基本信息
浏览量:259
职业迁徙
个人简介
Dr. Lingfei Wu is an Engineering Manager in the Content and Knowledge Graph Group at Pinterest, where they are building the next generation Knowledge Graph to empower Pinterest recommendation/research systems across all major surfaces including Homefeed, Search, Ads, and etc. He earned his Ph.D. degree in computer science from the College of William and Mary in 2016. Previously, he was a Principal Scientist at JD.COM Silicon Valley Research Center, leading a team of 30+ machine learning/natural language processing scientists and software engineers to build intelligent e-commerce personalization systems. Before that, he was a research staff member at IBM Thomas J. Watson Research Center and led a 10+ research scientist team for developing novel Graph Neural Networks methods and systems, which leads to the #1 AI Challenge Project in IBM Research and multiple IBM Awards including three-time Outstanding Technical Achievement Award. He has published one book (in GNNs) and more than 100 top-ranked conference and journal papers, and is a co-inventor of more than 40 filed US patents. Because of the high commercial value of his patents, he received eight invention achievement awards and was appointed as IBM Master Inventors, class of 2020. He was the recipients of the Best Paper Award and Best Student Paper Award of several conferences such as IEEE ICC’19, AAAI workshop on DLGMA’20 and KDD workshop on DLG’19. His research has been featured in numerous media outlets, including NatureNews, YahooNews, AP News, PR Newswire, The Time Weekly, Venturebeat, MIT News, IBM Research News, and SIAM News. He has served as Industry and Government Program Co-Chairs of IEEE BigData'22, Sponsorship Co-Chairs of KDD'22 and Associate Conference Co-Chairs of AAAI'21 and is the founding co-chairs for several workshops such as Deep Learning on Graphs (with AAAI’20-22 and KDD’19-22). He has also served as Associate Editor for IEEE Transactions on Neural Networks and Learning Systems and ACM Transactions on Knowledge Discovery from Data.
研究兴趣
论文共 56 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
CoRR (2023)
arXiv (Cornell University) (2021)
引用1浏览0引用
1
0
加载更多
作者统计
#Papers: 56
#Citation: 1175
H-Index: 19
G-Index: 34
Sociability: 5
Diversity: 3
Activity: 4
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn