Professor Idris Eckley is a Distinguished Professor of Statistics at Lancaster University's School of Mathematical Sciences. He holds affiliations with several research centers including the Data Science Institute (DSI), STOR-i Centre for Doctoral Training, and Energy Lancaster. His work focuses on developing advanced statistical methodologies with applications across various domains. Professor Eckley's primary research interests include: Wavelets and multiscale methods Time series analysis and forecasting methods Changepoint detection algorithms Statistical applications in business and finance Statistical computing for large datasets His recent publications demonstrate a strong focus on developing efficient online changepoint detection methods, particularly for time series data. His work bridges theoretical statistics with practical applications in areas ranging from economic forecasting to astrophysics. Much of his recent research involves collaborative work with colleagues at Lancaster and other institutions, developing computational methods that address real-world data challenges while maintaining statistical rigor. Professor Eckley has received recognition as a Fellow of the Learned Society of Wales (FLSW). His research has been supported by grants including the STORi project funded by Elsevier Limited with £30,000. Professor Eckley actively supervises postgraduate research, currently guiding 8 PhD students including Dylan Bahia, Theo Crookes, Yuntang Fan, Benjamin Lowery, Kes Ward, Tessa Wilkie, Ziyang Yang, and Yiyin Zhang. His research is closely connected with the Changepoints and Time Series research group and the Foundations team within the Data Science Institute, where he contributes to both theoretical developments and practical applications of statistical methodology.