Role: Main Lecturer
A 12-week postgraduate course on deep learning fundamentals and modern architectures, emphasizing theory, implementation, and research discussions. The course combines weekly lectures, coding sessions, and project work using PyTorch.
Role: Main Lecturer
A 16-week course with two 1.5-hour sessions per week, covering classical machine learning, representation learning, autoencoders, CNNs, LSTMs, GANs, and advanced topics like zero-shot learning and model robustness.
Role: Main Lecturer
A 16-week course focusing on AI trustworthiness β including safety, security, fairness, bias, transparency, and adversarial robustness. Students participated in paper discussions, research presentations, and implementation projects, with assessments based on seminars, projects, and a final exam.
Role: Main Lecturer
This 16-week course paralleled the βAdvanced Topics in AIβ course at IPM, focusing specifically on deep learning safety and security, including adversarial attacks and model robustness.