KTU Big Data School 2021 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.
Lecturers:
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.
Prof. dr. Luca Citi
Short-bio: Dr. Luca Citi is a professor at Essex University in UK. He holds a degree University of Florence (Italy). He obtained a PhD in Biorobotics Science and Engineering jointly offered by IMT School for Advanced Studies Lucca (Italy) with a thesis about the decoding of neural signals for the control of robotic arm prostheses. His main research is directed to applications in medicine. Luca’s skills and expertise involve machine learning, biomedical signal processing, computational intelligence, pattern recognition, signal processing, classification, supervised learning, statistical learning, electroencephalography, etc.
Dr. Diana G. Maynard
Short-bio: Dr Diana Maynard is a Senior Researcher at the University of Sheffield, where since 2000 she has led the development of Sheffield’s open-source multilingual text analysis tools, and has led research teams on a number of UK and EU projects. Her main research interests are in tools for language technology, information extraction, sentiment analysis, social media analysis and terminology. Dr. Maynard has recently worked on EU projects developing social media analysis tools for investigating attitudes towards climate change, and for communication during disasters, and currently works on various projects ranging from social media, online abuse detection and freedom of the media to healthcare, food science, and scientometrics.
