Xiaokai Chen | Automobile Engineering | Editorial Board Member

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Assoc. Prof. Dr. Xiaokai Chen | Automobile Engineering | Editorial Board Member

Research Team Leader | Kunming University of Science and Technology | China

Assoc. Prof. Dr. Xiaokai Chen is an accomplished associate professor whose work centers on environmental health and safety in automobile cabins, contributing significantly to advancements in indoor air quality control, vehicle cabin pollution assessment, and the development of intelligent purification and safety systems for transportation environments. His professional experience includes long-term research and teaching in heating, ventilation, and air-conditioning (HVAC) engineering, where he has led multiple scientific projects, secured patents on innovative air-purification and disinfection technologies, and produced influential publications spanning air-pollution exposure, vehicle-cabin ventilation optimization, and safety-oriented engineering design. His research interests focus on vehicular environmental safety, pollutant behavior in transportation microenvironments, ventilation and purification system design, and risk assessment models for airborne contaminants affecting drivers and passengers. He demonstrates strong research skills in experimental testing, HVAC system design, pollutant detection and modeling, vehicle-cabin environmental analysis, and safety-oriented engineering optimization. His portfolio also showcases achievements such as contributing to monographs and textbooks, advising students who earned competitive academic recognitions, and guiding graduate researchers into industry sectors including construction, rail, quality supervision, and automotive manufacturing. In addition, he has provided extensive academic and social service as a technical expert in automotive research institutions, a member of key engineering societies, a reviewer for high-impact international journals, and an evaluator for national research foundations and academic competitions. His awards and honors reflect his contributions to technology innovation, student mentorship, research excellence, and professional service, reinforcing his reputation as a dedicated scholar promoting healthier and safer vehicular environments. Overall, his work bridges engineering innovation and public well-being, offering impactful solutions to real-world environmental health challenges in modern transportation systems, while sustaining active engagement in academic, industrial, and societal development. He has achieved 514 Citations, 14 Documents, 8 h-index.

Profiles:  Google Scholar  |  Scopus | ORCID

Featured Publications 

1.Feng, L., Xuan, Z., Zhao, H., Bai, Y., Guo, J., Su, C., & Chen, X. (2014). MnO₂ prepared by hydrothermal method and electrochemical performance as anode for lithium-ion battery. Nanoscale Research Letters, 9(1), 290. Citations: 239.

2. Xu, B., Chen, X., & Xiong, J. (2018). Air quality inside motor vehicles’ cabins: A review. Indoor and Built Environment, 27(4), 452–465. Citations: 141.

3. Chen, X., Zhang, G., Zhang, Q., & Chen, H. (2011). Mass concentrations of BTEX inside air environment of buses in Changsha, China. Building and Environment, 46(2), 421–427. Citations: 80.

4. Chen, X., Feng, L., Luo, H., & Cheng, H. (2014). Analyses on influencing factors of airborne VOCs pollution in taxi cabins. Environmental Science and Pollution Research, 21(22), 12868–12882. Citations: 52.

5. Feng, L., Xuan, Z., Bai, Y., Zhao, H., Li, L., Chen, Y., Yang, X., Su, C., Guo, J., et al. (2014). Preparation of octahedral CuO micro/nanocrystals and electrochemical performance as anode for lithium-ion battery. Journal of Alloys and Compounds, 600, 162–167. Citations: 38.

The nominee’s research advances scientific understanding of vehicle-cabin air quality and battery-material performance, addressing critical challenges in public health, environmental protection, and energy storage. His work supports cleaner transportation environments and contributes to the development of safer, more sustainable automotive technologies. Through impactful publications and applied innovation, his research drives progress at the intersection of engineering, society, and global well-being.

 

 

Hongbo Wang | Vehicle Dynamics | Best Researcher Award

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Prof. Hongbo Wang | Vehicle Dynamics | Best Researcher Award

Professor  |  Hefei University of Technology  | China

Prof. Hongbo Wang is a distinguished scholar whose work in intelligent vehicle dynamics and control has shaped both academic research and industrial applications, consistently advancing methodologies in vehicle motion modeling, intelligent control algorithms, and automated driving technologies. With extensive experience leading more than forty national, provincial, and municipal projects, his professional contributions span high-impact investigations into off-road vehicle technology, autonomous driving stability, integrated chassis control, and intelligent mobility systems. His research interests focus on vehicle dynamic behavior analysis, intelligent control strategies, computational modeling, and multi-source information fusion for advanced driving systems, supported by strong research skills in algorithm development, real-time system implementation, experimental platform construction, and interdisciplinary engineering integration. His portfolio of scientific achievements includes more than one hundred academic publications, thirty authorized invention patents, six software copyrights, participation in two provincial standard developments, and the publication of two influential monographs, positioning him as a leading contributor to the field’s evolution. His professional experience is complemented by service roles such as External Expert of the Off-Road Vehicle Technology Branch of the Chinese Society of Automotive Engineers, Member of the Vehicle Control and Intelligentization Technical Committee of the Chinese Association of Automation, and Director of the Anhui Society of Automotive Engineers, reflecting broad recognition across national organizations. His awards include the First Prize of the Science and Technology Award of the Chinese Society of Automotive Engineers, the Second Prize of the Machinery Industry Technology Invention Award, and multiple Anhui Provincial Teaching Achievement Awards, underscoring excellence in both research innovation and educational leadership. Overall, his career demonstrates a sustained commitment to advancing intelligent automotive technologies and fostering academic growth in the engineering community. He has achieved 532 Citations,  63 Documents , 12 h-index.

Profile:  Scopus

Featured Publications 

1. Wang, H., et al. (2025). Multi-objective parallel human–machine steering coordination control strategy of intelligent vehicles path tracking based on deep reinforcement learning. Chinese Journal of Mechanical Engineering (English Edition).

2. Wang, H., et al. (2025). Trajectory tracking multi-constraint model predictive control of unmanned vehicles based on sideslip stiffness estimation with XGBoost algorithm. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering.

3. Wang, H., et al. (2025). Yaw stability control of tractor vehicle based on nonsingular fast terminal sliding mode. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering.

4. Wang, H., et al. (2025). Intelligent vehicle path tracking coordinated optimization based on dual-steering cooperative game with fault-tolerant function. Applied Mathematical Modelling.

5. Wang, H., et al. (2025). Identification of intrusion obstacles for underground locomotives based on the fusion of LiDAR and wireless positioning technology. International Journal of Vehicle Performance.

Professor Hongbo Wang’s research advances intelligent vehicle control by integrating reinforcement learning, predictive modeling, and human–machine cooperation to enhance safety, stability, and autonomy. His work contributes directly to next-generation intelligent transportation systems, improves industrial vehicle technologies, and supports global innovation in automated mobility.

Adekanmi Adeyinka | Hybrid Vehicles | Best Researcher Award

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Mr. Adekanmi Adeyinka | Hybrid Vehicles | Best Researcher Award

Research Associate | Auburn University | United States

Mr. Adekanmi Miracle Adeyinka is an accomplished researcher, engineer, and educator with a distinguished background in mechanical and energy systems engineering, renewable energy technologies, and sustainable innovation. His professional experience spans academia, industry, and entrepreneurship, combining technical expertise with leadership in renewable energy advocacy and implementation. As Chief Executive Officer of Solar Pride Ltd., he spearheaded transformative projects, including the development of a 10-year renewable energy roadmap for a telecommunications firm, policy advocacy for sustainable energy regulations, and the establishment of the Solar Pride Academy to train young engineers in solar energy technologies. His earlier role as an Energy Consultant at T9 Embedded Systems Laboratory involved leading energy audits, integrating smart grid solutions, and implementing solar-wind hybrid systems that enhanced energy efficiency across industries. In academia, Adeyinka served as Lecturer II at the Federal University of Technology, Akure, where he redesigned the mechanical engineering curriculum and mentored research projects in sustainable energy applications. Currently, as a Graduate Teaching and Research Assistant at Auburn University, his research focuses on thermal management systems for lithium-ion batteries, improving battery performance, safety, and efficiency—work that has led to multiple high-impact publications and conference presentations. His research interests include battery thermal modeling, renewable energy integration, hybrid power systems, sustainable manufacturing, and energy policy development. Adeyinka’s research skills encompass data analysis, modeling, experimental design, energy systems optimization, and climate risk assessment, with proficiency in tools such as MATLAB, COMSOL, ANSYS, Python, and Power BI. His excellence has been recognized through several awards, including the 2024 SAE Doctoral Engineering Scholarship, Commonwealth Scholarship, and Walt Woltosz Fellowship. He is an active member of professional bodies such as ASME, IEEE, COREN, and SAE International. Adeyinka continues to advance the frontiers of clean energy innovation, with a deep commitment to sustainability, academic excellence, and technological advancement. He has achieved 65 Citations,  5 Documents, 3 h-index.

Profiles:  Google Scholar  | ORCID  |  Scopus

Featured Publications 

1. Adeyinka, A. M., Esan, O. C., Ijaola, A. O., & Farayibi, P. K. (2024). Advancements in hybrid energy storage systems for enhancing renewable energy-to-grid integration. Sustainable Energy Research, 11(1), 26.
Citations: 99

2. Adediji, Y. B., Adeyinka, A. M., Yahya, D. I., & Mbelu, O. V. (2023). A review of energy storage applications of lead-free BaTiO₃-based dielectric ceramic capacitors. Energy, Ecology and Environment, 8(5), 401–419.
Citations: 63

3. Adeyinka, A. M., Mbelu, O. V., Adediji, Y. B., & Yahya, D. I. (2023). A review of current trends in thin film solar cell technologies. International Journal of Energy and Power Engineering, 17(1), 1–10.
Citations: 54

4. Osibodu, S. J., Adeyinka, A. M., & Mbelu, O. V. (2024). Phase change material integration in concrete for thermal energy storage: Techniques and applications in sustainable building. Sustainable Energy Research, 11(1), 45.
Citations: 23

5. Ijaola, A. O., Akamo, D. O., Adekanmi, A. M., Saberi, Q., Koken, D., & Asmatulu, E. (2022). Superhydrophobic and self-cleaning electrospun microfibers from recycled styrofoam. Results in Surfaces and Interfaces, 9, 100086.
Citations: 19

Dr. Adekanmi Adeyinka’s research advances the frontiers of clean energy storage and sustainable materials, bridging gaps between renewable energy generation and grid reliability. His pioneering studies on hybrid storage systems, solar technologies, and eco-friendly materials contribute to reducing global carbon footprints and enhancing energy resilience. Through interdisciplinary innovation, his work empowers a transition toward a more sustainable, efficient, and circular energy economy worldwide.

Sreya Ghosh | Vehicular Communication Systems | Women in Automotive Award

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Dr. Sreya Ghosh | Vehicular Communication Systems | Women in Automotive Award

Assistant Professor  | IEM Kolkata  |  India

Dr. Sreya Ghosh is an accomplished researcher and academic specializing in intelligent transportation systems, vehicular ad hoc networks (VANETs), and wireless communication technologies. Currently serving as an Assistant Professor in the Department of Computer Science and Engineering (AIML) at the Institute of Engineering and Management, Kolkata, she has contributed significantly to the advancement of AI- and ML-driven solutions for next-generation vehicular networks. Her doctoral research at Jadavpur University focused on the design of vehicular ad hoc networks with enhanced performance applicable to intelligent transportation systems, integrating machine learning and communication optimization techniques. Over the years, she has published several impactful research papers in reputed international journals such as Wiley and Springer, with notable works including intelligent sensing-based resource allocation in 5G-V2X networks, RSU deployment optimization using complex network analysis, and enhanced routing algorithms for energy-efficient vehicular communication. Dr. Ghosh has also presented her research at numerous IEEE conferences, contributing to the development of algorithms for CO₂ emission reduction, cooperative caching, and congestion mitigation in smart cities. Her research interests span sensor networks, AI/ML applications, natural language processing, IoT, and algorithm design, with a strong emphasis on sustainable intelligent mobility. She possesses advanced technical skills in Python, PyTorch, Keras, MATLAB, and C, enabling her to develop and simulate intelligent systems effectively. She has been awarded prestigious fellowships, including the CSIR Senior Research Fellowship and the UGC UPE Fellowship, in recognition of her research excellence. Additionally, she has contributed as a reviewer for reputed IEEE and Springer journals and conferences and has organized academic events promoting innovation in computing and communication technologies. Her dedication to research and academic excellence reflects her commitment to advancing intelligent systems for societal benefit. She has achieved 61 Citations,   11 Documents, 5 h-index.

Profiles: Google Scholar  |  ORCID  |  Scopus

Featured Publications 

  1. Ghosh, S., Misra, I. S., & Chakraborty, T. (2023). Optimal RSU deployment using complex network analysis for traffic prediction in VANET. Peer-to-Peer Networking and Applications, 16(2), 1135–1154. Citations: 18

  2. Ghosh, S., & Misra, I. S. (2020). Enhanced QoS performance with reduced route overhead by ant colony optimization algorithm for VANET. In 2020 IEEE Applied Signal Processing Conference (ASPCON) (pp. 237–241). IEEE. Citations: 10

  3. Ghosh, S., & Misra, I. S. (2017). Design and testbed implementation of an energy efficient clustering protocol for WSN. In 2017 International Conference on Innovations in Electronics, Signal Processing and Communication (IESC) (pp. 55–60). IEEE. Citations: 9

  4. Ghosh, S., Misra, I. S., & Chakraborty, T. (2023). Improved Quality of Service by canine olfactory route finding algorithm for Vehicular Ad Hoc Network. Transactions on Emerging Telecommunications Technologies, 34(6), e4764. Citations: 5

  5. Ghosh, S., Misra, I. S., & Chakraborty, T. (2022). Developing an application for intelligent transportation system for emergency health care. In 2022 IEEE Calcutta Conference (CALCON) (pp. 39–43). IEEE. Citations: 2

Dr. Sreya Ghosh’s research integrates artificial intelligence, wireless communication, and vehicular networking to build smarter, safer, and more sustainable transportation ecosystems. Her innovative work on RSU optimization, QoS enhancement, and energy-efficient network design contributes to the development of next-generation intelligent transportation systems that support traffic efficiency, environmental sustainability, and smart city evolution worldwide..

 

Ding Peng | Autonomous Vehicles | Best Researcher Award

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Assist. Prof. Dr. Ding Peng | Autonomous Vehicles | Best Researcher Award

Associate Professor | Wuxi University of Technology |China

Assist. Prof. Dr. Ding Peng is an accomplished academic and researcher currently serving as an Associate Professor at Wuxi University of Technology, formerly known as Wuxi Institute of Technology, China. He is also a key member of the Jiangsu Province Engineering Research Center for Energy Saving and Safety of New Energy Vehicles, where he plays a vital role in promoting innovation and sustainability in the automotive sector. Dr. Peng obtained his degree in Vehicle Engineering from Chongqing University which laid a strong foundation for his expertise in intelligent vehicle systems and new energy technologies. His professional experience includes working as a Design Engineer at King Long United Automotive Industry (Suzhou) Co., Ltd., where he participated in the design and development of commercial buses, followed by a distinguished academic career at Wuxi University of Technology . Over the years, Dr. Peng has demonstrated exceptional competence in teaching and research, covering courses such as Automobile Structure, Automobile Theory, Principles of Automatic Control, and Intelligent and Connected Vehicle Technologies. His research interests focus on thermal management technologies for new energy vehicles, autonomous vehicle control strategies, and intelligent connected vehicle (V2X) technologies. His research skills encompass modeling, simulation, data fusion, control algorithms, and system optimization, emphasizing practical integration between academia and industry. Dr. Peng has led numerous enterprise and government-funded projects, published several high-impact academic papers, and secured multiple national patents, showcasing his dedication to advancing innovation in smart and sustainable mobility. His awards and honors include recognition for his leadership in research excellence, academic innovation, and contributions to engineering education. Driven by a vision of merging scientific theory with real-world application, he continues to nurture the next generation of engineers while advancing intelligent vehicle technologies. He has achieved 29 citations , authored 7 scientific papers, and holds an h-index of 2 .

Profiles:  Scopus | ORCID

Featured Publications

  1. Ding, P. (2025). A Cooperative Control Strategy for Predicting Passing Capacity and Intelligent Obstacle Avoidance in Autonomous Vehicles Based on Multisensor Fusion. Journal of Energy Storage.

  2. Ding, P. (2024). A distributed multiple-heat source staged heating method in an electric vehicle. International Journal of Vehicle Performance and Energy Systems.

  3. Ding, P. (2024). Distributed multi-heat-source hybrid heating system based on waste heat recovery for electric vehicles. Journal of Thermal Science and Energy Engineering.

  4. Ding, P. (2023). Research on interactive coupled preheating method utilizing engine-motor cooling waste heat in hybrid powertrains. Applied Thermal Engineering

 

Mohammad Anis | Transportation Engineering | Best Researcher Award

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Mr. Mohammad Anis | Transportation Engineering | Best Researcher Award

PhD Student | Texas A&M University| United States

Mr. Mohammad Anis is a dedicated Ph.D. candidate in Civil and Environmental Engineering at Texas A&M University, specializing in traffic safety, autonomous vehicle safety, crash risk modeling, pedestrian safety, and digital twin applications. He previously earned an M.S. in Civil Engineering from the University of Texas Rio Grande Valley (2021), where he conducted pioneering research on electrically heated rigid pavements, and a B.S. in Civil Engineering from Dhaka University of Engineering & Technology, Bangladesh (2018). With over four years of research experience, he has worked extensively on federally and state-funded projects with agencies such as FHWA, TxDOT, NCHRP, FMCSA, and ODOT, contributing to crash prediction models, pedestrian safety analysis, driver distraction studies, and systemic roadway design improvements. His dissertation integrates physics-informed near-miss data with hierarchical Bayesian frameworks for real-time crash occurrence risk estimation, pushing the boundaries of data-driven traffic safety planning. His professional experience includes roles as a doctoral researcher at Texas A&M University, a graduate research assistant at the Texas A&M Transportation Institute, and a graduate teaching assistant at both Texas A&M University and UTRGV, where he mentored students in transportation engineering and civil materials. His research interests lie in real-time safety modeling, AI and machine learning applications in transportation, spatiotemporal crash risk prediction, and sustainable roadway infrastructure. He is skilled in programming (Python, R, MATLAB), statistical modeling (MCMC, machine learning, time-series analysis), traffic simulation tools (SUMO, VISSIM, CARLA), and GIS platforms (ArcGIS, QGIS). He has published widely in high-impact journals such as Accident Analysis & Prevention and Transportation Research Record, along with multiple IEEE and Scopus-indexed conferences. Among his many accolades are the Keese-Wootan Transportation Fellowship (Top 5%), Zachry Excellence Fellowship, Terracon Foundation Scholarship, and Graduate Student Travel Awards. With a strong record of publications, collaborations, and peer-review service, Mr. Anis demonstrates outstanding potential to lead future research in traffic safety and intelligent mobility systems. He has achieved 30 citations across 27 documents, with 8 publications and an h-index of 2.

Profiles:  Scopus | ORCID

Featured Publications

Anis, M., Geedipally, S. R., & Lord, D. (2025). Pedestrian crash causation analysis near bus stops: Insights from random parameters Negative Binomial–Lindley model. Accident Analysis & Prevention, 220, 108137.

Zhang, H., Li, S., Li, Z., Anis, M., Lord, D., & Zhou, Y. (2025). Why anticipatory sensing matters in commercial ACC systems under cut-in scenarios: A perspective from stochastic safety analysis. Accident Analysis & Prevention, 218, 108064

Anis, M., Li, S., Geedipally, S. R., Zhou, Y., & Lord, D. (2025). Real-time risk estimation for active road safety: Leveraging Waymo AV sensor data with hierarchical Bayesian extreme value models. Accident Analysis & Prevention, 211, 107880.

Abdel-Raheem, M., & Anis, M. (2025). Toward sustainability: A new construction method for electrically heated rigid pavement systems. Transportation Research Record: Journal of the Transportation Research Board, 2679(3), 281–303.

Anis, M., & Abdel-Raheem, M. (2024). A review of electrically conductive cement concrete pavement for sustainable snow-removal and deicing: Road safety in cold regions. Transportation Research Record: Journal of the Transportation Research Board, 2678(9), 50–71.