generative models

KAUST Workshop on Distributed Training in the Era of Large Models

Nov 24 - 26, All day

Auditorium between B4 & 5, L0, R0215

machine learning Distributed algorithms generative models ML

Join leading researchers and innovators to explore how distributed training is reshaping the next generation of large-scale AI models.

Xiaoqian Shen

Ph.D. Student, Computer Vision- Core Artificial Intelligence Research

generative models low-resource learning

Education Xiaoqian Shen is a Master's student at Vision-CAIR group in Visual Computing Center (VCC), King Abdullah University of Science and Technology (KAUST). • 2018-2022: BSc in Computer Science & Technology Dept. of Computer Science and Technology, Jilin University, China Research Interest • My research mainly focuses on leveraging natural language to facilitate better visual representation in a low-resource setting. Work Experience • Medical relation extraction for Chinese medicine instructions, 2021, Tsinghua University, China • Self-supervised Learning for medical image segmentation

Ivan Skorokhodov

Ph.D. Student, Computer Science

Deep learning Computer Vision generative models

Ivan Skorokhodov is a Ph.D. candidate in the Computer Science Program under the supervision of Professor Peter Wonka at Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). His research interests include such areas of deep learning as generative models, hypernetworks and neural rendering. Ivan Skorokhodov has obtained his Ph.D degree and graduated in March 2023. Education and Early Career Ivan obtained his bachelor's degree in Management from the Moscow Engineering Physics Institute in 2014. He continued his studies there and received his master's degree