DESCRIPTION
Marketing studies on consumer behavior analysis increasingly depend on trustworthy AI methods and signal processing techniques for extracting objective and reliable independent variables that are less prone to variances introduced by self-reported variables and metrics. Advanced and expensive sensors (e.g., eye-trackers and electroencephalograms) are employed to collect consumer-independent spatiotemporal high-dimensional data, mainly including video recordings and electrical signals corresponding to some given input stimuli e.g., a visual advertisement. Neuromarketing, being a multidisciplinary domain, studies and develops methods and tools for extracting advanced consumer behavior insights by analyzing multimodal biometric data from sensors, facilitating and streamlining marketing studies. This short course equips the audience with the necessary knowledge and skills for conducting research on the Neuromarketing domain, including lectures overviewing state-of-the-art neuromarketing sensors and tools, the underlined AI and signal processing methods for signal/video acquisition/filtering/processing in order to extract variables correlated with high-level Cognitive Human Emotional Responses (e.g., attention), the timely challenges in the domain and concludes with proposals for future research/further study directions.
DETAILS
Course type: Short course
Duration: 8 1h lectures for a total duration of 8 hours (full day)
Institutions of lecturers: University of Antwerp, Belgium, Center of Research & Technology Hellas (CERTH)
Notes: Course will include theoretical and programming parts. The theoretical part will be evaluated with multiple choice questions prepared using an online form and the programming part will be evaluated with a short assignment. Students will be deemed successful if they have correctly answered more than 50% of the total questions and have completed the assignment. There will be no ECTS accreditation, as University of Antwerp is not an AIDA member.
LECTURERS
Dr. Vasileios Mygdalis & Dr. Vangelis P. Oikonomou
Dr. Vasileios Mygdalis is a research associate specialized in Machine Learning. He is currently a postdoctoral research fellow (MSCA-PF) at the Marketing Research Group, University of Antwerp. He received his Ph.D. in Computer Science from Aristotle University of Thessaloniki (2019). He has served as researcher and teaching assistant in the fields of machine learning, image processing, computer vision and pattern recognition. Vasileios has (co-)authored more than 38 peer-reviewed papers in academic journals and international conferences. His current research interests include the areas of Attention-Based Marketing, Trustworthy AI, Adversarial Robustness, Computer Vision, Machine Learning, Robotic Perception.
Dr. Vangelis P. Oikonomou received his diploma degree in Computer Science, the MSc degree in Computer Science and the PhD degree in Bayesian methods for biomedical signal and image analysis, from University of Ioannina in 2001, 2003 and 2010, respectively. From 2011-2015 he was a visiting Assistant Professor in Technological Educational Institutes of Ionian Islands and Epirus. He is author and co – author of more than 50 journal papers, book chapters and peer-reviewed conference publications. He had supervised more than 5 theses. His research interests include machine learning, Bayesian reasoning, data analysis, biomedical signal and image analysis, statistical signal processing, medical imaging, and, brain – computer interfaces. He is currently a senior researcher in the Information Technologies Institute (ITI) at the Centre for Research & Technology Hellas (CERTH). He has participated in a number of EC-funded projects.