Michal Gnacik
About Michal Gnacik
Michal Gnacik is a Senior Data Scientist at Arca Blanca in London, specializing in deep learning models for facial expression recognition. He has a strong academic background in mathematics, holding a PhD from Lancaster University and a Master's degree from Vrije Universiteit Amsterdam.
Work at Arca Blanca
Currently, Michal Gnacik serves as a Senior Data Scientist at Arca Blanca, an Artefact company, since 2023. In this role, he focuses on developing deep learning models, including convolutional neural networks (CNNs) and Siamese Networks, specifically for identifying facial expressions. Prior to this position, he worked as a Data Scientist at the same company from 2022 to 2023.
Education and Expertise
Michal Gnacik holds a Doctor of Philosophy (PhD) in Mathematics from Lancaster University, where he studied from 2010 to 2014. He also earned a Master of Science (MS) in Mathematics from Vrije Universiteit Amsterdam in 2010. Additionally, he completed a Master's degree in Mathematics at Uniwersytet Śląski w Katowicach from 2005 to 2010. His research interests include inverse eigenvalue problems and the application of linear algebra techniques to machine learning.
Background
Before joining Arca Blanca, Michal Gnacik held various academic positions at the University of Portsmouth. He served as an Associate Professor/Senior Lecturer in Mathematics from 2019 to 2022 and as an Assistant Professor/Lecturer from 2016 to 2019. His earlier role at the university included working as an Academic Tutor/Learning Support Tutor from 2014 to 2016. He also gained experience as a Graduate Teaching Assistant at Lancaster University from 2010 to 2014.
Research and Development
Michal has developed a 'Live voice vowel inference web app' funded by the University of Cambridge, aimed at automated extraction and analysis of vowels. He has published multiple papers in prestigious international journals, including Annales Henri Poincaré, Journal of Statistical Physics, and Physical Review E. His skills include using Plotly and Folium for creating interactive choropleth maps and plots, as well as building spatial models for the real estate industry.
Professional Experience
Prior to his academic career, Michal worked as an Associate Test Engineer at Kroll Ontrack from 2008 to 2009. His professional experience also includes a focus on developing reinforcement learning-driven dynamic pricing engines and utilizing variational autoencoders in automated audio processing.