题目：Privacy and Utility of Geographic Data: Revealing, Evaluating, and Mitigating the Externalities of Geographic Privacy Protection

        林玥博士是芝加哥大学空间数据科学中心（CSDS）的助理教学教授，分别于2015年和2023年在武汉大学与俄亥俄州立大学获得学士和博士学位。她的研究和教学领域涵盖地理计算、地理空间数据科学以及数字隐私与公正。目前，她致力于开发计算方法，以确保在地理空间数据的传播和挖掘中实现隐私、准确性和公平性的平衡。林玥已在GIS、地理以及社会科学领域的期刊（如IJGIS、Annals of American Association of Geographers、TGIS等）和会议（如AutoCarto、GIScience）上发表12篇论文，其中以第一作者发表11篇。她曾荣获2023年制图与地理信息学会博士生奖学金、2023年E. Willard and Ruby S. Miller奖学金、2022年国际制图协会奖学金、2022年Fenburr杰出博士生旅行奖学金，以及多个最佳论文奖项。

报告摘要：Geographic data is increasingly important in fields such as demography, public health, and transportation. However, the use of this data has raised privacy concerns, which have been intensified by recent technological advancements in location tracking and geospatial data analytics. Efforts to address these concerns include restricted access to data, anonymization and aggregation, and data perturbation. But these methods can limit the availability, transparency, and accuracy of geographic data, leading to externalities that affect data usage. This study proposes a methodological framework with three key components to address the externalities of geographic privacy protection: a synthetic data generator, measures to quantify privacy and utility, and spatial optimization models to find optimal solutions for producing and protecting useful geographic data. The proposed framework is validated using U.S. Census data and provides practical strategies for extending geographic privacy protection in real-world applications.

主持人：徐成东 副研

时  间：2023年8月10日（星期四）15:00-17:00

地  点：中国科学院地理科学与资源研究所A0847会议室