Wei Ding is Distinguished Professor of Computer Science and Executive Director of the Paul English Applied AI Institute at the University of Massachusetts Boston. For nearly two decades, Professor Ding has strengthened ICDM through leadership in student development, sponsorship, workshops, conference operations, and technical programs, culminating in her service as Program Committee Co-Chair of ICDM 2025. She has served as Student Travel Awards Committee Chair, Sponsorship Chair, Workshops Chair, PhD Forum Co-Chair, Area Chair, Finance Chair, and Tutorial Chair, alongside continuous Program Committee service since 2011. These contributions have strengthened conference operations, preserved institutional knowledge, and expanded opportunities for emerging researchers.
Her broader leadership includes service as Program Committee Co-Chair of IEEE Big Data 2024, Short Paper Program Committee Co-Chair of ACM CIKM 2023, General Co-Chair of DASFAA 2025, and Blue Sky Track Chair of SIAM SDM 2025. Through her role as General Co-Chair of ACM BCB 2027 and through ACM KDD's AI for Science & Science for AI Special Day (2024) and Health Day (2025), she has connected data mining with bioinformatics, healthcare, and scientific discovery.
Her associate editorships at ACM Transactions on Knowledge Discovery from Data, ACM Transactions on Intelligent Systems and Technology, IEEE Transactions on Knowledge and Data Engineering, Knowledge and Information Systems, and ACM Computing Surveys have reinforced rigorous peer review across data mining and AI.
As a Program Director in the National Science Foundation's Division of Information and Intelligent Systems (2019-2023), she supported interdisciplinary research and early-career investigators, earning the 2022 NSF CISE Director's Award. As Executive Director of the Paul English Applied AI Institute at the University of Massachusetts Boston, she strengthens the institutional foundations and talent pipeline that sustain progress in data mining and AI. Her leadership broadens participation and builds partnerships across academia, industry, and communities, preparing the next generation to advance research and translate innovation into societal benefit.
Professor Ding's sustained leadership strengthens the institutions, partnerships, and talent that advance data mining and prepare its next generation to lead.