TS. Trần Quốc Long
TS. Trần Quốc Long hiện công tác tại Trường ĐH Công nghệ, ĐHQG Hà Nội. Tiến sĩ Long tốt nghiệp Tiến sĩ năm 2015 tại Viện Công nghệ Georgia (Georgia Tech, USA). Hướng nghiên cứu gần đây bao gồm mô hình sinh dữ liệu bằng học sâu và ứng dụng học máy trong phân tích dữ liệu ảnh y tế. 

Talk title: Diffusion models
Abstract: The development of diffusion models has provided powerful tools for text-conditional generative tasks. The popular text-to-image models can now synthesize high-quality, artistic/photo-realistic images just from the semantic description, drastically affecting the future of art and different aspects of life. Besides images, the upcoming works promise to produce high-quality videos, 3D models, and 4D videos, opening a wide range of real-life applications.
 

Asoc. Prof. Trần Thế Truyền
Dr Truyen Tran is Associate Professor, Head of AI, Health and Science at Deakin University where he leads a research team on the next generation of deep learning and applications to computer vision, materials sciences, biomedicine and software. Tran has received multiple recognitions, awards and prizes for his research. He obtained a Bachelor of Science from University of Melbourne and a PhD in Computer Science from Curtin University in 2001 and 2008, respectively.

Talk title: Deep learning and reasoning: Recent advances
Abstract: Deep learning has recently reached the height the pioneers wished for, serving as the driving force behind recent breakthroughs in AI, which have arguably surpassed the Turing test. In this tutorial, we will provide an overview of the fundamental principles of deep learning and explore the latest advances in the field, including Foundation Models. We will also examine the powers and limitations of deep learning, exploring how reasoning may emerge from carefully crafted neural networks and massively pre-trained models.