Her research vision is in general artificial intelligence systems to facilitate deep learning implementation on various edge devices and bridge the gap between algorithm innovations and hardware performance optimizations by a hardware and software co-design approach. It includes energy-efficient deep learning and artificial intelligence systems and accelerations of deep neural networks such as large-scale models for AI-generated content. Yifan’s works (first-authored) have been published in top-tier conferences and journals including ICML, ICLR, ICCV, ECCV, DAC, ICCAD, and TODAES.