Keynote Speaker

Dr. Branislav Vuksanovic

Associate Head of School for Research and Innovation

University of Portsmouth, UK


Dr. Branislav Vuksanovic is an accomplished Electrical and Power Engineer, with a rich academic and professional background. He completed his undergraduate studies at the prestigious University of Belgrade, Serbia, and later earned his MSc degree in Measurement and Instrumentation from South Bank University in London, UK. He went on to earn his PhD in Active Noise Control from the University of Huddersfield, UK. Dr. Vuksanovic has an impressive career history, which includes working as a Project Engineer for the Croatian Electricity Board in Osijek, Croatia, and as a Research Fellow at Sheffield and Birmingham Universities. At the University of Derby, he served as a Lecturer and was a member of the Sensors and Controls Research Group. Currently, he holds the position of Associate Head of School for Research and Innovation at the University of Portsmouth, School of Energy and Electronic Engineering. He has authored numerous papers, including those in the areas of active noise control, biomedical signal processing, and pattern recognition for intrusion detection and knowledge-based authentication. He has also authored a book in the Digital Electronics and Microcontrollers field, and organized and chaired several international conferences and workshops. Dr. Vuksanovic currently serves as an Editor-In_Chief for the Journal of Image and Graphics and is a member of the IET and ASR. His current research interests revolve around the application of pattern recognition techniques for power systems, acoustic noise analysis and the processing of ground-penetrating radar data.

Speech Title: FER - Facial Expression Recognition - Advances and Challenges

Abstract: Facial expression recognition stands at the intersection of computer vision, machine learning, and human-computer interaction, with applications ranging from emotion analysis to human-robot interaction. This talk will provide a journey through the dynamic landscape of facial expression recognition, from its foundational principles to current state-of-the-art techniques. It will also delve into unsolved problems that persist in this field such as adapting to diverse human expressions, robustness to variability and cross-database generalisation. Finally, it will try to shed a bit of light on the ongoing research efforts of the presenter in the problem of cross-database expression recognition, aiming to bridge the gap between training data and real-world scenarios.