Yongtao Wu

Yongtao Wu is a Doctoral Assistant and student in the doctoral program in Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL). He is affiliated with the Laboratory for Information and Inference Systems (LIONS), part of the School of Engineering (STI) and the Institute of Electrical Engineering (IEM). His research focuses on machine learning, adversarial learning, computer vision, and deep learning, with applications in vision-language models, robustness analysis, and optimization algorithms.

His work explores topics such as diffusion-based purification for vision-language models, adversarial attacks on large models, and parameter-efficient fine-tuning techniques. He contributes to advancing foundational AI models and their robustness in real-world scenarios. His research also intersects with cybersecurity, structural engineering predictions, and quantum computing methodologies.

Yongtao is actively involved in the LIONS lab, collaborating on projects that bridge theoretical advancements with practical applications in computer science and engineering. His doctoral studies emphasize interdisciplinary approaches to solving complex problems in AI and machine learning.