikit-learn
- Pandas
- NumPy
- CatBoost
- Hugging Face
Visualization
- Matplotlib
- Plotly
Backend & APIs
- FastAPI
- Spring Boot
- Celery
- REST APIs
- Server-Sent Events
- Authentication
- Role-based Access Control
Databases & storage
- PostgreSQL
- MySQL
- Redis
- Qdrant
- ChromaDB
- DuckDB
- Vector Databases
- S3-compatible Storage
- Garage
Web & mobile
- React
- Vue.js
- Nuxt
- Vite
- Streamlit
- Flutter
- Progressive Web Apps
- Capacitor
LLM systems
- RAG
- LangChain
- Ollama
- Embeddings
- Hybrid Search
- BM25
- LLM Routing
- AI Agents
Infrastructure & collaboration
- Linux
- Docker
- Docker Compose
- Git
- GitHub
- uv
- Asynchronous Processing
- Reproducible Experiments
- API Deployment