Wenhua Cheng is a Software Engineer at Intel, with a strong background in large language model (LLM) quantization, model compression, and computer vision. Previously, he worked at Alibaba Cloud as a software engineer and at Intel Labs as a researcher. Wenhua holds a Master’s degree from Zhejiang University and a Bachelor’s degree from Nanjing University of Science and Technology. Wenhua’s expertise spans two main domains:

LLM Compression: As the first author, he has contributed to methods such as SignRound and SignRoundV2, signed gradient descent-based rounding optimizations for LLM quantization, and TEQ (Trainable Equivalent Transformation).

Computer Vision: As a co-first author, he won two championships in the DawnBench competition, outperforming teams from Huawei, Google, and others. As the first author, he also ranked 4th and 6th in two tracks of the 2017 ICDAR Scene Text Detection Competition.

Wenhua has filed 21 patents, 11 of which have been granted. Over the past four years, he has contributed to 300+ merged PRs.