Functional data with complex structures are emerging in a broad range of scientific areas, such as time-course proteomic data, longitudinal genomic data, bio-signals monitoring using wearables, and functional magnetic resonance (fMRI) data. There is a growing need in revamping contemporary functional data analysis, as well as proposing effective frameworks to study statistical issues of estimation, prediction, and inferences. Several key problems for functional data plan to be studied in this session, such as the study of the inter-dependency among the random functions, and general regression models with distributional data. Besides, this session plans to cover some practically relevant problems such as the investigation of the brain functional connectivity using fMRI data, which reveals intrinsic architecture of the brain and evidences associated with cognitive and behavioral functions. 

This session is expected to attract audience from many disciplines such as neuroscience, healthcare research, genetics, and machine learning. The speakers of this session also represent a diverse level of academic ranks, including both junior and senior researchers of their careers. 

--Format of the session: session with four speakers (no discussants) 

--List of invited speakers: 

-Speaker 1: Hans-Georg Müller, Department of Statistics, University of California at Davis, email: hgmueller@ucdavis.edu

-Speaker 2: Bing Li, Department of Statistics, Pennsylvania State University, email: bxl9@psu.edu 

-Speaker 3: Victor Panaretos, Institute of Mathematics, EPFL, email: victor.panateros@epfl.ch

-Speaker 4: Kuang-Yao Lee, Department of Statistical Science, Temple University, email: kuang-yao.lee@temple.edu 

Organiser: Dr Kuang-Yao Lee 

Chair: Dr Kuang-Yao Lee 

Speaker: Dr Hans-Georg Müller

Speaker: Victor Panaretos 

Speaker: Bing Li 

Speaker: Kuang-Yao Lee