Konstantinos Georgatzis

Konstantinos Georgatzis has a strong background in data science and research. Konstantinos is currently the Director of Data Science & Research at WovenLight starting from May 2022. Prior to this, they worked at QuantumBlack as a Senior Principal in Data Science and as the Global Head of R&D in Data Science, from October 2016 to March 2022. At QuantumBlack, they handled data science projects, coordinated teams, and developed advanced analytics methods. Konstantinos also served as an Associate Partner at McKinsey & Company from October 2016 to March 2022.

Before their industry roles, Konstantinos was a PhD student at the University of Edinburgh Informatics School from September 2012 to October 2016. Konstantinos'sresearch focused on dynamic probabilistic graphical models for physiological condition monitoring. Konstantinos collaborated closely with NHS clinical experts and their work was reviewed and approved by leading NHS intensivists. Konstantinos also had teaching responsibilities, serving as a teaching assistant, tutor, marker, and reviewer for undergraduate and postgraduate students during this time.

In addition, Konstantinos gained experience as an intern at The Alan Turing Institute in the summer of 2016. Konstantinos contributed to the research project "Cloudy with a Chance of Pain," where they explored the relationship between weather and pain using machine learning methods. Konstantinos also worked as a research assistant at Aalto University School of Science and Technology in 2012.

Overall, Konstantinos Georgatzis has a wealth of experience in data science, research, and academia, with a focus on applied machine learning and advanced analytics methods.

Konstantinos Georgatzis obtained a Master of Engineering (MEng) degree in Electrical Engineering and Computer Science from the National Technical University of Athens from 2003 to 2009. Following this, they pursued a Master's Degree in Artificial Intelligence (Machine Learning) at The University of Edinburgh from 2010 to 2011. Finally, they completed their education with a Doctor of Philosophy (Ph.D.) degree in Machine Learning from The University of Edinburgh from 2012 to 2016.