PhD research project: Semantic Future Prediction. The project is part of the ARCHIMEDES Unit, implemented by the National Recovery and Resilience Plan “Greece 2.0” and funded by the European Union – NextGenerationEU.
Research Experience
Relevant research experience in designing, developing, and evaluating self-supervised learning methods. While working on his diploma dissertation thesis, he studied unsupervised learning techniques for leveraging large sets of unlabeled data to enhance accuracy, efficiency, and scalability of perception systems used in autonomous vehicles.
Education
Meng in Electrical and Computer Engineering from the Democritus University of Thrace, specialized in Electronic and Information Systems, graduated in December 2022, achieving the highest grade among his peers.
Background
Research interests include computer vision and deep unsupervised learning. Specifically, his research will focus on developing innovative self-supervised learning methods to extract high-quality representations from large sets of unlabeled multimodal data.