KTU Big Data School 2022 is both theoretical and practical scientific event aiming at updating participants about the most recent advances in the critical and fast developing area of big data, which covers topics such as big data and financial analytics, machine learning, big data processing, etc.
The event is concentrated towards deep theoretical background and improving skills during practical workshops.
The event will take place at Kaunas University of technology and is organized by the Faculty of Mathematics and Natural Sciences. The sessions will be held at KTU Technology and Business Centre Santaka Valley.
There will be three sessions given by different experienced speakers involving lectures and practical tasks.
The event is addressed to Industry practitioners, Scientists, PhD students, postdocs and Master students.
Dr. Michael Fairbank
Short-bio: Michael Fairbank is a Computer Science lecturer at the University of Essex, UK. He is an active machine-learning researcher, with publications in reinforcement learning, deep learning and neural networks. In his previous careers he worked as a computer consultant and as a mathematics teacher. He has a passion for all things related to computing, mathematics and AI.
Assoc. prof. Hannes Mueller
Short-bio: Hannes Mueller is a tenured researcher at the Institute for Economic Analysis (IAE-CSIC) and an Associate Research Professor at the Barcelona School of Economics (BSE) . He is the director of the Data Science for Decision Making Program and head of department at the IAE-CSIC. Mueller’s fields of interest are Machine Learning, Political Economy, Development Economics and Conflict Studies with a particular focus on the effect of violent conflict on the economy.
Assoc. prof. Christian Brownlees
Short-bio: Christian Brownlees is an Associate Professor in the Department of Economics and Business at the Universitat Pompeu Fabra. Christian received his PhD in Statistics from Universita’ di Firenze, he was a visiting PhD researcher at UCSD and post-doc researcher at NYU. Christian’s research lays at the intersection of statistics, econometrics, economics and finance. In particular, his research focuses on volatility, network models and systemic risk.Christian has published in the Journal of Econometrics, the Review of Economics and Statistics, Annals of Statistics and the Review of Financial Studies.