Conference: The Past, Present, and Future of Statistics in the Era of AI
- Institution
- George Washington University, DC
- Principal investigator
- Tatiyana V Apanasovich
- Funding
- $18K
- Duration
- 2025–2026
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Abstract
The Department of Statistics at George Washington University will host the conference “The Past, Present, and Future of Statistics in the Era of AI” from May 8-10, 2025, in Washington, DC. This event will explore the evolving relationship between statistics and artificial intelligence (AI), examining its growing impact on scientific research, education, and society. The conference will explore AI’s influence on statistical research and its role in shaping the future of data-driven decision-making. The program will feature technical sessions, short courses, panel discussions, and poster presentations, providing a platform for knowledge exchange and interdisciplinary collaboration. The event will also include plenary talks from leading experts in the field, offering insights into cutting-edge developments and future directions. Additionally, we have invited practitioners from both academia and industry to attend and participate in panel discussions, ensuring a broad range of perspectives. A key priority of the conference is to promote the active participation of junior scholars, including as speakers and presenters, providing them with opportunities to engage with experts and showcase their work. The conference contributes to statistical science by facilitating dialogues among experts, inspiring new research directions, and promoting advancements in statistical methodologies and AI applications. In particular, discussions will focus on scalable data analysis, model interpretability, causal inference, and responsible AI. Key topics include uncertainty quantification through probabilistic modeling, Bayesian methods for AI-driven decision-making, and fairness and bias correction in machine learning. The program will also address reinforcement learning for dynamic treatment regimes and privacy-preserving statistical methods for large-scale datasets. The conference will serve as a hub for knowledge sharing, highlighting the evolving role of AI in statistical research and its broader implications for innovation and societal progress. More details about the event, including registration and program updates, can be found at https://statistics.columbian.gwu.edu/GW-STAT-90. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- Tatiyana V ApanasovichPI
- Xiaoke Zhang
- Subrata Kundu
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