Liangliang Sun | Optimization | Best Researcher Award

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 πŸŽ“, he has cultivated deep expertise in steelmaking-continuous casting optimization, energy systems, and industrial automation βš™οΈ. His prolific research spans over 18 high-impact publications πŸ“š, multiple national-level projects 🎯, and several patented innovations πŸ”¬. Prof. Sun has earned accolades such as the Xingliao Talent Plan 🌟 and has been a two-time champion πŸ† in China’s prestigious Challenge Cup competitions. His contributions extend into teaching, editorial responsibilities πŸ–‹οΈ, and international collaborations 🌐. Known for integrating theory with real-world industrial applications πŸ”„, he bridges gaps between research and practice seamlessly. As a dynamic thought leader πŸš€ in control engineering and smart manufacturing, Prof. Sun continues to inspire innovation and academic excellence across global platforms 🌍.

Professional ProfileΒ 

Scopus Profile

πŸŽ“ 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 πŸ‡¨πŸ‡³, laying the groundwork for a solid technical foundation. He later pursued a prestigious dual Ph.D. from Northeastern University and the University of Connecticut πŸ‡ΊπŸ‡Έ, 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 πŸ”¬. 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 πŸ“˜.

🏒 Professional Experience

Prof. Sun has cultivated an impressive professional track record in academic and applied engineering settings πŸ”§. 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 πŸ‡ΊπŸ‡Έ, 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 πŸ’‘. Prof. Sun also holds leadership roles in editorial boards and technical committees, actively shaping global discourse in control systems and industrial AI πŸ“Š. His trajectory exemplifies research-driven engineering leadership βš™οΈ.

πŸ” Research Interest

Prof. Sun’s research orbits around intelligent optimization, industrial control, and smart scheduling algorithms πŸš€. He explores dynamic production scheduling in steelmaking, aiming to enhance process integration, reduce emissions, and boost system efficiency πŸ”„. 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 πŸ› οΈ, 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 πŸ“š.

πŸ… Awards and Honors

Prof. Liangliang Sun has garnered prestigious awards that reflect his academic leadership and innovation excellence πŸ†. 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 πŸ§ͺ. These honors demonstrate his sustained excellence in advancing automation, energy intelligence, and industrial digitization. Each accolade fortifies his status as a distinguished researcher πŸ’Ό.

🧩 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 πŸ’‘. He leads with purpose, engages in collaborative discovery, and mentors the next generation of scientific leaders πŸ‘¨β€πŸ«. Prof. Sun’s contributions enhance the technological landscape and redefine the future of smart manufacturing and sustainable engineering πŸ”‹. 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 πŸ”.

Publications Top Notes

πŸ“˜ 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


πŸ“˜ 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


πŸ“˜ 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


πŸ“˜ 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


πŸ“˜ 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


πŸ“˜ 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


πŸ“˜ 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