Kuang-chih Lee
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Kuang-chih Lee |
Contact Information
Email: kuang-chih AT alibaba-inc DOT com (Work)
leekc307 AT gmail DOT com (Personal)
My Linkedin
Short Bio
Kuang-chih Lee is the head of Marketplace Optimization in AliExpress.com, an Alibaba Group company, the world largest cross-border trading e-commerce platform with billions of dollars in transactions each year. He manages all aspects of research and development for real-time personalized e-commerce marketplace. His research interests span a broad range of topics in search and recommendation systems, online advertising, fraud detection, supply chain management, big data, distributed system, machine learning, data mining, NLP, and computer vision. He has 30+ research papers published in top conferences (CVPR, NIPS, AAAI, CIKM, and KDD) and journals (PAMI, and CVIU), as well as 20+ patents. As reported by Google Scholar, there are 5000+ citations to his publications. Prior to joining Alibaba Inc, Kuang-chih Lee was the principal scientist and research director at Yahoo Inc. Before that he held various research and development leadership positions at Turn Inc, Flashfoto, DigitalPersona, and like.com. like.com was acquired by google in year 2010. Kuang-chih Lee received his CS PhD degree in UIUC in 2005.
李广智任职于阿里巴巴子公司AliExpress.com。 AliExpress.com是一个国际化电商平台，代表着中国品牌出海的主流渠道，国家一带一路的重要承载体。目前担任技术部资深总监，管理市场治理算法以及工程部门。他的团队构建的平台包含了跨国家，多语言，个性化，实时和大数据量的服务。目前开发的算法包括个性化搜索和推荐，点击率以及转换率的预测，商机发掘，动态定价，包裹搭售，以及商品知识图谱建设。这些算法目前支持所有AliExpress的盈收以及广告投放。李广智在过去十四年间已经发表超过三十篇学术论文在各个顶级的国际学术会议(CVPR, NIPS, AAAI, CIKM, and KDD)和期刊(PAMI, and CVIU)，以及超过二十个专利。以这些技术开发的多项产品在市场上多数取得了很大的成功。在管理层面上，他也有相当深厚大型跨国界项目管理经验，以及跨部会的领导及支援能力。过去多年在日常开发管理中，与亚洲，欧洲，及北美各地的销售，研发，测试，和运维团队有着深入交流，同时合作资料分析，并且共同制定跨部门的整合策略，伙伴关系，和中长期战略。对管理多元文化团队和跨国合作有深切领会。在加入阿里巴巴之前，李广智在美国雅虎公司担任广告数据科学总监，负责雅虎广告部门供给和需求两端的服务。所实践的算法支持雅虎三分之一的盈收，约数十亿美元的规模。在此之前，他在许多创业公司担任研发要职。值得一提的是其中一家创业公司like.com于2010年被谷歌以上亿美金价格收购。李广智于2005年在美国伊利诺州香槟分校取得计算机博士学位。
News
We continue hosting a workshop in 2020 KDD conference, 2020 ADKDD in this summer, after a huge success of the previous 2019 ADKDD last summer, and would like to invite every scientist to participate and submit interesting papers to this workshop.
In addition, we start hosting another Deep learning workshop: DLP KDD 2020, and again welcome to participate and submit papers.
KDD Conference is a top data mining and machine learning conference that brings together leaders from academia and industry. Presenting a paper at the workshop would be a great chance to get external exposure for your research.
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