Hey there! ๐ค I am Gleb Lukicov, a machine learning engineer with a passion for MLOps.
On this page, you can read about
my ML projects and articles,
PhD research, outreach activities,
and interests.
๐ค ML projects and articles ๐
❖ Are you a data scientist or an AI engineer
trying to bridge local development and production deployment of
ML projects without the hassle?
Read this blog post to find out how pipelines enable scalable experimentation with Kubeflow, Docker, uv and Vertex AI on Google Cloud.
❖ In the video below, I share my
professional journey at
Virgin Media O2, where we are utilising the power of Google
Cloud to enable us
to make data-driven
decisions that improve our customers' experiences.
For this work, our team won the DevOps award in 2022
and 2023
❖ In this podcast by, I discuss why your business might benefit from MLOps,
MLOps Community London meetups
and the exciting work we do at Electric Twin on simulating human behaviour in real-time with AI.
❖ Essential software tools for data
science projects ๐งโ๐ป -
Python, Matplotlib style, Git Pages, VSCode, Notion,
Grammarly. I describe it in this Towards Data
Science article.
❖ Set-up of a personal GPU server ๐ฅ for
ML with Ubuntu
and TensorFlowGPU, JupyterLab, CUDA, Port-forwarding, DNS,
SSHFS.
I explain it in this Towards Data
Science article.
❖ ๐ Some great resources
that helped me on my
data science and ML journey:
1)
Hands-On
Machine Learning by Aurelien Geron,
which is accompanied by well-structured Jupyter notebook
exercises.
2)
Designing
Machine Learning Systems by Chip Huyen.
Chip also maintains an excellent and up-to-date collection of MLOps
materials.
3)
Build
a Career in Data Science by Emily Robinson and Jacqueline
Nolis.
This is a wonderful resource covering interview preparation and how
to grow in your new
data science role.
Emily and Jacqueline also host a podcast
on the very same topic!
1) Hands-On Machine Learning by Aurelien Geron, which is accompanied by well-structured Jupyter notebook exercises.
2) Designing Machine Learning Systems by Chip Huyen. Chip also maintains an excellent and up-to-date collection of MLOps materials.
3) Build a Career in Data Science by Emily Robinson and Jacqueline Nolis. This is a wonderful resource covering interview preparation and how to grow in your new data science role. Emily and Jacqueline also host a podcast on the very same topic!
The g โ 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.
Software developmentTo accurately measure this anomaly, a calibration of the tracking detectors is required. The main project of my PhD involved developing, testing and deploying the calibration software framework, which increased the yield of data by 3% and the data quality by 4%. The alignment procedure is a statistical problem, which involved the optimisation of the p-values of tracks via matrix inversion.
Presenting at the American Physical Society conference. (Boston 2019)
Research software developed:
Data analysis:
Detector calibration:
Selected written work:
There is also an additional measurement that will be made using the tracking detectors: setting a new limit on the electric dipole moment (EDM) of the muon, producing a world-leading result. I have been developing algorithms to measure the muon EDM, by analysing large and complex datasets using regression and Fourier transform methods.
Data acquisitionAn essential component of the experiment is the data acquisition (DAQ) system, which manages the data flow from the detector electronics. The experiment is acquiring raw data at a rate of 20 GB/s. This is accomplished by employing a parallel data processing architecture using 28 high-speed GPUs (NVIDIA Tesla K40), reducing the recorded data rate to 200 MB/s. To support the smooth operation of the experiment and ensure continuous data taking, a team of data acquisition (DAQ) experts are available for 24/7 support. I have actively participated as the DAQ on-call computing expert between 2017 and 2019.
๐ญ Education outreach projects ๐ฌ
I am actively engaged in the MLOps Community London, the largest MLOps community in Europe, as a co-host and events organiser. We are putting regular in-person meetup-ups, for the community to learn together and discuss latest MLOps trends over ๐บ and ๐. Keep an eye on the upcoming events here. (London 2023)
Delivering an alumni talk at the Woodhouse College ๐ about my all-time favourite particle - the muon - and how it can be used for treasure-hunting ๐, making borders more secure ๐ฎโโ๏ธ, and unlocking the mysteries of the Universe ๐. I come back to the college every year to encourage students in pursuing a career in STEM. (London 2019)
๐ Guiding a public tour of the Fermilab Muon g — 2 experiment. The experiment has measured an anomaly in a property of a fundamental particle, expanding our knowledge of the Universe and providing evidence of the existence of new particles.(Chicago 2018)
Explaining spectroscopy ๐ญ to primary school students at the Your Universe astronomy festival at UCL. I was involved with the festival between 2010 and 2015. Every year, I was able to deliver educational activities to 300 pupils. I also had a chance to meet Geraldine Cox during the festival. (London 2015)
๐โโ๏ธPersonal interests ๐ดโโ๏ธ
As part of a charity fundraising, I ran my first full marathon ๐โโ (5:31 / 1 km elevation) and cycled 100 km ๐ด (4:44 / 2 km elevation). This motivated me all the way (twice!) to the top of that mountain, and our team manged to fundraise ยฃ2.3K for Street Child. (Switzerland 2022)
Next year, our team was back at it! With a mini tour-of-Netherlands: ๐ด 160 km day 1 (6:28 / 0.8 km elevation) and ๐ด 175 km day 2 (6:37 / 1.1 km elevation). This time, we have raised ยฃ3.8K for Street Child. (Netherlands 2023)