Papers
2
Total Citations
26
H-Index
2
About
Weihua He is a rising researcher at the intersection of artificial intelligence and biomedical engineering, with key contributions in human-computer interaction and single-cell biophysical characterization. His work spans two distinct but innovative domains: generative AI for human motion synthesis and microfluidic cytometry for cellular analysis. In his highly cited 2022 paper, "Audio-Driven Stylized Gesture Generation with Flow-Based Model," He pioneered a method to generate realistic, stylized co-speech gestures from audio input using normalizing flows, achieving 23 citations and opening new avenues for virtual avatars and assistive technologies. Complementing this, his 2023 work in *Small* introduced an impedance-based multimodal electrical-mechanical flow cytometry framework that enables five-dimensional intrinsic characterization of single cells—measuring electrical, mechanical, and biophysical properties simultaneously. This "intelligent robot" approach, with 3 citations to date, promises label-free, high-throughput cell analysis for disease diagnostics. He’s ability to bridge deep learning with microfluidics demonstrates a rare versatility, positioning him as a promising interdisciplinary innovator whose work impacts both animation technology and biomedical sensing.
Research Focus
Key Achievements
Top Papers
- 1Audio-Driven Stylized Gesture Generation with Flow-Based Model23 citations · 2022
- 2