International Conference on Machine Learning and Applications · 2022
Cited
3
Resume (English only)
Research Experience
Conducted research on human motion prediction using deep learning models during his PhD; completed a six-month internship at Amazon, where he developed and deployed a Transformer-based system for real-time transit time estimation across the EU logistics network.
Education
Worked on computer vision techniques for detecting road lanes in autonomous vehicles during his Master's degree, which sparked an interest in deep learning. Pursued a PhD in human motion prediction, exploring how deep learning models could predict movement patterns based on contextual information derived from the agent and its trajectories.
Background
Motivated by machine learning, data science, computer vision, and robotics. Driven to learn new topics within these areas and deploy them in real-world applications.
Miscellany
Still as curious and driven as ever, eager to continue learning and pushing the boundaries of what AI can achieve in the real world.