Georgios Chatzikonstantinidis

Georgios Chatzikonstantinidis has a strong background in data science, with experience in various roles and industries. Georgios is currently working as a Data Scientist at OilX, where they have developed an MLOps toolkit for time series analysis, supervised an NLP project for news extraction, and maintained ETL processes. Prior to this, Georgios completed mandatory military service in the Hellenic Army, where they were responsible for organizing and assigning tasks to privates and providing administrative support to commanding officers. Georgios also worked as a PHD Researcher at the University of Birmingham, where they developed algorithms for classifying rare events in large data sets, led the measurement of novel parameters sensitive to new physics, and contributed to the development of software tools for parameter estimations. During their time at the University of Birmingham, they also served as a Teaching Assistant. In addition, Georgios gained valuable experience as a Summer Student at CERN.

Georgios Chatzikonstantinidis completed their education in a chronological order as follows:

Georgios pursued a Doctor of Philosophy (PhD) in Particle Physics from the University of Birmingham, during the period from 2015 to 2019.

Prior to their PhD, they obtained a Master's degree in Particle and Astroparticle Physics from the University of Amsterdam between 2013 and 2015.

Georgios had previously attended Aristotle University of Thessaloniki (AUTH) from 2007 to 2013, where they obtained a Bachelor's degree in Physics.

In addition to their formal education, Georgios has acquired several certifications to complement their academic background. These include the following:

- "Docker Masterclass for Machine Learning and Data Science" from Udemy, obtained in May 2022.

- "Scalable Data Analysis in Python with Dask" from Udemy, obtained in October 2021.

- "NLP - Natural Language Processing with Python" from Udemy, obtained in August 2021.

- "GIT: Advanced commands" from Udemy, obtained in July 2021.

- "Machine learning for High Energy Physics" from Yandex, obtained in August 2018.