Bin Yang – AI for Everything – Best Researcher Award

Bin Yang - AI for Everything - Best Researcher Award

Chongqing University of Posts and Telecommunications - China

AUTHOR PROFILE

SCOPUS

ORCID

πŸ§‘β€πŸ« ACADEMIC BACKGROUND AND RESEARCH PASSION

Dr. Bin Yang, also known as Sean Bin Yang, is an Assistant Professor at Chongqing University of Posts and Telecommunications. With a deep passion for leveraging big data and artificial intelligence (AI) to address urban challenges, he has been making significant contributions to the field. He is also a member of the Chongqing Key Laboratory of Image Cognition, working closely with Prof. Xinbo Gao.

πŸŽ“ EDUCATION AND GLOBAL COLLABORATIONS

Dr. Yang obtained his Ph.D. in Computer Science from Aalborg University in 2022, under the guidance of Prof. Bin Yang and Associate Prof. Jilin Hu. During his doctoral studies, he collaborated with renowned researchers at the Center for Data-Intensive Systems (Daisy) and the Machine Learning Group. He also spent time at the Mila-Quebec AI Institute in Canada, working with Associate Prof. Jian Tang.

πŸ“š PROLIFIC PUBLICATION RECORD

Dr. Yang has authored more than 20 peer-reviewed publications in prestigious international journals and conferences, including KDD, ICML, and TKDE. His work, such as the development of lightweight path representation models, has gathered over 452 citations, with an h-index of 13. His innovative research in data mining, machine learning, and AI continues to push the boundaries of knowledge in these fields.

πŸ’‘ INNOVATIVE PATENTS AND TECHNOLOGY APPLICATIONS

Dr. Yang's commitment to practical applications of his research is demonstrated by his filing of over 10 patents in China. These patents reflect his dedication to advancing technology through innovation, particularly in the fields of AI-driven solutions for urban and transportation challenges.

πŸŽ“ SUPERVISION AND MENTORSHIP

As a dedicated mentor, Dr. Yang has supervised numerous student research projects, including those on construction waste management through AI techniques. His guidance has led to the publication of impactful research articles, helping his students make meaningful contributions to the field of artificial intelligence and urban problem-solving.

πŸ”¬ RESEARCH IN AI AND URBAN CHALLENGES

Dr. Yang's research focuses on using AI to tackle complex urban issues, such as waste management, transportation optimization, and infrastructure development. His work in path representation learning, unsupervised learning, and predictive autoscaling has significantly contributed to the advancement of smart city technologies.

πŸ… CONFERENCE AND JOURNAL INVOLVEMENT

Dr. Yang is an active member of the research community, serving as a Program Committee member for top conferences like ICML, KDD, and IJCAI. His expertise is frequently sought as a reviewer for leading journals such as IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Intelligent Transportation Systems, highlighting his influence in the AI and big data research domains.

NOTABLE PUBLICATION

Title:Extended-state-observer-based double-loop integral sliding-mode control of electronic throttle valve
Authors: Y. Li, B. Yang, T. Zheng, Y. Li, M. Cui, S. Peeta
Journal: IEEE Transactions on Intelligent Transportation Systems
Year: 2015

Title: Unsupervised path representation learning with curriculum negative sampling
Authors: S.B. Yang, C. Guo, J. Hu, J. Tang, B. Yang
Journal: arXiv preprint arXiv:2106.09373

Title: Context-aware path ranking in road networks
Authors: S.B. Yang, C. Guo, B. Yang
Journal: IEEE Transactions on Knowledge and Data Engineering
Year: 2020

Title: Luenberger-sliding mode observer based fuzzy double loop integral sliding mode controller for electronic throttle valve
Authors: B. Yang, M. Liu, H. Kim, X. Cui
Journal: Journal of Process Control
Year: 2018

Title: An extended continuum model incorporating the electronic throttle dynamics for traffic flow
Authors: Y. Li, H. Yang, B. Yang, T. Zheng, C. Zhang
Journal: Nonlinear Dynamics
Year: 2018

Jia Song – Intelligence theory and applications – Best Researcher Award

Jia Song - Intelligence theory and applications - Best Researcher Award

School of Astronautics, Beihang University - China

AUTHOR PROFILE

SCOPUS

πŸŽ“ ACADEMIC BACKGROUND AND EXPERTISE

Jia Song earned her B.S. degree in Electrical Engineering and Automation, and Intelligent Systems from Harbin Engineering University in 2005, followed by a Ph.D. in Control Theory and Control Engineering from the same institution in 2009. Her profound expertise in these fields laid the foundation for her future endeavors in advanced control systems and intelligent decision-making.

πŸ›οΈ PROFESSOR AND DOCTORAL SUPERVISOR

Currently a Professor and doctoral supervisor at the School of Astronautics, Beihang University, Jia Song plays a crucial role in shaping the next generation of engineers and researchers. Her work focuses on advanced flight control systems and collaborative decision-making, where she mentors doctoral students, guiding them through complex research challenges.

πŸš€ RESEARCH IN ADVANCED FLIGHT CONTROL

Jia Song's research is centered on the development of advanced flight control systems, particularly in high-stakes scenarios involving high dynamic vehicles. Her studies address critical issues such as control precision and margin adequacy in environments with multiple constraints, such as no-fly zones and high-velocity interceptors, making significant strides in the field of aerospace engineering.

🎯 INNOVATIVE PENETRATION GAME STRATEGY

One of her notable contributions is the investigation of penetration game strategies for high dynamic vehicles. Her innovative approach involves an enhanced artificial potential field method that improves lateral penetration guidance strategies, effectively balancing obstacle avoidance and target reachability. This research not only advances theoretical understanding but also offers practical solutions for real-world applications.

πŸ”§ APPLICATION OF ARTIFICIAL INTELLIGENCE AND PREDICTIVE MODELS

Jia Song integrates advanced artificial intelligence techniques, such as the Kalman filter and Transformer network, into her research. These tools are used to denoise detection information and predict multi-step state outcomes, significantly increasing the success rate of high dynamic vehicles in confronting high-velocity interceptors. Her work exemplifies the fusion of AI with traditional engineering to solve complex problems.

πŸ“Š NUMERICAL SIMULATIONS AND VALIDATION

Her research is rigorously validated through numerical simulations, which demonstrate the effectiveness and performance of the proposed penetration game guidance strategies. These simulations confirm the practicality and reliability of her methods, ensuring that they can be applied to real-world scenarios with confidence.

πŸ† CONTRIBUTIONS TO AEROSPACE ENGINEERING

Jia Song’s contributions to aerospace engineering, particularly in the areas of flight control and collaborative decision-making, are highly regarded in the academic and professional communities. Her innovative research and commitment to excellence continue to push the boundaries of what is possible in the field of astronautics, making her a leading figure in her domain.

NOTABLE PUBLICATION

ADRC-Based Compound Control Strategy for Spacecraft Multi-Body Separation
Authors: Hu, Y., Wu, M., Zhao, K., Song, J., He, B.
Year: 2023
Journal: Aerospace Science and Technology

Survey on Mission Planning of Multiple Unmanned Aerial Vehicles
Authors: Song, J., Zhao, K., Liu, Y.
Year: 2023
Journal: Aerospace

Time-Cooperative Trajectory Optimization Method for Hypersonic Vehicle Based on Improved Grey Wolf Artificial Potential Field Method
Authors: Teng, B., Xu, X., Song, J.
Year: 2023
Conference: 2023 China Automation Congress (CAC 2023)

Fault Location and Separation Method of Distributed Inertial Measurement Units Based on IAC
Authors: Song, J., Shang, W., Wu, B., Ai, S.
Year: 2023
Conference: 2023 10th International Conference on Dependable Systems and Their Applications (DSA 2023)

Real-Time Trajectory Planning for Hypersonic Vehicle with Dynamic No-Fly Zone Constraints
Authors: Xiaowei, X., Jia, S., Kai, Z., Xindi, T., Yanxue, Z.
Year: 2023
Book Series: Lecture Notes in Electrical Engineering (LNEE)