Workshop on 

Date

16 - 20 March 2026

Place

Room D302,  The Institute of Statistical Mathematics, Tokyo, Japan

Aims and Scope

The inference of target properties from observational data is a fundamental paradigm underlying all branches of science. When data are sparse, indirect, or contaminated by noise, the reconstruction of underlying physical or structural parameters inevitably leads to inverse problems. The rapid advancement of computational techniques in data science, including signal processing, optimization theory, statistics, and machine learning, has updated the methods for solving such problems. For instance, the imaging of black holes with the Event Horizon Telescope and the microscopy techniques such as cryo-electron microscopy (cryo-EM) and Ptychography would have been difficult to achieve without the recent progress in data science. This workshop focuses on inverse problems in sensing technologies and data-driven methodologies, aiming to explore and discuss the recent developments in these approaches and their applications.

Invited Speakers

Natsuki Akaishi, Keidai Arai, Kohei Yatabe, Tokyo University of Agriculture and Technology, Japan

Phase retrieval algorithms for X-ray nanoimaging (presentation slides)

Kazunori Akiyama, Heriot-Watt University, UK

Frontier of Black Hole Imaging: Computational Algorithms Driving the Scientific Breakthroughs

Stefan Catheline, INSERM, Lyon, France (presentation slides)

Gravitational lense effect in a fabric membrane

Eric Chassande-Mottin, CNRS and APC, Paris, France

Lessons from a decade of gravitational-wave astronomy and advances in polarimetric sensing (presentation slides)

Colin Fox, Otago University, New Zealand

Posterior inference in large-scale inverse problems by MCMC, and not MCMC (presentation slides)

Ryoichi Horisaki, The University of Tokyo, Japan

Computational imaging with randomness (presentation slides)

Contributed Speakers

Grégoire Doat, Université Grenoble-Alpes, Gipsa-lab, pôle GAIA, France

Geometric phases to infer polarization fluctuations of gravitational waves (presentation slides)

Philippe Flores, CNRS - GIPSA-lab, France

Structured low-rank methods for gravitational wave ringdown data analysis (presentation slides)

Ammar Mian, Université Savoie Mont-Blanc, France

Robust sparse convolution coding for radar applications (presentation slides)

Kazumi Murata, Kanagawa Institute of Technology, Japan

Statistical Validation of Structures in Astronomical and Medical Image Reconstruction via Hypothesis Testing (presentation slides)

Shota Takahashi, The University of Tokyo, Japan

Majorization-Minimization Bregman Proximal Gradient Algorithms for NMF with the Kullback–Leibler Divergence (presentation slides)

Akio Taniguchi, Kitami Institute of Technology, Japan

Decomposition of Signal and Noise toward Deep Imaging Spectroscopy with Submillimeter Single-dish Telescopes (presentation slides)

Hiroki Yoneda, Kyoto University, Japan

Image Reconstruction Framework for MeV Gamma-ray Astronom: From INTEGRAL/SPI to COSI (presentation slides)

Application for Presentation

We accept applications for oral presentations. Please note that the presentation must be provided on-site once it is accepted. Send your title and abstract through this link. Due date is 15 Dec 2025.

Participation Registration

Here is the link to the registration form for both on-site and online participation. The deadline for on-site participation is 31 January 2026 (subject to venue capacity). The deadline for online participation is 28 February 2026.

Important Dates

19 Oct 2025: website open

15 Dec 2025: due date of application for a talk

31 Dec 2025: decision on acceptance

10 Jan 2026: registration open

31 Jan 2026: deadline: registration for on-site participants (up to the venue capacity)

28 Feb 2026: deadline: registration for online participants

Organizing Committee

Shiro Ikeda, The Insitute of Statistical Mathematics

Nicolas Le Bihan, CNRS, GIPSA-Lab

Sponsors

JSPS KAKENHI  (International Leading Research ) 23K20035

Research Center for Statistical Machine Learning, The Institute of Statistical Mathematics

CNRS MITI interdisciplinary research program 

ANR, French National Research agency under the RICOCHET program