معرفی
Yanda Tao is a Researcher at the Department of Computing, Imperial College London, funded by Samsung since March 2024. He graduated with distinction from the MSc Advanced Computing program at Imperial College London (2022-2023) and holds an Ingénieur degree in AI from CentraleSupélec, Université Paris-Saclay (2019-2023). During his master's, he developed HetML, a system for heterogeneity-aware automatic parallel training of deep learning models under the supervision of Professor Peter Pietzuch at LSDS (Large-Scale Data and Systems Group).
His research focuses on machine learning systems design for heterogeneous GPU clusters, optimizing cloud infrastructure for deep learning workflows, and improving distributed training efficiency. Technical expertise includes system architecture, parallel computing, and ML pipeline deployment gained through internships at Alstom (Data Scientist) and SAP France (Software Engineer). His work bridges theoretical system design with practical implementation challenges in large-scale ML environments.
The HetML project (2023, in preparation) demonstrates his specialization in automatic parallelism techniques and heterogeneity-aware optimization for distributed deep learning. This aligns with his broader interest in scalable machine learning infrastructure and cost-efficient system design for democratizing large-scale AI applications.
