Skip to content
View glukicov's full-sized avatar
🀠
Focusing
🀠
Focusing
Block or Report

Block or report glukicov

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
glukicov/README.md

Hey there πŸ‘‹

Ask Me Anything !

I am Gleb Lukicov, a machine learning engineer with a passion for MLOps. Visit my homepage to read about my PhD research and ML projects. When I am not de-bugging my code, I am actively engaged in the MLOps Community London as a co-host, πŸ“ tech blogging, or πŸš΄β€β™‚οΈ road cycling. You can contact me for collaborations ideas or questions on LinkedIn.

The project repositories below contain some of the analysis code used in my PhD thesis and personal ML projects:

1. EDMTracking contains analysis code (Python, C++, Bash) to perform Fourier transforms and regression on large datasets.

The Muon g βˆ’ 2 experiment at Fermilab, near Chicago, discovered a tantalising sign of New Physics (a new force of nature!). This was done by measuring a deviation between the experimental and theoretically predicted value of the muon magnetic anomaly. As part of my PhD, I collaborated on the experiment with 200 scientists and engineers.

This project contains analysis code to measure the Electric Dipole Moment (EDM) of the muon using the tracking detectors. The oscillation in the number of the observed tracks in the detector can be plotted and fitted, as shown below

2. alignTrack is the detector calibration codebase (C++, Python, Fortran) using iterative optimisation and data simulation.

This project contains code and plotting scripts for the internal alignment (calibration) of the tracking detector. The alignment procedure aims to establish the corrections to the assumed detector position, and hence, minimise the residuals. This minimisation of the residuals is a statistical problem, involving the optimisation of the p-values (i.e. track quality) of fitted tracks in data.

This work led to a publication (arXiv:1909.12900): https://arxiv.org/pdf/1909.12900.pdf, where alignment results with data are discussed.

Alignment software infrastructure is shown below

3. ML_GPU contains personal practice ML code, and Deep Learning on GPUs using scikit-learn, TensorFlow and Keras.

I wrote a practical guide on setting a personal GPU server for Machine Learning with Ubuntu 20.04 avaialbe on the Towards Data Science (TDS) website.

Photo by Caspar Camille Rubin on Unsplash.

Pinned Loading

  1. EDMTracking EDMTracking Public

    Electric Dipole Moment (EDM) analysis code with big-data (Python, C, SQL)

    Jupyter Notebook 1 1

  2. alignTrack alignTrack Public

    Alignment Code for the g-2 tracking detector (C++, Python, Fortran)

    Jupyter Notebook 1

  3. ML_GPU ML_GPU Public

    ML practice code: simple ML examples and Deep Learning on GPU

    Jupyter Notebook 3 3