Bio
I am currently a Ph.D. candidate in Computer Science at the University of Illinois Chicago (UIC) guided by Prof. Yan Yan.
My research focuses on data-centric machine learning, with interests in dataset distillation, synthetic data generation, and data selection for LLMs. My work has been published in top-tier conferences such as CVPR, ICCV, ECCV, and NeurIPS, covering topics like dataset distillation for image and multimodal datasets, synthetic dataset generation, and algorithm for data selection.
I interned at Argonne National Laboratory in 2023 and 2025. In 2023, I studied the performance of distributed training frameworks such as PyTorch DDP, Horovod, and DeepSpeed. In 2025, I returned to Argonne to work on LLM training on high-performance computing (HPC) platforms, where I conducted a comparative study of DeepSpeed, TorchTitan, and FSDP for scalable optimization.
Before Ph.D., I received my M.S. in Computer Science from the Illinois Institute of Technology (IIT) and a B.S. in Computer Science and Engineering from Nanjing University of Post and Telecommunications (NJUPT).
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