16th IWCFTA

1.Prof. Marian Wiercigroch, University of Aberdeen, UK [nonlinear dynamics]

Personal Details:
Professor Marian Wiercigroch educated in Poland, US and UK holds a prestigious Sixth Century Chair in Applied Dynamics and he is a founding director of the Centre for Applied Dynamics Research at the University of Aberdeen.
His area of research is theoretical and experimental nonlinear dynamics, which he applies to various engineering problems. Wiercigroch has published extensively (over 500 journal and conference papers) and sits on a dozen editorial boards of peer review journals. He is a frequent keynote and plenary speaker at major international conferences and the Editor-In-Chief of International Journal of Mechanical Sciences, a premier journal in mechanics and mechanical engineering.
He is the inventor of new patented drilling technology called Resonance Enhanced Drilling and the Founder and Chief Technology Officer of a spinoff company iVDynamics Ltd. He has established in Aberdeen unique experimental laboratories allowing to investigate complex nonlinear dynamic interactions in mechanical systems with the focus on energy generation.
He has received many awards and distinctions including a Senior Fulbright Scholarship (1994), Fellowship of the Royal Society of Edinburgh (2009), DSc honoris causa from the Lodz University of Technology (2013), Distinguished Professorships at the Perm National Research Polytechnic University (2017), Balseiro Institute (2018) and Yanshan University (2021). Marian is a Scottish Champion of Knowledge Exchange (2020) and he served as a panelist in the Research Excellence Framework (2014, 2021), which assess the quality of research in the UK.
The curriculum vitae and list of publications of Prof. Marian Wiercigroch is summarized below:
Curriculum vitae and list of publications
Title: Advances in Non-smooth Dynamics: Theory and Applications
Abstract: Non-smooth dynamics is the most vibrant area of nonlinear dynamics where new fundamental and applied advances are being made. In this lecture I will introduce the recent advances in the field of nonlinear dynamics with a special focus on non-smooth dynamical systems [1], which is the newest and vastly developing area with new phenomena such as grazing induced bifurcations [2] and a broad range of applications in science and engineering.
In the first part, I will review major advances in non-smooth dynamics over the last three decades with emergence of grazing and grazing induced bifurcations [3]. I will define the fundamental concepts in nonlinear dynamics with their techniques and I will focus on a class so-called non-smooth dynamical systems. Then I will show how such problems can be effectively modelled and analysed by low dimensional but calibrated dynamical systems [3,4]. The generic complexity of non-smooth dynamics will be demonstrated by an elastic impact oscillator – an archetypal model for modelling of high frequency vibro-impact drilling [5].
The second part will be devoted to what we might call Nonlinear Dynamics for Engineering Design where I will present results from my recent projects, where nonlinear dynamic interactions have been used to enhance the performance of real systems and structures. I will put a special emphasis on one large projects from energy industry, where we have developed a revolutionary downhole drilling technology [6] tested in our unique drilling laboratories [7,8]. I will argue that this would not be possible without calibrated low dimensional models.
[1] Wiercigroch, M. Modelling of dynamical systems with motion dependent discontinuities. Chaos Soliton Frac 11(15), 2429-2442, 2000.
[2] Jiang, H., Chong, A.S.E., Ueda, Y. and Wiercigroch, M. Grazing-induced bifurcations in impact oscillators with elastic and rigid constraints. Int J Mech Scie 127, 204-214, 2017.
[3] Wiercigroch, M., Kovacs, S. Zhong, S., Costa, D., Vaziri, V., Kapitaniak, M., Pavlovskaia, E. Versatile mass excited impact oscillator. Nonlinear Dynamics 99(1), 323-339, 2020.
[4] Cao, Q. Wiercigroch, M., Pavlovskaia, E.E., Thompson, J.M.T. and Grebogi, C. Piecewise linear approach to an archetypal oscillator for smooth and discontinuous dynamics. Phil T Roy Soc A 366, 635-652, 2008.
[5] Pavlovskaia, E.E., Wiercigroch, M. and Grebogi, C. Modelling of an impact system with a drift. Phys Rev E 64, 056224, 2001.
[6] Wiercigroch, M. Resonance Enhanced Drilling: Method and Apparatus. Patent No WO2007141550, 2007.
[7] Kapitaniak, M., Vaziri, V., Paez, J., Nandakumar, K. and Wiercigroch, M. Unveiling complexities of drill-string vibration: Experiments and modelling, Int J Mech Sci 101-102, 324-337, 2015.
[8] Liao, M., Wiercigroch, M., Sayah, M., Ing, J., 2021 Experimental verification of the percussive drilling model. Mech Syst Signal Process 146, 107067.

2. Prof. Chee Wah Lim（林志华), City University of Hong Kong [nonlinear mechanics]

Personal Details:
Currently a fellow of ASME, ASCE, EMI and HKIE, Ir Professor Lim received a B.Eng. from University of Technology of Malaysia, M.Eng. and PhD from National University of Singapore and Nanyang Technological University, respectively. Prior to joining City University of Hong Kong, he was a post-doctoral research fellow at The University of Queensland and The University of Hong Kong. He is also a visiting professor at various universities worldwide. He has expertise in theory of plates and shells, dynamics of smart piezoelectric structures, nanomechanics, metamaterials and symplectic elasticity. He is currently the subject editor for Journal of Sound and Vibration, joint-editor for Journal of Mechanics of Material and Structures, subject editor for Applied Mathematical Modelling, Managing Editor (Asia-Pacific Region) for Journal of Vibration Engineering & Technologies, Associate Editor for International Journal of Bifurcation and Chaos, etc. and also on the editorial board of some other top-ranked international journals. He has published one very well-selling title entitled “Symplectic Elasticity”, co-authored with W.A. Yao and W.X. Zhong from Dalian University of Technology, as recorded by the publisher, World Scientific, in Engineering Mechanics and Mechanical Engineering. He has published more than 370 international journal papers and have more than 13,000 citations. Recently Professor Lim was awarded the prestigious 2020 JN Reddy Medal as a recognition “for significant and original contributions to vibration of plates and shells, smart piezoelectric structures, nanomechanics, and symplectic elasticity”. He will deliver a plenary lecture and chair another plenary lecture at WCCM-APACM 2022, the largest biennial meet for computational scientists worldwide. In another scientific forum of four speakers organized by Chinese Science Bulletin and broadcasted on five online platforms, Professor Lim presented the opening lecture and the forum attracted accumulatively over 30,000 audience. He was also previously awarded Top Referees in 2009, Proceedings A, The Royal Society. Professor Lim is a registered professional engineer in Hong Kong.
Title: Nonlinear Dynamic Bifurcation and Chaos Characteristics of Piezoelectric Composite Plates
Abstract: This article investigates the nonlinear bifurcation and chaos characteristics of piezoelectric composite lattice sandwich plates at 1:3 internal resonance. The nonlinear vibration partial differential equation is first discretized into an ordinary differential equation by applying the Galerkin method. The main resonance modulation equations and the parametric resonance for the external excitation frequency that is close to the system second-order modal frequency are then obtained by using the multi-scale method. The Newton Raphson method is subsequently applied to obtain the bifurcation diagram of the steady-state equilibrium of modulation equation with varying system parameters. The equilibrium stability is finally analyzed. We conclude the existence of static bifurcation such as saddle-node bifurcation, pitchfork bifurcation, and Hopf dynamic bifurcation. A detailed analysis is also conducted on the complex nonlinear jump phenomenon caused by the presence of multiple nonlinear steady-state solution regions. In the dynamic Hopf bifurcation interval, the fourth-order Runge Kutta method is used to continue to track the dynamic periodic solution of the modulation equation in Cartesian coordinates. It is found that there are multiple boundary crises and attractor merging crises in the vibration system for piezoelectric composite lattice sandwich plates.
Keywords: bifurcation; chaos; Hopf bifurcation; lattice sandwich plates; nonlinear jump phenomenon; piezoelectric; resonance

3. Prof. Jianqiao Sun (孙建桥), University of California at Merced, USA [nonlinear vibrations]

Personal Details:
Dr. Jian-Qiao Sun earned a BS degree in Solid Mechanics from Huazhong University of Science and Technology in Wuhan, China in 1982, a MS and a PhD in Mechanical Engineering from University of California at Berkeley in 1984 and 1988. He worked for Lord Corporation at their Corporate R&D Center in Cary, North Carolina. In 1994, Dr. Sun joined the faculty in the department of Mechanical Engineering at the University of Delaware as an Assistant Professor, was promoted to Associate Professor in 1998 and to Professor in 2003. He joined University of California at Merced in 2007, and is currently a professor of the Department of Mechanical Engineering in School of Engineering. Besides many other editorial experiences, he is the Editor-in-Chief of International Journal of Dynamics and Control published by Springer.
His research interests include stochastic non-linear dynamics and control, cell mapping methods, multi-objective optimization, intelligent control systems and high-density piezoelectric energy harvesting from highway traffic.
Title: From Complexity to Simplicity
Abstract: Nonlinear dynamic systems can exhibit highly complex responses. Many mathematical methods have been created for analyzing the complex responses. These methods themselves are complicated. Nevertheless, it is always our dream to simplify solution methods. This talk presents several examples of engineering problems which are difficult to study, but can be simplified by taking a different view. Furthermore, we point out that modern machine learning tools are promising to create such as simplified approach for engineering system analysis. Examples of analysis of nonlinear stochastic systems are presented to illustrate the point.

4. Prof. Jianzhong Su (苏建中), University of Texas at Arlington, USA

Personal Details:
Dr. Jianzhong Su is Professor and Chair of Mathematics at University of Texas at Arlington. He received his Ph.D. in 1990 from University of Minnesota under Professor Hans Weinberger and he has been in higher education for over 30 years. His research specialty is applied mathematics, data science, and computational neuroscience, with over 80 papers in peer-reviewed journals. He has actively collaborated with other scientists, engineers, and physicians is US and worldwide. He is an experienced researcher, educator, and academic leader. He has served as PI/co-PI on over $12 million federal research, education and training funding from National Science Foundation, National Institutes of Health, US Department of Education, US Department of Agriculture and other agencies, published over 80 peer-reviewed journal papers and been invited to over 70 seminars and conferences, and advised over 12 math students who attained their Ph.D. degree under his supervision. He is very involved student mentoring of undergraduate students and high school students. He has been the chair of Mathematics Department at UT Arlington over 10 years and has been leading the development of the UT Arlington Mathematics Department. The UTA Mathematics Department has been the recipient of American Mathematical Society Award for Exemplary Mathematics Department in 2013 and American Mathematical Society Award for Mathematics Programs That Make a Difference in 2023.
Title: Brain Complex Data Analytics To Identify Epileptic Activity Sequences Based On EEG Source Localization Methods
Abstract: Data analytics plays an increasing role in brain research and medicine. The well-known Hodgkin-Huxley theory for neurons laid a foundation for computational neuroscience. However, understanding activities in the whole brain remains a focus of active research for this very complex system. Full brain Electroencephalography (EEG) and its source localization is a brain imaging modality based on multi-channel EEG signals. It measures the brain field potential fluctuations on the entire scalp for a period of time, and then we can compute the electric current density inside the brain by solving an inverse problem for an electric field equation on the 3-D brain finite element model. In this talk, we introduce computational methods for the EEG imaging problems, their validations through experimental data, and discuss its applications. One application is in identifying brain activity abnormalities and the sequence of excitation in brain anatomic areas during seizures of infant patients with Glucose Transporter Deficiency Syndrome. Our research shows the EEG data sets can be used to glean into the inner working of brain normal and pathological functions in specific brain areas using data analytic algorithms.

5. Prof. Guangyi Wang (王光义), Hangzhou Dianzi University, Hangzhou [memristors]

Personal Details:
Wang Guangyi received the Ph.D. degree in electronic science and technology from the South China University of Technology, in 2004. He is currently a Professor with the School of Electronic Information, Hangzhou Dianzi University. He is the founding directors of the Institute of Modern Circuits and Intelligent Information in 2009, the National teaching team for Electrical and Electronic Experiments in 2008, National Demonstration Center for Electrical and Electronic Experiments in 2006, and the Virtual Simulation Centre for Electronic Information Technology in 2012. His main research pursuit is memristive systems, chaotic circuits and chaotic cipher, including memristor modeling, memristive chaos, memristive neural networks, memristor-based logic circuits, chaotic circuit design, chaotic encryption systems, and chaotic secure communications. He has hosted 4 NSFC projects, one National ***project and one Zhejing Key NSF project, and was the co-PI of 9 NSFC projects (second member). He has published one academic monograph, 3 teaching books and over 100 SCI papers (4 highly cited papers) in refereed journals and conferences. He is the holder of over 20 national patents for invention, of which 6 technologies on chaotic encryption and memristor applications were transferred. His main honors and awards are as follows:
• 2023 IEEE Transactions on Circuits and Systems Guillemin-Cauer Best Paper Award from the IEEE Circuits and Systems Society (Corresponding author).
• The 2021 Armen H. Zemanian Best Paper Award from Circuits, Systems and signal Processing (Corresponding author).
• National Model Teacher of China conferred by the Ministry of Human Resources and Social Security, and the Ministry of Education of China, in 2019.
• National Teaching Achievement Award of China in 2018 (second-class prize, first prize winner) conferred by the Ministry of Education of China.
• National Teaching Achievement Award of China in 2009 (second-class prize, second prize winner) conferred by the Ministry of Education of China.
• National Teaching Achievement Award of China in 2023 (second-class prize, one of main prize winners) conferred by the Ministry of Education of China.
• Scientific Research Achievement Awards of Zhejiang Provincial University in 2009 (second prize, first author).
• Zhejiang Teaching Achievement Special Prize (2022), First Prizes (2009, 2016), and Second Prize (2022), from the People’s Government of Zhejiang Province.
• Zeng Xianzi Excellent Teacher Award from the Zeng Xianzi Educational Foundation (1999), Excellent Teacher Award of Zhejiang Province University from the People’s Government of Zhejiang Province (2012), Excellent Teacher of Shandong Province (1997).
Title: Edge of Chaos and Complex Dynamics of Locally Active Memristive Circuits
Abstract: From the perspective of complexity generating mechanism, this presentation applies the theories of local activity and edge of chaos to explore the design and complex dynamics analysis of LAM (locally active memristor)-based circuits and their applications in neuron/neural networks and chaos. We propose the small signal equivalent circuits of voltage-controlled and current-controlled LAMs, and the identifying conditions of their edge of chaos domains. On this basis, we use a LAM endowed with an edge of chaos as a minimum basic module (or core) to give a design method of LAM-based circuits and name it a "LAM + x" method. Based this method we design some LAM-based neuron circuits, neural networks and chaotic circuits, and find rich and complex dynamics phenomena near the edge of chaos, such as more than 20 kinds of neuromorphic behaviors and chaos, including "all or none", monophasic and diphasic action potentials, refractory period behavior, chimera state, unstable limit cycle and various chaotic attractors. We also shed light on the dynamic mechanism of the complex behaviors of LAM-based circuits, and explain Smale's paradox and Turing instability via supercritical and subcritical Hopf bifurcations near the edge of chaos. The calculation of edge of chaos domains, which is highly challenging, is the key to designing and analyzing LAM-based circuits and other complex systems. Hence, we propose a shortcut of calculating edge of chaos domains for typical LAM-based circuits. Furthermore, we implement a locally active Chua Corsage Memristor (CCM) with an inexpensive hardware circuit, which can be used to perform the hardware experiments of LAM-based circuits. Importantly, we for the first time observe the continuous DC V-I curves of CCM with an unstable branch in the CCM experiments.

6. Prof. Xiaosong Yang (杨晓松), Huazhong University of Science and Technology, Wuhan.

Personal Details:
Dr. Xiaosong Yang is currently Professor of Mathematics at Huazhong University of Science and Technology in Wuhan. Before joining the faculty in the School of Mathematics and Statistics at Huazhong University of Science and Technology he was Professor of Control theory at Xiamen University. After finishing self-education in undergraduate courses of mathematics and physics he earned a MS degree in applied mathematics from Huazhong Normal University in Wuhan and then received his Ph.D. in Pure Mathematics in 1998 from University of Science and Technology of China in Hefei.
He has published over 100 papers on chaos in dynamical systems and control theory with applications to circuits and passive walking dynamics, and a few papers on differential geometry and algebraic topology, all in peer-reviewed journals. His current research research interests mainly include some problems from topology and geometry, mathematical theory for artificial intelligence, and robotics.
Title: Understanding the black box of Deep learning from geometric perspective
Abstract: Deep learning has remarkably established itself as the outstanding machine learning technique in artificial intelligence (AI) and shown overwhelming successes in widely different application areas. However the lack of mathematical foundations for deep neural networks results in a time consuming search for a suitable network architecture and failure in some practical situations. This talk presents a geometric perspective on understanding black box of deep neural neural networks, which are workhorses of current artificial intelligence. In the basic setting of typical neural networks such as Relue networks, some mathematically fundamental questions in AI are reviewed and some theoretical progresses are discussed. The geometric structure of datasets in input space and design of efficient deep neural networks are closely related with each other, this talk reveals such a connection from topological and geometrical point of view with some geometrically illustrative toy examples. In addition, some tentative discussions on how to study deep neural networks from geometric perspective are also given in this talk.

7. Prof. Tianshou Zhou (周天寿), Sun Yet-sen University, Guangzhou [systems biology]

Personal Details:
Tianshou Zhou works as a professor with the Mathematical School of Sun Yat-sen University. Currently, he is a deputy director of the computational mathematics Key laboratory of Guangdong province and the director of the computational systems biology Professional Committee of Operations Research Society of China. His research direction is Computational Systems Biology. By far, he has published more 200 papers in academic journals including PNAS, PRL and NAR, and two monographs at the Science Press of China. He also led multiple fund projects including two key projects of the national nature Science fund, one key support project of Major Research Plan of the national nature Science fund, and one sub-project of 973 plan. Currently, he is the editors of multiple international academic journals including the internationally renowned overview journal: Current Opinions in Systems Biology.
Title: Modeling and analysis of biomolecular networks
Abstract: Biomolecular systems are in essence biochemical reaction networks, and the time evolution of the states of these networks can be taken as the continuous time random walk on grids. Conventional modeling methods of networked systems are based on Markov hypothesis. In the biological field, however, Markov is exceptional and non-Markov is more general. In this talk, I will first introduce a generic modeling method for biomolecular networks, then introduce, by an example, how a biomolecular network is inferred from a given set of experimental data, and finally present a simple discussion on the topic of modeling and inference.

8. Prof. Xu Xu (徐旭), Jilin University, Changchun [delayed-ssytem bifurcations]

Personal Details:
Xu Xu is a professor of College of Mathematics at Jilin University, China. He is the standing director of the Industrial and Applied Mathematics Society, and Operations Research Society in Jilin, China. He has served on the editorial board of International Journal of Bifurcation and Chaos, and International Journal of Novel Ideas: Mathematics. He is the outstanding talent of the Ministry of Education in the new century. His current research interests include: delayed systems, complex systems, and data-driven modelling.
Title: Delayed self-feedback echo state network: dynamics and memory capacity
Abstract: As a typical reservoir computing method, Echo State Networks (ESN) performs well in some real problems such as data-driven modelling, chaotic time series prediction and classification. However, ESN needs a sufficiently long time washout processing, is sensitive to noise, and is difficult to get the optimal parameters. In addition, the memory performance of the ESN models gradually disappears over time. The insufficient memory capacity of the ESN models limit its ability to solve long-run prediction problems in complex systems. In this talk, we proposes an echo state network with the delayed self-feedback (self-ESN) for analysis and prediction of long-term behavior of complex systems, such as the bifurcation and chaos. The self-ESN model considers the time-delay effect of neurons in the reservoir layer and introduces the time-delay feedback of hidden layer state to reflect the influence of the past time information on the current state, which improves the memory performance of the neural network system. By optimizing the design of self-feedback parameters, more optimized system output can be obtained, avoiding the difficulty of selecting parameters in traditional ESN methods. The global and local echo state property are analyzed, and sufficient condition of ESP are obtained to guarantee the robustness on the small perturbations. A measure of the memory capacity (MC) of the self-ESN is investigated to evaluate how well it is possible to recall delayed versions of the input based on reservoir activations. Numerical examples have shown that the ESN model can be successfully applied to predict complex chaotic time series, reconstruct bifurcation diagrams, and reconstruct chaotic time series with noise. The results indicate that the proposed method is an effective tool for analyzing and predicting complex systems.