Interview with Dr. Hairong Lin—Winner of the Mathematics 2024 Young Investigator Award

Name: Dr. Hairong Lin
Affiliation: School of Electronic Information, Central South University, Changsha, China
Research interests: neural networks and neurodynamics; chaotic systems and circuits; chaotic encryption and information security; neuromorphic systems and circuits

Dr. Hairong Lin, Ph.D., is an associate professor and master supervisor at the School of Electronic Information, Central South University, China. He was selected for the 2023 and 2024 “World’s Top 2% Scientists” list released by researchers from Stanford University, USA. He is an IEEE Member, a member of the Chaos and Nonlinear Circuits Committee of the China Institute of Electronics, and a member of the Internet of Things Committee of the Hunan Institute of Electronics and serves as an editor or young editor of domestic and international journals. He has presided over several national and provincial projects and participated in a number of major projects of the National Natural Science Foundation of China. As the first/corresponding author, he has published more than 30 high-level SCI papers in international top-tier journals, including 9 ESI hot papers and 16 ESI highly cited papers. His papers have been cited more than 3,200 times in total, with an h-index of 33 in Scopus.
Our interview with him can be found below:

1. Could you give a brief introduction of yourself to the readers? Could you introduce your current research direction and provide an update on your progress?
I obtained my Ph.D. in computer science and technology from Hunan University, China, in December 2021. Subsequently, I conducted post-doctoral research at Hunan University for two years. In January 2024, I joined Central South University as an associate professor.
My research directions mainly focus on two aspects: the theoretical research and applications of neurodynamics. In terms of theoretical research, I’m committed to constructing neuron and neural network models by introducing emerging technologies such as nonlinear dynamics, fractional-order calculus, and memory components (such as memristors and memcapacitors) to simulate the nonlinear dynamic behavior of biological nervous systems. This research direction aims to deeply explore the computational mechanisms and intelligent characteristics of brain networks. At present, my team and I have successfully proposed a variety of memristive neural network models with complex dynamic behaviors, which have helped us reveal the evolution mechanisms of some brain dynamic behaviors.
In terms of the application of neurodynamics, I mainly focus on the application of brain-inspired chaotic encryption technology in resource-constrained terminal devices such as edge computing, intelligent perception, and the Internet of Things. Especially for the requirements of secure communication in extreme environments such as deep water and deep space, we are dedicated to developing communication solutions that are low-power, lightweight, efficient, reliable, and highly secure. Currently, we have proposed a variety of brain-inspired chaos-based data privacy protection schemes, which can be widely applied in fields such as the medical Internet of Things and satellite networks, providing strong protection for data security.
In the future, I will continue to deeply explore the frontier issues of neural networks and neurodynamics and strive to transform theoretical research results into practical applications, contributing to the development of intelligent technology.

2. Could you please share some particularly interesting or unexpected results you have found during your research experience? Also, what’s your opinion on interdisciplinary research?
When studying the multi-scroll attractor dynamics and multi-wing multi-butterfly attractor dynamics of memristive neural networks, we indeed encountered some very interesting and unexpected findings. Initially, we hypothesized that the generation mechanisms of multi-scroll and multi-wing multi-butterfly attractors might have similar internal laws. However, the experimental results surprised us.
We found that the generation of multi-scroll dynamic behavior mainly depends on the structure and parameter settings of the neural network model itself, while the generation of multi-wing multi-butterfly dynamic behavior is mainly affected by the memristor model and its parameters. This discovery completely overturned our expectations because usually, we would think that as a core component of the neural network, the memristor should play a key role in the generation of both types of attractors. However, the experimental results show that the memristor plays a dominant role in the formation of multi-wing multi-butterfly attractors, while its influence on the generation of multi-scroll attractors is relatively weak.
This phenomenon shocked us and also triggered our in-depth thinking about the underlying mechanism. Currently, we are further exploring the theoretical basis of this phenomenon, trying to reveal the specific mechanisms of the neural network model and the memristor in the generation of different attractors. We suspect that this may be closely related to the topological structures, dynamic characteristics of the two types of attractors, and the nonlinear behavior of the memristor, but the specific reasons still need to be verified through more experiments and theoretical analyses.
This discovery not only provides a new perspective for the research of memristive neural networks but also brings more possibilities for our subsequent research directions. We hope that through further research, we can reveal more mysteries about the complex relationship between neural networks and memristors and provide theoretical support for applications in related fields. In scientific research, we often encounter such “accidents”, and these “accidents” are often the driving force that pushes us forward.

3. Which research topics do you think will be of particular interest to the research community in the coming years?
Personally, I think that in the next few years, the research on neurodynamics based on new memory components such as memristors and memcapacitors will still be a hot topic in this field. New memory components have natural memory-bionic characteristics and are considered core components of brain-inspired computing. Although the research on memristive neurons and neural networks is already very extensive, high-dimensional memristive neural networks and discrete memristive neural networks are still research hotspots.
In addition, compared with memristors, the research on memcapacitors is still in its infancy. However, its unique physical properties and potential application value make it show great development potential in the fields of neurodynamics, brain-inspired computing, and artificial intelligence. Therefore, the research on neurodynamics based on memcapacitors not only has important theoretical significance but may also provide a new breakthrough for the development of future intelligent technology.
In my opinion, interdisciplinary research is the key to solving complex problems. At present, the development of science and technology is increasingly showing a trend of cross-integration. The research methods of a single discipline often cannot cope with complex real-world problems. For example, the research of neurodynamics requires the integration of knowledge from multiple disciplines such as mathematics, physics, computer science, and biology, while the application of memcapacitors and memristors involves fields such as materials science, electronic engineering, and information security.
Interdisciplinary research can not only break down disciplinary barriers and promote the innovation and integration of knowledge but also provide a more comprehensive perspective and methods for solving practical problems. Therefore, I believe that in the future, interdisciplinary research will witness more vigorous development and become an important driving force for scientific and technological progress.

4. Do you have any advice for aspiring young researchers looking to make a meaningful impact in their respective fields?
For young researchers who aspire to have a significant impact in their respective fields, I wouldn’t say I’m giving suggestions, but I can share some of my personal experiences.
First of all, it’s very important to choose a promising small field and continue to delve into it. Scientific research requires time and patience. Only by continuously accumulating in one direction can you form your unique insights and make breakthroughs.
Secondly, the path of scientific research is not always glamorous. Many times, you need the perseverance to “sit on the cold bench”. Chasing hot topics can bring short-term attention, but real influence often comes from the long-term exploration of core issues.
Finally, the courage to break through traditional thinking is also essential. Scientific progress often stems from the questioning and innovation of existing theories. Young researchers should keep an open mind and be brave enough to challenge the norm. I’m also constantly learning and exploring, and I hope to encourage each other with everyone and jointly push the boundaries of science.

5. As the winner of this award, is there something you want to express or someone you wish to thank most?
As the winner of this Young Investigator Award, I’m filled with gratitude and emotion.
First of all, I would like to sincerely thank the chairperson of the journal Award Committee and all the judges for their hard work and recognition. This honor is not only an affirmation of my personal research but also an incentive for my future scientific research path.
Secondly, I would like to thank the journal Mathematics and peer experts for their continuous support and encouragement. It is with such an open and inclusive academic platform that I can communicate and cooperate with outstanding peers at home and abroad and keep making progress.
Finally, I would like to especially thank my supervisor, Professor Chunhua Wang from Hunan University, China. Professor Wang is the guide of my academic career. From my master’s to Ph.D. and post-doctoral stages, I have been learning and growing under his guidance. Professor Wang’s rigorous academic attitude, profound academic attainments, and boundless enthusiasm for scientific research have deeply influenced me. It can be said that without his careful guidance and support, I wouldn’t have achieved my current academic achievements. He has not only taught me how to conduct research but also made me understand the responsibilities and missions of scientific researchers. This honor belongs to all those who have helped me and every member of our team. In the future, I will continue to work hard, hold myself to higher standards, and contribute to the development of scientific undertakings. Thank you again for your support and love!

6. What is your opinion of the open access model of publishing?
The open access publishing model is undoubtedly the future direction of academic publishing. It plays an important role in promoting the dissemination and communication of academic achievements.
First of all, open access breaks down the barriers of the traditional subscription model, enabling global researchers to access the latest research results for free and instantly, which greatly promotes the sharing and dissemination of knowledge. Especially for scholars in regions with limited research funds, this model provides them with an equal opportunity to access academic resources, helping to narrow the research gap.
Secondly, the open access publishing model, through its transparent publishing process and extensive reader participation, can to some extent curb the breeding of pseudo-academic research and enhance the quality and credibility of academic research. Although the open access model incurs page-charge expenses for authors, if the fees can be controlled within a reasonable range and supported by institutions or funds, the benefits far outweigh the costs.
Overall, the open access model not only accelerates the dissemination of academic achievements but also provides a broader platform for global scientific research cooperation and innovation, making it an important force in promoting academic progress.

We wish Dr. Hairong Lin every success in his current work, and we look forward to his future contributions to the journal.

For more information about the awards presented by Mathematics, please visit the following link: https://www.mdpi.com/journal/mathematics/awards.

Mathematics Editorial Office