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Welcome To Keqian Li's Website!

About

Keqian Li is a Researcher Scientist in Yahoo Research, New York City, working in the intersection of data mining, natural language processing, big data / database and computer vision. Previously, he has worked at Facebook Newsfeed / Ads, Zenefits Z2, Microsoft Research Redmond and Google Ads under various research and engineering roles. Keqian received his Ph.D. Degree from University of California, Santa Barbara advised by Prof. Xifeng Yan, and his undergraduate from the the Yao Class in Tsinghua Univeristy supervised by Andrew Yao.

Experience

Ph.D. Researcher

Keqian spent 3 years working on his Ph.D. study “Concept level text mining and analysis” under the guidance of Xifeng Yan (Chair), William Y. Wang, Ambuj Singh, where he led the research effort in understanding the fundamental mechanism of concepts and the engineering effort in the design and implementation of large scale scientific literature analysis system, side of the teaching and studying in the beautiful UC Santa Barbara campus. .

Full Stack Engineer

Keqian worked as a full stack software engineer and helped developed various software solutions for Zenefits’ new generation enterprise platform (Z2), encompassing the end to end design - communication - serving - deployment cycle, thanks to the great business and technology leaders, and witnessed its up and down.

Research & Engineering Intern

Keqian worked as an Engineering Intern at Facebook for Facebook Ads, and then as Research Scientist Intern for core newsfeed machine learning, and participated in various aspect of the development in Facebook’s Personalized Advertisement Platform, developing end-to-end full stack solutions.

Research Intern

Keqian Li developed cutting-edge systems for data exploration and management at Microsoft. The internship has led to engineering patents as well as top conference publications.

Ph.D. Intern

• Developed very large scale machine learning solutions for personalized product recom- mendation by levearging Google user’s online activity and product knowledge base.

THU SEM

Keqian doubled majored in economics and received systematic training in Tsinghua School of Economics and management, one of the most prestigious business school in China.

Research

His current research interests spans across the following topics. Collaborations welcome!

[S]ocial Network Analysis & Event Organization
[K]nowledge Graph & Open Information Extraction
[A]utomatic Mining and Analysis of Scientific Literature
[W]eakly Supervised Learning and Large-scale Data Analytics

Selected Papers
[K7, W7, A6] K. Li, Shiyang Li, Semih Yavuz, Hanwen Zha, Yu Su, and Xifeng Yan. "HierCon: Hierarchical Organization of Technical Documents based on Concepts." In Proceedings of the 2019 IEEE International Conference on Data Mining(ICDM'19), 2019. [Best Paper Candidate of ICDM 2019] [pdf]
[slides]
[poster]
[K6, W6, A5] Hanwen Zha, Wenhu Chen, Keqian Li Xifeng Yan. "Mining Algorithm Roadmap in Scientific Publications." In Proceedings of the 25th ACM SIGKDD international conference on Knowledge discovery and data mining(KDD'19) , 2019. [Paper]
[K5, W5, A4] Keqian Li, Hanwen Zha, Yu Su, Xifeng Yan. "Concept Mining via Embedding." In Proceedings of the 2018 IEEE International Conference on Data Mining(ICDM'18), 2018. (acceptance rate: 8.86%) [Paper]
[K4, A3] Keqian Li, Ping Zhang, Honglei Liu, Hanwen Zha, Xifeng Yan. "PoQaa: Text Mining and Knowledge Sharing for Scientific Publications." In Proceedings of the 24th ACM SIGKDD international conference on Knowledge discovery and data mining(KDD'18), 2018. (demo) [Paper] [Posters] [Video]
[K3, A2] Hanwen Zha, Jiaming Shen, Keqian Li, Warren Greiff, Michelle Vanni, Jiawei Han and Xifeng Yan, "FTS: Faceted Taxonomy Construction and Search for Scientific Publications", In Proceedings of the 24th ACM SIGKDD international conference on Knowledge discovery and data mining(KDD'18), 2018. (demo) [System] [Paper]
[K2, W4, A1] Keqian Li, Hanwen Zha, Yu Su, and Xifeng Yan. "Unsupervised Neural Categorization for Scientific Publications." In Proceedings of the 2018 SIAM International Conference on Data Mining(SDM'18), pp. 37-45. Society for Industrial and Applied Mathematics, 2018. [Paper] [Posters] [Supplementary]
[K1, W3] Keqian Li, Yeye He, and Kris Ganjam. Discovering Enterprise Concepts Using Spreadsheet Tables. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'17), pp. 1873-1882. ACM, 2017. [Paper] 
[S1, W2] Keqian Li, Wei Lu, Smriti Baghat, Laks Lakshmanan, Cong Yu. "On Social Event Organization", Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD'14) ACM, New York, NY, USA, 1206-1215. [Paper] [Slides] [Posters] [Citations]
[W1] Wei Lu, Shanshan Chen, Keqian Li, Laks Lakshmanan. "Show Me the Money:Dynamic Revenue-Maximizing Recommendations",  Proceedings of the VLDB Endowment 7.14 (2014) [Paper]

Contact


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New York City
NY 10003


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