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Hi!

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.

Job

I am looking for a job for September 2024. If you are looking for a

  • Machine Learning Engineer/Data Scientist
  • Software Engineer in C++/Rust

in Western Europe, don't hesitate to send me a mail! See below for more information about me.

Personal interests

  • 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.

ML Projects

  • 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

Dev projects

  • 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

Past experiences

  • 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

Daniel Mokeev's Projects

burn icon burn

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

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