I am Haoyi Zhou (周号益), currently an associate professor in the College of Software at Beihang University, also with Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC) in the ACT lab research unit.
My current research interests are in artificial intelligence and machine learning research, with a focus on the application of time-series forecasting, task decision-making, AI safety, AI for Science and other technologies in the industrial field and medical care. We forge the BUAA-SMART group. If you are eager for the similar research vision, please feel free to reach me.
My group has several fully funded PhD positions starting in Fall 2025. Anyone passionate about AI and AI4S research with a focus on SEQUENCES is welcome to apply and reach out. Please send me your CV and a cover letter describing your preferred research topics.
haoyi [at] buaa.edu.cn
Room G503
New Main Building
Beihang University
37 Xueyuan Road
Haidian District
Beijing, 100191
P.R. China
Shenzhen Institute of Computing Sciences (Dec 2021 – June 2022, Shenzhen, China), advisor: Prof. Wenfei Fan
Beihang University (Sep 2015 – June 2021, Beijing, China), advisor: Prof. Jianxin Li
Thesis: Generalizable Sequential Data Modeling Method [Link]
Rutgers University (Aug 2019 – Sep 2020, Newark, US), advisor: Prof. Xiong Hui
Beihang University (Sep 2013 – Aug 2015, Beijing, China), advisor: Prof. Xiao Bai
Thesis: Graphical Matching and Retrieval of Images [Transfered]
Beihang University (Sep 2009 – July 2013, Beijing, China)
Thesis: Numerical Algorithms for Solving Two-point Boundary Problems
Invited Talk: The OmniArch Equation Solving model Based on MindSpore Framework, Ascend Developer Summit, May 11, 2024
Invited Talk: AI for scientific computing: from the sequential architecture, The 7th Global Intelligent Industry Conference, Mar 31, 2024
Invited Talk: Building AI for scientific computing platform, The 6th Xiuhu Conference, Oct 20, 2023
Spotlight Presentation: AutoST: Towards the Universal Modeling of Spatio-temporal Sequences, NeurIPS (online), Dec 7, 2022
Oral Presentation: Triplet Attention: Rethinking the similarity in Transformers, KDD (online), Aug 17, 2021
Invited Talk: Exploring the long sequence time-series forecasting, Nvidia Symposium, June 30, 2021
Invited Talk: 长序列预测向左,计算复杂度向右, Tianjin University (北洋智算论坛), June 6, 2021
Oral Presentation: Informer: Beyond efficient transformer for long sequence time-series forecasting, AAAI (online), Feb 9, 2021
Invited Talk: The Informer in Long Sequence Time-series Forecasting, BAAI (智源预讲会), Dec 9, 2020
Oral Talk: The Generalization Performance in Machine learning, IWCST (Beijing), Nov 12, 2017
Oral Presentation: Improving the Generalization Performance of Multi-class SVM via Angular Regularization, IJCAI (Melbourne), Aug 23, 2017
LibHunt. Top 22 Python time-series Projects (Ranked 4th), June 1, 2021
Topbots. Top Research Papers With Business Applications, April 12, 2021
TowardsDataScience. Adding the Informer Model to Flow Forecast, April 8, 2021
Qita. 時系列データTransformer論文3選を読んでみた, March 23, 2021
Synced & Medium. AAAI 2021 Best Papers Announced, Feb 4, 2021
将门创投. 从“鹦鹉”到“乌鸦”,AI的本质是探索通用智能的可能性, May 7, 2022
文汇报. 有「最好土壤」的上海,集聚AI「最牛尖子生」, July 12, 2021
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解放日报. 数字化时代AI冲浪者,追求产业变革最优解, July 10, 2021
人民日报. 全球AI青年人才论坛:改变世界从改变产业做起, July 9, 2021
中国新闻网. AI青年科学家联盟“A班”朋友圈扩容:中国AI大有可为, July 9, 2021
科技日报. 让数据支撑抗议科学决策——记北航新冠疫情大数据分析团队, June 6, 2020
Thanks to Vasilios Mavroudis for the template! The source code is available at here.