Machine Learning of Commercial and Residential Load Components in the Northwestern United States. - Huifen Zhou; Zhangshuan Hou; Pavel V. Etingov; Yuan Liu 023 (e-Energy, 2019)

Optimal Future Sub-Transmission Volt-Var Planning Tool to Enable High PV Penetration. - Quan Nguyen; Xinda Ke; Nader Samaan; Jesse Holzer; Marcelo Elizondo; Huifen Zhou; Zhangshuan Hou; Renke Huang; Mallikarjuna Vallem; Bharat Vyakaranam; Malini Ghosal; Yuri V. Makarov (CoRR, 2019)

MH Pose: 3D Human Pose Estimation based on High-quality Heatmap. - Huifen Zhou; Chaoqun Hong; Yong Han; Pengcheng Huang; Yanhui Zhuang (IEEE BigData, 2021)

FESTH: Visual Tracking with Feature Enhancement and Space-time History Frame Networks. - Yanhui Zhuang; Chaoqun Hong; Xuebai Zhang; Chaohui Tang; Huifen Zhou (IEEE BigData, 2021)

Weather and Random Forest-based Load Profiling Approximation Models and Their Transferability across Climate Zones. - Huifen Zhou; Z. Jason Hou; Yuan Liu 023; Pavel V. Etingov (HICSS, 2021)

Predicting Peak Day and Peak Hour of Electricity Demand with Ensemble Machine Learning. - Tao Fu; Huifen Zhou; Xu Ma; Z. Jason Hou; Di Wu 021 (CoRR, 2022)