Shakeel Gavioli-Akilagun |
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Hello! Welcome to Shakeel's academic website. I am a Fellow in the Department of Decision Analytics and Operations at City University Hong Kong, and a visiting Fellow by courtesy in the Department of Statistics at the London School of Economics. Previously I was a PhD student at the London School of Economics, where I was supervised by Professor Piotr Fryzlewicz. Some of my research interests include:
A recent version of my CV can be found here.
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Optimal Online Change Detection via Random Fourier Features. F. Kalinke† and S. Gavioli-Akilagun†. NeurIPS (forthcoming), 2025 [arXiv; software; numerical examples]
AdaDetectGPT: Adaptive Detection of LLM-Generated Text with Statistical Guarantees. H. Zhou, J. Zhu, P. Su, K. Ye, Y. Yang, S. Gavioli-Akilagun, and C. Shi. NeurIPS (forthcoming), 2025 [software]
Fast and Optimal Inference for Change Points in Piecewise Polynomials via Differencing. S. Gavioli-Akilagun and P. Fryzlewicz. Electronic Journal of Statistics, 2025 [open access link; software; numerical examples]
Invited discussion of "Automatic Change-Point Detection in Time Series via Deep Learning" by Li, Fearnhead, Fryzlewicz, and Wang. S. Gavioli-Akilagun. Journal of the Royal Statistical Society Series B, 2023 [discussion; slides; original paper]
(The symbol † indicates equal contribution.) |
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Causal Change Point Detection using Kernels. F. Quinzan and S. Gavioli-Akilagun Work in progress, 2025+
Detecting Changes in Production Frontiers. S. Gavioli-Akilagun, Y. Chen, and F. Ziegelmann. Work in progress, 2024+
Online Detection of Changes in Mean Reverting Processes with Local Cointergration. S. Gavioli-Akilagun, B. Dou, S. Tiwari, and Q. Yao. Work in progress, 2024+
Robust Inference for Change Points in Piecewise Polynomials using Confidence Sets. S. Gavioli-Akilagun and P. Fryzlewicz. Manuscript in preparation, 2023+
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