Arda Baris Basaran is a doctoral researcher at ETH Zurich, working at ADAMMA within the Center for Digital Health Interventions. His current work includes contributing to the development of a smart health assistant, and more broadly, he is interested in how machine learning and multimodal models can support data-driven approaches to healthcare and human well-being.
Arda holds a Master’s degree in Electrical and Electronics Engineering from EPFL, specializing in Data Science and Systems, and a Bachelor’s degree from Middle East Technical University, where he developed a strong foundation in signal and image processing and 3D vision. Over the past two years, he conducted research at EPFL’s Signal Processing Laboratory 5 under the supervision of Prof. Jean-Philippe Thiran and Dr. Behzad Bozorgtabar. His work primarily focused on multimodal learning, computer vision, and self-supervised learning. His Master’s thesis explored anomaly detection in industrial environments using vision-language models, building on earlier projects involving knowledge distillation, contrastive learning, and self-supervised training. His industry experience includes developing real-time 6-DOF pose estimation pipelines at Logitech, alongside earlier roles involving visual navigation, computer vision, and machine learning.