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Dong DING is an Assistant Professor in the Department of Computer Science and Engineering at Michigan State University (MSU). He leads the Trustworthy AI and Causal Machine Learning Lab (TruCause Lab) at MSU. His research interests lie at the intersection of machine learning, artificial intelligence, and their applications, with a strong focus on Trustworthy AI. This includes areas like adversarial robustness, algorithmic fairness, interpretability, causality in machine learning, and privacy-preserving AI. Dr. Ding aims to develop machine learning models that are not only accurate but also reliable, fair, transparent, and secure, particularly for critical applications in computer vision, natural language processing, and healthcare. He is dedicated to advancing AI systems that humans can trust and effectively collaborate with.
Dong DING's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Recipient of the prestigious National Science Foundation (NSF) CAREER Award in 2023 for his research on 'CAREER: Towards Trustworthy Graph Neural Networks with Graph Counterfactual Explanations'.
Received an Amazon Research Award (Fall 2021 cycle) for his innovative work in machine learning, contributing to the advancement of AI technologies.
Authored and co-authored numerous research papers published in leading artificial intelligence and machine learning conferences and journals, including NeurIPS, ICML, ICLR, CVPR, ECCV, KDD, and AAAI, making significant contributions to the field.
Founder and director of the Trustworthy AI and Causal Machine Learning Lab (TruCause Lab) at Michigan State University, mentoring students and spearheading research in cutting-edge AI.
Frequently invited to give talks at academic and industry forums, and actively serves the research community as a reviewer, program committee member, and organizer for major AI conferences and workshops.
Singapore Management University - Year 2016
Beihang University - Year 2010
Xi'an Gaoxin No.1 High School - Year 2007
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