Dr. Kaicheng Yu, born in 1993 in Yantai, Shandong, earned a Bachelor of Engineering degree with First Class Honors from the University of Hong Kong in 2016 and a Doctorate in Computational and Communication Sciences from the Swiss Federal Institute of Technology in Lausanne (EPFL) in 2021. In 2019, he was one of only four individuals in Europe to be awarded the Qualcomm Innovation Fund. In 2021, he joined the Damo Academy's Autonomous Driving Laboratory under the Alibaba Talent Program to engage in perception algorithm research. The following year, he was selected for the Hangzhou City Overseas High-Level Talent Program. In August 2023, he joined Westlake University as an Assistant Professor and Ph.D. advisor, where he also established the Autonomous Intelligence Lab as the Principal Investigator (PI).

Prior to returning to China, Dr. Kaicheng Yu held research and development roles at Intel's Intelligent Systems Laboratory and Abacus.AI. He led three research projects and was a core member involved in an additional three, with total funding exceeding 7 million RMB. He also co-advised approximately ten undergraduate, master's, and doctoral students from world-renowned universities.

Dr. Kaicheng Yu has published more than ten papers as the first or corresponding author in A-class international journals and conferences recognized by the China Computer Federation. The commercial value derived from his research reaches 3.5 billion RMB. His seminal work has identified the core issues causing poor algorithmic sensitivity and robustness in the field of automated machine learning, which have been cited as one of the three major problems in the field by top workshops on neural architecture search. He subsequently proposed a ranking-guided new algorithm that greatly improves the robustness of various automated machine learning algorithms, pioneering a new approach to resolving such issues. The achievements of this project were honored with the Qualcomm Innovation Fund.

After returning to China, Dr. Kaicheng Yu led a team at Alibaba to translate the research findings into practical applications in the autonomous driving business. He constructed a data-closed-loop true value production system. His series of work, including BEVFusion, BEVHeight, BEVControl, and FusionAD, has achieved significant results in the multi-modal autonomous driving domain. He introduced a simple, universally applicable, and robust fusion perception framework that significantly enhanced the robustness of autonomous driving solutions and has been integrated into algorithmic solutions by multiple companies in the industry.

1. Kaicheng Yu*, Christian Sciuto*†, Martin Jaggi, Claudiu Musat, Mathieu Salzmann, “Evaluating the search phase of neural architecture search”, ICLR, 2020

2. Kaicheng Yu*, Rene Ranftl, Mathieu Salzmann, “Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search”, CVPR, 2021

3. Kaicheng Yu*, Rene Ranftl, Mathieu Salzmann., “An Analysis of Super-Net Heuristics in Weight-Sharing NAS”, Trans. Pattern Analysis and Machine Intelligence, 2021, 44-11, 8110 - 8124.

4. Tingting Liang*†, Hongwei Xie*, Kaicheng Yu*, Zhongyu Xia, Zhiwei Lin, Yongtao Wang, Tao Tang, Bing Wang, Zhi Tang., “BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework”,  NeurIPS, 2022, [Supervised student project]

5. Lei Yang†, Kaicheng Yu, Tao Tang, Jun Li, Kun Yuan, Li Wang, Xinyu Zhang, Peng Chen, “BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection”, CVPR, 2023, [Supervised student project]

6. Kaicheng Yu, Tang Tao†, Hongwei Xie, Zhiwei Lin, Zhongwei Wu, Zhongyu Xia, Tingting Liang, Haiyang Sun, Jiong Deng, Dayang Hao, Yongtao Wang, Xiaodan Liang, Bing Wang， “Benchmarking the Robustness of LiDAR‑Camera Fusion for 3D Object Detection”, CVPR Workshop 2023

7. Tao Tang†, Longfei Gao, Guangrun Wang, Peng Chen, Dayang Hao, Xiaodan Liang, Mathieu Salzmann, Kaicheng Yu, LiDAR‑NeRF: Novel LiDAR View Synthesis via Neural Radiance Fields, in submission.

8. Kaicheng Yu*, Hongwei Xie, Jianhua Xu, Haoyue Zhang, Chunhuan Lin, Haiyang Sun, Liang Shao, Hang Zheng, Peng Chen, Chao Huang, Dayang Hao, “AutoML System V1”, Alibaba DAMO Academy, 2023. [Product]

Email: autolab.hr@westlake.edu.cn

We have various open academic positions, including but not limited to PhD students, postdocs, research assistants, 6 month research internship, etc.

Prof.Yu‘s research interests cover broader areas of computer vision , machine learning, and building a multi‑modality autonomous intelligent system. We commit to utilizing the cutting-edge large models and multi‑modality technologies to eventually achieve progresses from automatic machine learning to autonomous intelligence. Specifically, our research focus includes:

1. Broader topics of automatic machine learning;

2. Applied research on end-to-end autonomous driving, visual perception;

3. Build a future data-in-the-loop autonomous intelligent AI system;

4. Explore the interdisciplinary future research possibility of AI and Science, preferably using AI to help knowledge discovery.