Mobirise

Lingfei Wu

A computational social scientist with research interests in the future of research, education, and employment in an AI economy driven by knowledge production. 






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Selected Publication

Mobirise

Small Teams Disrupt

Large teams develop and small teams disrupt science and technology.

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Soft Skills Matter

Skill discrepancies between research, education, and jobs reveal the critical need to supply soft skills for the data economy.

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Virtual Life Accelerates

Scaling behaviours in the growth of networked systems and their geometric origins.

Schedule

2019/06/10-12          
            

Science of Science Conference in Beijing

Jointly host with James Evans (U of Chicago) and Jie Tang (Tsinghua U) at Beijing

2019/06/7-12            

Complex Networks, Geometry, and Machine Learning Workshop

Jointly host with Yi-Zhuang You (UCSB), Pan Zhang (CAS), Jiang-Zhang (BNU) at Beijing

2019/05/27-31         

Machine Learning in Network Science Satellite, NetSci19 

Jointly host with Nicola Perra (ISI), Márton Karsai (ENS Lyon), Bruno Ribeiro (Purdue)
and Ciro Cattuto (ISI) at Burlington, Vermont

2019/04/11-12          

University of Pittsburgh

Invited Talks in School of Computing and Information by Bruce R. Childers

2019/04/3-5             

University of California, Davis

Invited Talks in Department of Communication and Data Science Initiative by Cuihua (Cindy) Shen

Research Projects

 
500 Million Workers LinkedIn 

How to Get a Better Job

To prepare people for workforce transitions in the AI economy, I analyze the skills and knowledge of 500 million LinkedIn users, predict salary from skills using GNN (graph neural network), and compute the optimal marginal skills to enhance for job switching.


13 Million Innovators 
Web of Science

When to Reset Your Innovation Clock

To understand why innovation slows down over time for scientists and inventors and what are the critical events that may reset the innovation clock, I identify 10 million scientists from Web of Science and 3 million inventors from United States Patents and analyze the effect of institutional and geographic mobility on innovation.

Book: Data Mining in Social Science

My ebook that covers all stages throughout the lifecycle of typical data science projects, including data collection, analysis, and visualization. For each stage, several examples with Python codes are provided.

Syllabus: How Society Thinks: Social Networks as Neural Networks

My syllabus designed to address this question: if we can use artificial networks to learn, then does the evolution of real-world social networks also present evidence of learning, and if yes, what are they learning? This syllabus connects literature across fields including machine learning, social science, and statistical physics around this central question.

Institutions

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School of Computing and Information

2016 - present

Assitant Professor

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The Department of Sociology, Knowledge Lab

2018 - present

Postdoctoral Researcher

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School of Journalism and Communication

2018 - present

Adjunct Professor

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Tencent Research Institute

Since 2019 Fall

Consultant

Previous Talks and Visiting

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Team Algebra 

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Word Embedding

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Social Network
Computation

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Clickstream dynamics

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Team Innovation

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Social Network
Computation

Address

The University of Chicago
Department of Sociology
1126 East 59th Street
Chicago, IL 60637

Contacts

wlf850927@gmail.com