| |
Multi-modal Learning in Soccer
|
Speaker (s):
Karolina Seweryn
Senior Data Scientist
NASK National Research Institute
|
|
Date:
Time:
Venue:
|
|
11 December 2023, Monday
10:30am – 12:00pm
School of Computing
& Information Systems 1 (SCIS 1)
Level 5, Meeting Room 5-1
Singapore Management University
80 Stamford Road, Singapore 178902
Please register by 6 December 2023.
We look forward to seeing you at this research seminar.
|
|
About the Talk
In the evolving world of sports, gaining a competitive edge often relies on leveraging the capabilities of data and technology. This talk explores the transformative potential of multi-modal learning in soccer, where the fusion of diverse data sources, such as video footage, sensor data, and textual analytics, creates a holistic understanding of athletic performance. By integrating information from various sensory modalities, coaches, athletes, and analysts can access valuable insights into strategy optimization, injury prevention, and player development. I will discuss cutting-edge techniques, including computer vision, natural language processing, and sensor data integration, that enable the extraction of actionable intelligence from complex, multi-dimensional datasets.
This seminar is co-organized by the IEEE Computational Intelligence Society Singapore Chapter.
About the Speaker
Karolina Seweryn is a Senior Data Scientist at NASK and a Ph.D. student at the Doctoral School of Information and Biomedical Technologies, Polish Academy of Sciences, specializing in multimodal data analysis, focusing on the fusion of text and video data for action recognition tasks. Karolina completed her master's in Mathematics with a specialization in Mathematical Statistics and Data Analysis at the Faculty of Mathematics and Information Science, Warsaw University of Technology, in 2020. In early 2021, she began her academic journey at Warsaw University of Technology, leading the research module "Data Modeling and Quality” of the grant project. In addition to her academic endeavors, Karolina has over 5 years of hands-on experience in applying machine learning models in the business sector, particularly in the banking and pharmaceutical industries, where she analyzed tabular data, textual data, and images.
|
