• Vision-language models (general and domain-specific) for diverse downstream tasks and evaluation
• Video understanding with spatio-temporal modelling, particulary human activity analysis
• Multimodal representation learning
• Object recognition and detection
• Deep learning models, particulary CNNs, RNNs, Transformers

Selen Pehlivan Tort is a Research Scientist at VTT Technical Research Centre of Finland. With over 15 years of experience in computer vision and machine learning, she focuses her research on visual recognition, video understanding, deep learning, and multimodal representation learning. She received her PhD in computer vision from the Department of Computer Engineering at Bilkent University in 2012. She was a visiting scholar at the University of Illinois at Urbana-Champaign (2009–2011), a postdoctoral research associate at the Center for Research in Computer Vision at the University of Central Florida (2013), and a faculty member in the Department of Computer Engineering at TED University, Turkey (2014–2020). Before joining VTT, she worked as a researcher in the Department of Computer Science at Aalto University (2019–2023).