MS 1


Prof. Dr. Anatoly G. Yagola, Lomonosov Moscow State University, Russia,

Prof. Yanfei Wang, Chinese Academy of Sciences, China,

Topic: Computational methods for inverse problems and applications

In this minisymposium, inverse problems arising from applied sciences, e.g., geophysics, optics, medical science and engineering will be discussed. Related topics include geophysical data processing and imaging, signal/image processing, parameter identification and solution methods. In solving methodology, with different mathematical models, advanced numerical methods for solving these models such as iterative regularization methods, memory saving optimization methods, MPI programming, machine learning and distributed algorithms are discussed.


MS 2


Prof. Isaac Elishakoff, Florida Atlantic Universitys, USA,



MS 3


Prof. Igor Nikolayevich Egorov, General Director, IOSOLabs, Russia,

Topic: Optimization problems for real-life objects


MS 4


Prof. Daniel Lesnic, University of Leeds, United Kinddom,

Topic: Inverse coefficient identification problems

Inverse coefficient identification problems (ICIP) occur whenever the specimen under testing has unknown physical properties. For non-uniform materials, properties such as conductivity, capacity or storativity can be transient, inhomogeneous, anisotropic or nonlinear. The proposed workshop aims to gather experts on solving such problems to present, discuss and review the current state-of-the art on coefficient identification methodologies.


MS 5


Prof. Gyung-Jin Park, Hanyang University, South Korea,



MS 6


Prof. Dr. Roland Potthast, Deutscher Wetterdienst (DWD), Germany; Applied Mathematics, University of Reading, UK,


MS 7


Prof. Daniel Watzenig, Graz University of Technology, Austria,

Topic: Statistical inference and uncertainty quantification

Deterministic inversion consists of applying an approximation to the inverse of the forward map, referred to as regularization, in order to give a single point estimate of the unknown parameters. These regularized solutions can provide qualitatively appealing solutions in many situations but lead to quantitatively inaccurate estimates and predictions. This property is shared by estimators in general, since conditioning on point estimates gives poor predictive densities. In contrast, Bayesian inferential methods present averages over all solutions consistent with the data. This leads to a marked difference in robustness of properties calculated from solutions. These differences occur because the single most likely solution, found by a regularized minimization of misfit to the measured data, is typically unrepresentative of the bulk of feasible solutions particularly in high dimensional nonlinear problems. Bayesian inference applied to inverse problems provides a framework for quantified model fitting. Estimation of unknown quantities of interest is based on the posterior distribution over the unknowns and unobserved data, conditioned on measured data. Uncertainty in recovered parameters arises from measurement noise, measurement sensitivities, model inaccuracy, discretization error and a priori uncertainty; each of these sources may be accounted for and in some cases taken advantage of. Estimates or properties of the unknown parameters can be calculated as summary statistics over the posterior distribution using sampling techniques. Inferential solutions to inverse problems provide substantial advantages over deterministic methods, such as:

(1) a range of parameters that are consistent with measured data can be quantified

(2) data-dependent error estimates can be given

(3) calculation of confidence intervals

(4) inclusion of arbitrary forward maps and treatment of arbitrary error distributions

(5) the parameter space can be discrete, discontinuous, or of variable dimension

(6) treatment of non-stationary measurement data using recursive Bayesian formalism

The proposed minisymposium will address recent advances in computational statistical inference, Bayesian analysis, numerical approximations, and quantification of model and measurement uncertainties in the probabilistic design and robust optimization of today’s engineering problems.


MS 8


Prof. Benny Y.C. Hon, City University of Hong Kong, China,

Topic: Inverse problems related to medical imaging


MS 9


Prof. Zuhair Nashed, University of Central Florida, USA,

Topic: Inverse problems and optimization meet the geosciences


MS 10


Prof. Sergey Kabanikhin, Russian Academy of Sciences, Russia,

Prof. Shuhua Zhang, Tianjin University of Finance and Economics, China,

Topic: Inverse problems in finance and economics

We are going to discuss new and very important class of inverse problems arising in finance and economics, including Solow and Black-Scholes models, stochastic approach, theoretical and numerical analyses.


MS 11


Prof. Lydie Mpinganzima, University of Rwanda, Rwanda,

Topic: Inverse problem for acoustic and electromagnetic waves

This minisymposium concerns recent development in wave modeling and related inverse problems based on acoustic and electromagnetic waves. In these problems, it is assumed that the acoustic or electromagnetic field can be measured on an open part of the domain. Applications range from the determination of acoustic cavities, the determination of the radiation field surrounding a source of radiation, …

The minisymposium aims to bring together experts and young researchers in the field, to give them the opportunity to present their recent work and exchange ideas, and to possibly start new collaborations. .


MS 12


Prof. Haitian Yang , Dalian University of Technology, China,

Prof. Miao Cui, Dalian University of Technology, China,

Prof. Yiqian He, Dalian University of Technology, China,

Topic: Recent findings in inverse heat transfer problems

This MS aims at to promote, exchange and disseminate recent findings on wide-ranging topics of inverse heat transfer problems, and their application in science and engineering, either in the theoretical aspect, or /experimental/numerical aspects. Under the framework of inverse heat transfer problem, subjects of interests include but are not limited to,

(1) Identifications of thermophysical properties, boundary/initial conditions, and geometrical parameters;

(2) Ill-posed problems;

(3) Uncertain forward/invers problems;

(4) Optimization.


MS 13


Prof. Shutian Liu, Dalian University of Technology, China,

Prof. Qi Wang, Dalian University of Technology, China,

Topic: New trends in structural optimization for additive manufacturing

Additive manufacturing (AM) is an emerging technique that provides a great flexibility for the fabrication of complex structures, and gives engineers great freedoms to design novel structures with complex geometries. This has led to a growing interest in AM-oriented structural optimization, especially topology optimization, among the researchers from all over the world. The objective of this symposium is to provide a forum for researchers from academia, industry and national labs to present, discuss and exchange the latest development in theoretical, computational, and experimental studies on structure optimization for additive manufacturing. Both fundamental research and practical applications are welcome. Topics invited for this symposium include but are not limited to,

(1) Topology optimization for AM;

(2) AM-oriented lattice material or meta-material design;

(3) Optimization design subjected to manufacturing constraints;

(4) Material property prediction considering size effect;

(5) Robust/Reliability design considering material and manufacturing uncertainties;

(6) Post-treatment of topology optimization results for AM;

(7) Practical applications of AM-oriented structural design.


MS 14


Prof. Bo Han , Harbin Institute of Technology, China,

A/prof. Yong Chen , Harbin Institute of Technology, China,

Topic: Accelerated iterative regularization methods and applications

This minisymposium will discuss some fast iterative regularization methods obtained with acceleration techniques, such as Nesterov acceleration, proximal algorithm, sequential subspace optimization method, Kaczmarz method, et al., in Hilbert or Banach spaces. We seek to bring together researchers to present and discuss their latest results in analysis and numerical simulations of regularization methods for ill-posed problems and their applications in full waveform inversion in seismic, diffuse optical tomography, electrical impedance tomography, and so on.


MS 15


Prof. Gongsheng Li, Shandong University of Technology, China,

A/prof. Dr. Zhiyuan Li, Shandong University of Technology, China,

Topic: Inverse problems in nonlocal models and related topics

In recent years, partial differential equations with fractional derivatives have gathered increasing popularity among multidisciplinary researchers, owing to their novel features in mathematics and potential feasibility in applied sciences. Especially, many related inverse problems possess practical significance in some environmental issues of common concern. This minisymposium will bring together researchers on inverse problems for fractional-order partial differential equations to share new ideas and present the latest progresses on this topic and related areas, including inverse source problems, coefficient inverse problems, etc.. Also, this minisymposium aims at further strengthening the collaboration in the mathematical and numerical analyses of relevant problems.


MS 16


Prof. Zhihai Xiang, Tsinghua University, China,

Prof. Xiaoming Zhou, Beijing Institute of Technology, China,

Prof. Yiqian He, Dalian University of Technology, China,

Topic: Novel methods in the design of functional materials and structures

Design of functional materials and structures is a typical inverse problem. In recent years, many novel ideas emerge in this field, such as meta-materials, super lubrication, smart structures with optimized sensor placement, etc. We welcome relevant researchers, either in the theoretical, experimental or numerical aspects, to participate this mini-symposium that will be richly rewarding. The topics of interest for this mini-symposium include, but not limited to,

(1) Inverse design of meta-materials and meta-structures for wave controlling;

(2) Identification of effective parameters for heterogeneous materials;

(3) Novel damping or low friction materials;

(4) Smart structures with embedded actuators and sensors.


MS 17


Prof. Chao Jiang , Hunan University, China,

Dr. Bingyu Ni, Hunan University, China,

Topic: Structural uncertainty analysis and reliability design

Uncertainties have been acknowledged as being extremely important in a wide variety of areas relating to risk assessment and reliability design of structures. To handle with the aleatory and epistemic uncertainties that frequently encountered in practical engineering, a series of effective uncertainty quantification models and reliability analysis approaches have been proposed and developed. Among the various research topics in structural uncertainty analysis and reliability design, this mini-symposium aims to provide a forum for in-depth discussion of key issues including uncertainty quantification models, uncertainty propagation analysis methods, structural reliability analysis methods, reliability-based design optimization, etc. Topics of interests include but are not limited to the following aspects:

(1) Interval analysis;

(2) Imprecise probability methods;

(3) Time-variant/dynamic reliability analysis;

(4) Interval finite element methods;

(5) Reliability-based design optimization;

(6) Interval uncertain optimization;

(7) Advanced Monte Carlo simulation methods;

(8) Reliability analysis of engineering structures.


MS 18


Prof. Hu Wang, Hunan University, China,

Prof. Haobo Qiu, Huazhong University of Science and Technology, China,

Prof. Jian Zhang, Jiangsu University, China,

Topic: Data-driven surrogate modeling techniques for inverse and other engineering problems

The surrogate modeling technique is an important tool for parameter inverse methodology. However, with the ever-increasing complexity of inverse problems, the surrogate modeling technique is difficult to handle some critical issues, such as curse of dimensionality, uncertainties, massive sampling data, etc. Therefore, in this mini-symposium, some recently proposed novel strategies might be employed for inverse problems. The themes involve but not limited to,

(1) Surrogate modeling theory and methodology;

(2) Surrogate-based optimization;

(3) Surrogate-assisted evolutionary optimization;

(4) Machine learning methods in surrogate modeling;

(5) Uncertainty Quantification and Uncertainty Propagation in Surrogate modeling;

(6) Data-driven (Numerical simulation-based) design and optimization;

(7) Design of Experiments for surrogate modeling;

(8) Surrogate model assessment;

(9) Surrogate modeling for large data set and high dimensional problems;

(10) Surrogate modeling and surrogate-based optimization in practical engineering applications.


MS 19


Prof. Tommy H.T. Chan, Queensland University of Technology, Australia,

Dr. Zhen Chen, North China University of Water Resources and Electric Power, China,

A/Prof. Jie Liu, Hunan University, China,

A/Prof. Baijie Qiao, Xi’an Jiaotong University, China,

Topic: Recent regularization methods for dynamic load identification

Load identification as the second kind of inverse problem in structural dynamics, plays an important role in structural health monitoring, optimization design, transfer path analysis, etc. Recently, various regularization methods such as Tikhonov regularization, function approximation, sparse regularization, compressed sensing, Bayesian and Kalman filters are widely developed to overcome the ill-posedness of load identification in the time or frequency domain. The topics of interest for this mini-symposium include, but not limited to,

(1) Impact force identification for structural health monitoring;

(2) Moving force identification for beam/bridge structure;

(3) Distributed load identification in space-time domain;

(4) Dynamic load identification with uncertainty quantification.


MS 20


A/prof. Yingchun Bai, Beijing Institute of Technology, China,

A/prof. Huiming Ning, Chongqing University, China,

A/prof. Fei Lei, Hunan University, China,

Topic: Automotive lightweight design

The topics of interest for this mini-symposium include, but not limited to,

(1) Additive manufacturing driven innovative design;

(2) Composite structural analysis and optimization;

(3) Lightweight joining methods and applications;

(4) Multi-mateiral body structural techniques;

(5) EVs and HEVs integration and optimization.


MS 21


A/prof. Qian Zhang, Tianjin University, China,

Topic: Detection data intelligent analysis and parameter identification

Submissions related on methods or applications of detection data analysis are welcomed, such as but not limited to:

(1) Intelligent analysis of engineering detection data;

(2) Mechanical modeling of experimental data;

(3) Parameters identification of detection data.


(Relevant information and more minisymposium proposals will be updated soon)

Important Dates


Previous IPDO Symposia