Announcements

We are pleased to announce that Dr. Vijayalakshmi K. Kumarasamy, Prof. Dr. Yu Liang and Prof. Dr. Dalei Wu’s paper “Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization” has won the Symmetry Best Paper Award, as it is one of the exceptional articles published in Symmetry (ISSN 2073-8994). As winners of this award, authors will receive CHF 400, a certificate, and a free voucher for article processing fees valid for one year.

The following is a short interview with the winners, Dr. Vijayalakshmi K. Kumarasamy, Prof. Dr. Yu Liang and Prof. Dr. Dalei Wu:

1. Congratulations on winning the Symmetry Best Paper Award! Could you please briefly introduce yourself?
Dr. Vijayalakshmi K. Kumarasamy: Hello everyone. My name is Vijayalakshmi Kumarasamy, and I just recently graduated with my PhD in computer science. My great advisers were Prof. Liang and Prof. Wu. Currently I’m working as Visiting Assistant Professor at the University of Tennessee at Chattanooga and my research has focused on artificial intelligence, reinforcement learning, digital twins and especially intelligent transportation systems during my PhD thesis.
Prof. Dr. Dalei Wu: Good morning, everyone. I am a professor with the Department of Computer Science and Cyber Security at the University of North Georgia. I just moved from the University of Tennessee at Chattanooga. I started this position on July 1st this year. Previously the three of us worked in the same research group at UTC; that is why we did this research together and submitted and published this paper. I am very glad that this work received this award.
Prof. Dr. Yu Liang: Good morning. My name is Yu Liang. I am a professor of computer science and engineering at UTC, and my research interests are AI modeling simulations and numerical linear algebra.

2. Could you give a brief overview of the main content of your award-winning paper?
Dr. Vijayalakshmi K. Kumarasamy: This paper investigates how decentralized graph-based multi-agent reinforcement learning can be integrated with digital twin to improve traffic signal control. Our motivation was to address an important limitation of conventional traffic control. Traffic conditions vary considerably across intersections and throughout the day at different times. But traditional control methods may not adapt effectively to those changing conditions, like the changing and asymmetric conditions. In our work, each intersection is represented as an intelligent agent that makes local traffic signal decisions while also using graph-based information from the nearby intersections. So, the digital twin provides a realistic virtual representation of the traffic corridor in which the agent can learn and be evaluated safely. We tested the approach using MLK (Martin Luther King) Smart Car Corridor in Chattanooga, Tennessee. The result showed meaningful reductions in our vehicle stops and stop-related delays, which suggested that this approach would contribute to more efficient and environmentally suitable urban traffic management. I’m very pleased that our paper received more than 7,300 views and I believe the interest reflects the growing importance of combining artificial intelligence, digital twin and real-world transportation infrastructure.

3. Please introduce your current research focus and the main research areas of your team.
Dr. Vijayalakshmi K. Kumarasamy: I’m working on using edge processing, like internet of things, on how we can move our application into the real world and how it can scale up the application to multiple intersections. We have already designed our application that way, scalable and adaptable, and I’m focusing on how it can adapt to edge processing and include multimedia data, like pedestrians and pedestrian crossings with signal control data, with pedestrian arrival as well as images and videos. In the real world, traffic conditions vary based on the day and time, as well as weekdays and weekends.
Prof. Dr. Dalei Wu: My research mainly focuses on data-driven intelligent systems, cyber–physical systems and trying to integrate AI into the system to make them more adaptable, autonomous and intelligent. We especially explore using AI technology in transportation, energy and urban infrastructure.
Prof. Dr. Yu Liang: Besides what my colleagues have mentioned, we also have sponsored work involving AI-enabled medical applications, such as those used in physical and psychological therapy.

4. Could you describe some challenges and breakthroughs in your research field?
Prof. Dr. Dalei Wu: Because we use AI machine learning models sometimes, we don’t have high-quality data, especially data for training the machine learning models. That’s a challenge. To overcome it, we apply simulation modeling to generative data, but sometimes it is not close to real-world data and that affects the performance of the machine learning models.
Prof. Dr. Yu Liang: I think there are two big challenges we are facing right now; the first one is that this field of AI progresses so rapidly so it’s very challenging to keep up with the newly developed technologies. The second one is validation. We need a collaboration with domain experts to validate our AI systems. This can be challenging as not everyone is fond of AI.
Dr. Vijayalakshmi K. Kumarasamy: From my side, another challenge is getting from model development into real-world development. In the real world there are a lot of restraints and restrictions based on environment and safety conditions. I have encountered this challenge even in my current research paper as well. Safety is very important, especially when dealing with vulnerable users. Another challenge is handling sensitive information processing and accuracy. Furthermore, in this research, an important breakthrough is a movement towards safe and constrained reinforcement learning, where the operational rules are built directly into the agent’s action space.

5. What factors attracted you to submit your paper to Symmetry? How was your submission experience?
Dr. Vijayalakshmi K. Kumarasamy: With Symmetry, the submission process was very smooth, and we got clear instructions once the review process completed.
Prof. Dr. Dalei Wu: At the time when we were looking for journals to publish this paper, we found that Symmetry has a broad topic scope and publishes papers in different areas. The publications also have solid foundational work. These factors determined us to submit to the journal.
Prof. Dr. Yu Liang: I like Symmetry because it values both mathematic integrity and also engineering applications. This attracted me most to the journal.

6. In your opinion, which research topics will attract widespread attention in the academic community in the coming years?
Dr. Vijayalakshmi K. Kumarasamy: What I’m seeing more often are topics such as multimodal data integration, edge processing, and computer vision. These areas appear to be receiving increasing attention in current research and development. On the industry side, I noticed that they are trying to adapt to generative AI. Digital twins are also continuing to grow as an important area of research.
Prof. Dr. Dalei Wu: I think AI has achieved profound advances. I think the next steps for research will be how to integrate AI with physical world systems. The topic of physical AI, I think it will be pretty popular and attractive research topic. Some of the fundamental research challenges include achieving controllability, explainability, and reliability in AI-enabled physical systems.
Prof. Dr. Yu Liang: Besides what my colleagues just mentioned, I would like to add quantum computing, quantum sensing and quantum communication as relevant areas of research.

7. What advice would you give to young researchers who aspire to produce high-impact research results?
Prof. Dr. Dalei Wu: I would encourage young researchers to keep exploring and keep digging deeper; to be optimistic that no work will be wasted and they will be rewarded.
Dr. Vijayalakshmi K. Kumarasamy: We have to begin with a meaningful real-world problem, not just a trending technology. Be strong and collaborate across disciplines in different groups and chapters, try to attend conferences. Also, be honest with the limitations encountered and be curious and persistent.
Prof. Dr. Yu Liang: They should be confident. As a faculty member and adviser, I want to add that we should always have faith in our students and give them full academic freedom. We can tell them the topic but let the student figure out the pathway and how to do the work.

8. As the recipient of this award, could you share your feelings and whom you would like to thank?
Dr. Vijayalakshmi K. Kumarasamy: Obviously, first we have to thank our collaborators at Georgia Tech University, University of Pittsburgh and ORNL and our UTC team of course. We are very thankful to the Symmetry Editorial Office and all the reviewers for recognizing our work and encouraging us. In the future we look forward to submitting more papers and engaging with MDPI journals.
Prof. Dr. Dalei Wu: We are thrilled to receive this award. This research work was supported by a grant from DOE funded and the project was led by Dr. Mina Sartipi. We also want to thank all the team members, including Dr. Michael P. Hunter from Georgia Tech, Dr. Mina Sartipi from UTC, Dr. Aleksandar Stevanovic from Pittsburgh and other researchers from Oak Ridge National Laboratory. We are grateful to all our team members and co-authors.
Prof. Dr. Yu Liang: I would like to add a big thanks to Vijayalakshmi, our first author. Her background is mathematics. In the beginning when we started this project, Prof. Wu and I were a little worried about not being able to get all the work done, but she very pleasantly surprised us. I appreciate her and her contributions.

9. Symmetry is an open access journal. How do you think open access impacts readers and authors?
Dr. Vijayalakshmi K. Kumarasamy: I think open access increases the visibility of the paper. We noticed that for closed access journals, people will reach out to us to ask for the papers. Open access, however, provides immediate access so that anyone can quickly read it.
Prof. Dr. Dalei Wu: Yes, I think open access definitely gives readers more information sources. It also provides authors with increased visibility for their research.
Prof. Dr. Yu Liang: I believe the open access is the future.

More information about journal awards can be found at the following link: https://www.mdpi.com/journal/symmetry/awards.