My name is Daniel Mokeev and I am a final year student in Applied Mathematics at UCLouvain in Belgium. My thesis is on efficient MCMC methods for density matrix estimation in Quantum Tomography (have a look here for a brief overview). I was previously an exchange student at Aalto University in Finland.

• I am very interested in Probabilistic Machine Learning, notably MCMC, Gaussian Processes, Causal Inference and Bayesian Statistics in general. Bonus points if there is some implementation involved!
• I really enjoy systems programming and programming languages, anything related to compilers, performance optimizations, databases, operating systems and other low level bits.

• Exoplanet detection with Conditional Variational Autoencoders with PyTorch
• Predicting solar PV production with State-Space Gaussian Processes with JAX
• Treatment effect estimation (ATE) with Causal Inference using R and Stan

• Currently going through PPC in C++ and Advanced Systems Programming in Rust
• Quick sort implentation on single/multi GPU in CUDA and MPI
• Full-stack implementation of a shopping cart with React/Node.js and deployed with Docker
• C projects: Multithreaded KMeans, simplified TCP with sender/receiver

• Machine Learning Intern at Aerospacelab
  • Cloud detection in satellite images using Vision Transformers in PyTorch
• Data Engineering Intern at Riaktr
  • ETL development, KPIs calculations, EDA using PySpark, Airflow, Pandas and deploying with Docker
• Python Developer at MBA
  • Working with Google APIs and SQL databases to develop internal tooling