// technical profile
Skills
Languages, frameworks, domains and tools I work with regularly.
Programming Languages
Primary
- Python
- C++
- Java
- C#
Systems & Mobile
- Swift
- C
- Bash
Other
- Haskell
- JavaScript
- Erlang
Algorithms & Theory
Algorithms
- Sorting / searching
- Graph algorithms
- Dynamic programming
- Greedy algorithms
Complexity
- Time / space complexity
- P vs NP
- NP-completeness
- Reductions
Formal Methods
- Finite automata
- Regular languages
- CFG
- Turing machines
Mathematics
Discrete
- Graph theory
- Combinatorics
- Logic
- Set theory
Analysis
- Limits
- Differentiation
- Integration
- Series
Probability & Stats
- Distributions
- Expected value
- Hypothesis testing
- Inference
Machine Learning
Models
- Linear regression
- Random Forest
- SVM
- Neural networks
Workflow
- Data preprocessing
- Feature engineering
- Train / test split
- Hyperparameter tuning
Evaluation
- Accuracy / F1
- ROC / AUC
- Confusion matrix
- Error analysis
- Cross-validation
- Bias-variance
- Regularization
- Overfitting
Advanced ML Models & Concepts
Generative Models
- Autoencoders (VAE)
- GAN
- Diffusion models
- Latent space modeling
Neural Rendering
- NeRF
- Gaussian Splatting
- 3D scene representation
- View synthesis
Learning Paradigms
- Few-shot learning
- Continual learning
- Transfer learning
- Representation learning
Applied Skills
- Model selection
- Result interpretation
- AI problem formulation
- Large-scale data analysis
Graph Theory & Graph ML
Graph Theory
- Graph representations
- Adjacency / incidence
- Directed / undirected graphs
- Weighted graphs
Algorithms
- BFS / DFS
- Shortest paths (Dijkstra)
- Spanning trees
- Connectivity
Graph ML
- Graph embeddings
- Node classification
- Link prediction
- Graph-based features
Applications
- Social networks
- Biological networks
- Molecular graphs
- Knowledge graphs
Data Engineering
Databases
- Relational databases
- SQL optimization
- Normalization
- Indexing
Big Data
- Distributed systems
- ETL
- Data pipelines
- Storage systems
Processing
- Batch processing
- Data cleaning
- Transformation
- Data modeling
ML in Drug Design
Molecular Data
- SMILES
- Molecular descriptors
- Fingerprints
- RDKit
Methods
- QSAR
- Virtual screening
- ADMET prediction
- Regression models
Data Sources
- ChEMBL
- PubChem
- ZINC
- Dataset preprocessing
Bioinformatics
Data
- DNA / RNA
- FASTA / VCF
- BAM files
- Protein data
Tools
- BLAST
- GATK
- samtools
- Pipelines
Analysis
- Sequence alignment
- Variant calling
- Phylogenetics (basic)
- Data interpretation
Biometrics
Modalities
- Face recognition
- Fingerprints
- Iris
- Voice
Processing
- Image preprocessing
- Feature extraction
- Signal processing
- Pattern matching
ML usage
- Classification
- CNN basics
- Feature vectors
- Evaluation
Low-level & Systems
Architecture
- x86 / x86_64
- Memory layout
- Cache
- Branch prediction
Assembly & C++
- Calling conventions
- System V ABI
- Intrinsics
- ASM + C/C++
Optimization
- SSE / AVX
- Loop optimization
- Memory access
- Profiling
Operating Systems
Core
- Processes / threads
- Scheduling
- Memory management
- Virtual memory
Concurrency
- Mutex / semaphores
- Deadlocks
- Synchronization
- Race conditions
Systems
- File systems
- System calls
- IPC
- Unix internals
Computer Networks
Protocols
- IPv4 / IPv6
- TCP / UDP
- DNS
- Routing
Infrastructure
- Routers / switches
- VoIP / SIP
- Servers
- IP cameras
Security
- Wireshark
- Traffic analysis
- Firewall
- Network security
Cryptography
Classical & Modern
- AES
- RSA
- SHA
- Digital signatures
Protocols & Concepts
- TLS / HTTPS
- Diffie–Hellman
- PKI
- Authentication
Post-Quantum & Advanced
- Lattice crypto
- CRYSTALS-Kyber
- ECC
- BB84
Tools & Systems
Dev Tools
- Git / GitHub
- VS Code
- Xcode
- JetBrains
Systems
- Linux / Unix
- Bash
- Docker
- SSH
Languages
- Polish — native
- English — C1