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职业迁徙
个人简介
My research seeks to unify techniques from theoretical data management, causal inference and machine learning to develop a new generation of decision-support systems that help people with heterogeneous background to interpret data. My ongoing work in causal relational learning aims to develop the necessary conceptual foundations to make causal inference from complex relational data. Further, my research in the area of responsible data science develops needed foundations for ensuring fairness and accountability in the era of data-driven decisions. I am a recipient of a Postdoc Research Award at Univeirsty of Washington, a Best Demonstration Paper Award at VLDB 2018, a Best Paper Award at SIGMOD 2019 and a Reserach Highlight Award at SIGMOD 2020.
研究兴趣
论文共 46 篇作者统计合作学者相似作者
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arxiv(2024)
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arxiv(2024)
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PROCEEDINGS OF THE 28TH ACM SYMPOSIUM ON ACCESS CONTROL MODELS AND TECHNOLOGIES, SACMAT 2023pp.145-155, (2023)
SIGMOD/PODS '23: Companion of the 2023 International Conference on Management of Datapp.171-174, (2023)
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ICDEpp.3663-3666, (2023)
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Proceedings of the 2022 International Conference on Management of Datapp.3209-3212, (2022)
Reasoning Webpp.105-131, (2022)
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