Oluwaseun Akinte | Optimization | Best Researcher Award

Published on by Math Scientist

Dr. Oluwaseun Akinte | Optimization | Best Researcher Award

Oluwaseun Akinte | Rajamangala University of Technology Thanyaburi | Thailand

Dr. Oluwaseun Olanrewaju Akinte is a Postdoctoral Researcher in Energy and Materials Engineering at Rajamangala University of Technology Thanyaburi, specializing in renewable energy systems, hybrid microgrids, and advanced storage technologies. He earned his Ph.D. in Energy and Materials Engineering from Rajamangala University of Technology Thanyaburi, an M.Sc. in Electrical and Electronic Engineering from Coventry University, United Kingdom, and a B.Sc. in Electrical and Electronic Engineering from Olabisi Onabanjo University, Nigeria. His professional journey spans academia and industry, including roles as Research Assistant at RMUTT, Academic Tutor in Nigeria, Project/Site Engineer with Electromechanical Integrators Inc., and voluntary postgraduate lecturer at the University of the People, USA. His research contributions focus on energy storage optimization, hybrid renewable energy networks, and techno-econometric analysis of integrated microgrids, producing impactful publications in high-ranking journals such as IEEE Access, Energies, Sustainability, and Franklin Open, alongside international conference presentations. Dr. Akinte has co-authored over 16 journal and conference papers with 18 citations across 18 documents, reflecting his growing scholarly influence. His leadership extends to collaborative projects with industrial partners, addressing energy efficiency and sustainability challenges, while his invited talks at international congresses highlight his recognition in the global research community. He has been honored with the E-CUBE-I RMUTT Scholarship and the Best Oral Presentation Award at the Energy Society and Sustainability Conference. In addition, he is an active member of the International Association of Engineers (IAENG), contributing to knowledge exchange in the field of electrical and energy engineering. With strong expertise in power system modeling, microgrid optimization, and renewable integration, Dr. Akinte continues to advance innovative energy solutions with global impact. Citations: 18, Documents: 5, h-index: 2.

Profiles: Google Scholar | Scopus | ORCID

Featured Publications

1. Akinte O.O.*, Plangklang B., Prasartkaew B., Aina T.S., Energy storage management of a solar photovoltaic–biomass hybrid power system. Energies, 2023, 16(13), 5122.

2. Aina T.S.*, Akinte O.O., Awelewa A.J., Adelakun D.O., Critical evaluation of waterfall project management methodology: A case study of digital management conference project. Int. J. Adv. Multidiscip. Res. Stud., 2022, 2, 1–10.

3. Akinte O.O.*, Aina T.S., HVAC vs HVDC power system: Contemporary development in HVAC and HVDC power transmission system. Int. J. Sci. Technol. Res., 2021, 19, 252–261.

4. Aina T.S.*, Akinte O.O., Iyaomolere B.A., Investigation on performance of microstrip patch antenna for a practical wireless local area network (WLAN) application. Int. J. Res. Appl. Sci. Eng. Technol. (IJRASET), 2022, 10, 221–226.

5. Aina T.S.*, Akinte O.O., Iyaomolere B., Tosin A.E., Abode I.I., Awelewa A.J., Implementation of an intelligent motion detector. Int. Res. J. Eng. Technol. (IRJET), 2022, 9(1), 1148–1165.

Binghao OuYang | Optimization | Best Researcher Award

Published on by Math Scientist

Dr. Binghao OuYang | Optimization | Best Researcher Award

Research assistant at City University of Hong Kong, China

Dr. OuYang Binghao (欧阳炳濠) is a promising early-career researcher specializing in game theory and distributed Nash equilibrium seeking algorithms ⚙️📊. Currently pursuing a joint PhD at City University of Hong Kong and University of Science and Technology of China, he holds a strong academic record with a GPA of 3.78/4.3 🎓. His research focuses on fixed-time convergence algorithms for complex control systems, with practical applications in non-cooperative games and Euler-Lagrange systems 🔍🤖. Dr. OuYang has earned several awards, including a gold medal at the National College Student Innovation Competition 🥇 and recognition as an outstanding undergraduate graduate. Skilled in Python, C++, and Matlab, he also applies reinforcement and deep learning techniques to advance his research 💻🧠. With a solid mathematical foundation and innovative approach, Dr. OuYang is a rising talent in control science and engineering, poised to make significant contributions to his field.

Professional Profile 

🎓 Education

Dr. OuYang Binghao (欧阳炳濠) has pursued a rigorous academic path in engineering and control science. He earned his Bachelor’s degree in Automation from the University of Science and Technology of China (USTC) (2016–2020) 🎯, followed by PhD studies in Control Science and Engineering (2020–2022) with a GPA of 3.50/4.3 📚. Currently, he is completing a Joint PhD in Biomedical Engineering and Control Science at City University of Hong Kong and USTC, maintaining an impressive GPA of 3.78/4.3 🏅. Guided by Professors Feng Gang and Wang Yong, his education blends theoretical depth with applied research, equipping him to tackle complex engineering challenges across interdisciplinary domains 🎓🔬.

💼 Professional Experience

Dr. OuYang has demonstrated practical innovation from early in his academic career. In 2020, his excellent undergraduate graduation project involved the development of a fingerprint attendance system 🛠️. Later, in 2021, he participated in the China International College Students Innovation Competition, helping design a motion perception and high-precision positioning system, which won a gold award 🥇. From 2022–2023, he conducted research at City University of Hong Kong focused on distributed Nash equilibrium seeking in non-cooperative games 🤝📈. His hands-on experience bridges theoretical modeling and real-world applications, showcasing a promising blend of technical creativity and research diligence 💡🧪.

🔬 Research Interest

Dr. OuYang’s core research areas include game theory, distributed Nash equilibrium algorithms, and fixed-time convergence strategies for control systems 📐⚙️. He is particularly focused on solving equilibrium-seeking problems in constrained and dynamic non-cooperative games, as well as Euler-Lagrange systems 🔄🧠. With expertise in reinforcement learning, deep learning, and optimization, his work integrates modern computational tools to address long-standing challenges in control science 🚀. His interest in convergence algorithms extends to real-time systems, offering broad applications in autonomous systems, multi-agent robotics, and decentralized networks 🤖🌐. His work is driven by a strong mathematical foundation and a vision for robust and scalable algorithm design 📊🧮.

🏆 Awards and Honors

Dr. OuYang has received multiple honors reflecting both academic excellence and innovation 🏅. He earned the Outstanding Undergraduate Graduate award from USTC in 2020, recognizing his stellar academic performance 🎓. His graduation project was named an Excellent Graduation Project, and he secured First-Class Graduate Scholarships in both 2020 and 2021 💸. In 2021, he won a Gold Award in the National College Student Innovation Competition for his contributions to a motion perception and positioning system 🥇. Earlier, in 2019, he received the Second Prize in the NXP Cup Intelligent Car Competition 🚗. These recognitions affirm his technical competence, creativity, and dedication to impactful research and development.

💼📘Conclusion

Dr. OuYang Binghao stands out as a dynamic and skilled researcher, combining academic excellence with practical innovation 💼📘. With a strong educational background, impactful project work, and research in high-impact areas such as game theory and fixed-time algorithms, he exhibits the qualities of a future leader in engineering and control systems 🧭. His proficiency in programming, AI integration, and control dynamics, along with international research exposure, positions him as a valuable contributor to the global research community 🌍. Dr. OuYang’s trajectory reflects not only promise but also a clear commitment to solving critical real-world problems through mathematics, computation, and collaborative research 🤝🔬..

Publication Top Notes

Title: Vertically Oriented Micron-Thick Perovskite Film Enables Efficient and Stable Inverted Perovskite Solar Cells

Authors: Bing-Hao Lv, Yong-Chun Ye, Jun-Gan Wang, Liu-Jiang Zhang, Yu-Hang Zhang, Ming-Li Zheng, Xian-Min Chen, Hui-Wei Du, Jie Yang, Xin-Yu Zhang, Meng-Lei Xu, Qiu-Feng Ye, Xingyu Gao, Jian-Xin Tang, Yongbing Tang

Year: 2025

Source: Chemical Engineering Journal, Volume 511, Article 161966CoLab

DOI: 10.1016/j.cej.2025.161966

Citation Metrics:

 

 

Liangliang Sun | Optimization | Best Researcher Award

Published on by Math Scientist

Prof. Liangliang Sun | Optimization | Best Researcher Award

Dean at Northeastern University, China

Prof. Liangliang Sun 🌟 is a distinguished scholar in control theory and intelligent scheduling systems, currently serving at Northeastern University, China 🏫. With a robust academic background including a Ph.D. from both Northeastern University and the University of Connecticut 🎓, he has cultivated deep expertise in steelmaking-continuous casting optimization, energy systems, and industrial automation ⚙️. His prolific research spans over 18 high-impact publications 📚, multiple national-level projects 🎯, and several patented innovations 🔬. Prof. Sun has earned accolades such as the Xingliao Talent Plan 🌟 and has been a two-time champion 🏆 in China’s prestigious Challenge Cup competitions. His contributions extend into teaching, editorial responsibilities 🖋️, and international collaborations 🌐. Known for integrating theory with real-world industrial applications 🔄, he bridges gaps between research and practice seamlessly. As a dynamic thought leader 🚀 in control engineering and smart manufacturing, Prof. Sun continues to inspire innovation and academic excellence across global platforms 🌍.

Professional Profile 

Scopus Profile

🎓 Education

Prof. Liangliang Sun’s academic journey is marked by scholarly excellence and international immersion 🌍. He earned his Bachelor’s and Master’s degrees in Automation and Control Engineering from Northeastern University, China 🇨🇳, laying the groundwork for a solid technical foundation. He later pursued a prestigious dual Ph.D. from Northeastern University and the University of Connecticut 🇺🇸, enriching his expertise through cross-cultural academic synergy. His doctoral research focused on intelligent optimization and industrial system control, setting the stage for impactful innovation. This global academic trajectory reflects a deep commitment to advancing modern engineering frontiers 🔬. With early exposure to cutting-edge research environments, Prof. Sun developed a unique ability to integrate Eastern precision with Western analytical frameworks, a blend that defines his distinctive academic persona 📘.

🏢 Professional Experience

Prof. Sun has cultivated an impressive professional track record in academic and applied engineering settings 🔧. Currently a full professor at Northeastern University’s School of Information Science and Engineering 🏫, he teaches and mentors in systems engineering and automation. His career includes a postdoctoral tenure at the University of Connecticut 🇺🇸, where he deepened his research in smart manufacturing. He has led numerous national research projects as Principal Investigator, collaborating with top-tier steel and energy enterprises 🏭. Beyond academia, he offers expert consultations on intelligent scheduling, production line efficiency, and energy optimization 💡. Prof. Sun also holds leadership roles in editorial boards and technical committees, actively shaping global discourse in control systems and industrial AI 📊. His trajectory exemplifies research-driven engineering leadership ⚙️.

🔍 Research Interest

Prof. Sun’s research orbits around intelligent optimization, industrial control, and smart scheduling algorithms 🚀. He explores dynamic production scheduling in steelmaking, aiming to enhance process integration, reduce emissions, and boost system efficiency 🔄. His work leverages artificial intelligence, deep learning, and energy modeling to address complex industrial challenges. With a passion for merging theory with real-world applicability 🛠️, his investigations span multi-objective optimization, cyber-physical systems, and data-driven control frameworks. He has also ventured into hydrogen-rich energy systems and low-carbon manufacturing pathways 🌱. His scientific vision aligns seamlessly with the evolving demands of Industry 4.0 and sustainable engineering 🌐. Through over 18 peer-reviewed papers, Prof. Sun has contributed significantly to reshaping production intelligence and process automation across diverse industrial landscapes 📚.

🏅 Awards and Honors

Prof. Liangliang Sun has garnered prestigious awards that reflect his academic leadership and innovation excellence 🏆. He’s a dual Champion of the National Challenge Cup, a rare feat highlighting his creativity and technical mastery early on 🧠. He is a selected recipient of the Xingliao Talent Plan, the “Hundred and Ten Thousand Talents Project”, and the Young Top Talent in Liaoning Province 🌟. Recognized nationally and provincially, he exemplifies the profile of a high-impact scholar pushing disciplinary boundaries 🚧. His awarded projects from the National Natural Science Foundation of China (NSFC) underline the national trust in his research potential 🧪. These honors demonstrate his sustained excellence in advancing automation, energy intelligence, and industrial digitization. Each accolade fortifies his status as a distinguished researcher 💼.

🧩 Conclusion

Prof. Liangliang Sun represents a remarkable blend of intellectual rigor, innovation, and practical relevance 🎯. With interdisciplinary strength across automation, AI, and energy systems, he bridges theoretical research with industrial transformation 🌐. His impactful publications, pioneering projects, and patented inventions underscore a career built on thoughtful innovation and global relevance 💡. He leads with purpose, engages in collaborative discovery, and mentors the next generation of scientific leaders 👨‍🏫. Prof. Sun’s contributions enhance the technological landscape and redefine the future of smart manufacturing and sustainable engineering 🔋. As a thought leader, he continues to shape high-impact solutions for complex industrial ecosystems, leaving a lasting imprint on global engineering science 🌟. His career is a testament to vision, resilience, and relentless pursuit of excellence 🔝.

Publications Top Notes

📘 Title: A learning-enhanced ant colony optimization algorithm for integrated planning and scheduling in hot rolling production lines under uncertainty
Authors: S. Jiang, L. He, L. Cao, L. Sun, G. Peng
Year: 2025
Citations: 1
Source: Swarm and Evolutionary Computation

📘 Title: A Self-adaptive two stage iterative greedy algorithm based job scales for energy-efficient distributed permutation flowshop scheduling problem
Authors: Y. Yu, Q. Zhong, L. Sun, X. Jing, Z. Wang
Year: 2025
Source: Swarm and Evolutionary Computation

📘 Title: Research on steelmaking-continuous casting cast batch planning based on an improved surrogate absolute-value Lagrangian relaxation framework
Authors: C. Li, L. Sun
Year: 2025
Source: International Journal of Automation and Control

📘 Title: An Online Learning-Based mACO Approach for Hot Rolling Scheduling Problems Involving Dynamic Order Arrivals
Authors: S. Jiang, Q. Liu, L. Cao, L. Sun
Year: 2025
Source: IEEE Transactions on Automation Science and Engineering

📘 Title: A robust optimization approach for steeling-continuous casting charge batch planning with uncertain slab weight
Authors: C. Li, L. Sun
Year: 2024
Citations: 1
Source: Journal of Process Control

📘 Title: Optimal control of three-dimensional unsteady partial differential equations with convection term in continuous casting
Authors: Y. Yu, Y. Wang, X. Pang, L. Sun
Year: 2024
Citations: 1
Source: Computers and Mathematics with Applications

📘 Title: Optimal Scheduling Works for Two Employees with Ordered Criteria
Authors: N.M. Matsveichuk, Y.N. Sotskov, L. Sun
Year: 2024
Source: WSEAS Transactions on Business and Economics