معرفی
Lei Zheng is an Assistant Professor in the Department of Management Science & Information Systems at the College of Management, University of Massachusetts Boston, specializing in the intersection of human and machine collaboration within digital platforms.
Her academic credentials include:
- Ph.D. in Data Science from Stevens Institute of Technology (2023)
- M.S. in Business Intelligence & Analytics from Stevens Institute of Technology (2018)
- B.S. in Economics and Management (Dual degree) from Southwestern University of Finance and Economics, China (2014)
Dr. Zheng's research critically examines how bots and AI algorithms reshape governance and participation in open collaboration ecosystems like Wikipedia. She employs advanced methodologies including machine learning, natural language processing, and graph neural networks to investigate stigmergic coordination, bot adoption dynamics, and human-AI symbiosis. Her work bridges theoretical insights with practical implications for platform design, emphasizing ethical automation and community resilience in algorithmically mediated environments.
Publication trends reveal a strategic evolution from foundational studies on coordination patterns (2018-2019) toward contemporary investigations of large language models and bot governance (2022-2024), with consistent contributions to premier venues like JMIS, ICIS, and CSCW. Recent work demonstrates increasing methodological sophistication through integration of GNNs and LLMs for community analytics.
Her scientific recognition includes:
- Best Paper Honorable Mention Award at ACM CSCW 2019 for “The Roles Bots Play in Wikipedia”
Dr. Zheng teaches graduate courses MSIS 680 (Advanced Machine Learning and AI) and MSIS 685 (Big Data Analytics), translating research insights into technical curriculum. Prior industry experience as a data scientist specializing in ML/NLP informs her applied research perspective. Ongoing projects include submissions to Management Science (reject/resubmit) and MIS Quarterly, reflecting sustained scholarly momentum.
Her research trajectory positions her at the forefront of human-centered AI studies, particularly in designing governance frameworks for hybrid human-machine collectives where algorithmic transparency and community agency remain paramount concerns.
