Jin Liu | Algorithm Development | Best Researcher Award

Published on by Research Data Analysis

Dr. Jin Liu | Algorithm Development | Best Researcher Award

Dr. Jin Liu | Algorithm Development – University of Leeds | United Kingdom

Dr. Jin Liu is a dedicated and forward-thinking researcher in the field of railway traffic management and intelligent transportation systems. Currently serving as a Research Fellow at the Institute for Transport Studies, University of Leeds, Dr. Liu has established himself as a key contributor to the development of next-generation transport technologies. His work bridges theory and practice, especially in areas of train rescheduling, real-time traffic control, and AI-driven optimisation methods for complex railway systems. With a solid foundation in electrical engineering and deep expertise in rail operation control systems, Dr. Liu continues to push boundaries in transport innovation through multi-agent systems, digital twins, and AI applications.

Professional Profile

SCOPUS

Education

Dr. Liu began his academic journey with a Bachelor of Engineering in Electrical Engineering and Automation from the Harbin Institute of Technology, China. He then pursued his Master’s degree in Electronic and Electrical Engineering at the University of Birmingham, UK, where he completed a significant final-year project on onboard wheel slip protection systems for high-speed rail. Building on his growing interest in rail systems, Dr. Liu remained at Birmingham to complete his Ph.D., focusing on a multi-agent-based approach for resolving real-time train rescheduling problems in large-scale railway networks. His doctoral work laid the groundwork for much of his subsequent research on optimising railway traffic management using intelligent algorithms.

Professional Experience

Dr. Liu’s academic career commenced at Newcastle University as a Research Assistant and later as a Research Associate in the School of Engineering. He transitioned to the University of Leeds in March 2022, where he now contributes to multiple EU and UK-funded transportation projects. His role in these initiatives often involves the development of advanced algorithms, decision-support tools, and data models for improving operational efficiency in rail and road transport. Dr. Liu also provides leadership in technical project deliverables, industrial collaboration, and conference participation. He has built a reputation for integrating academic research with real-world applications, especially in projects related to electric vehicles, nano-emission tracking, and rail timetable optimisation.

Research Interests

Dr. Liu’s research revolves around modelling, analysis, and optimisation of rail traffic operations, including both passenger and freight services. He is particularly interested in developing energy-efficient train operations, train speed profile optimisation, and multi-agent-based modelling for traffic management. His algorithmic expertise covers both exact methods and meta-heuristic approaches, and he is deeply engaged in applying artificial intelligence—especially reinforcement learning—to real-world transportation challenges. Furthermore, his research encompasses railway system requirements analysis, focusing on RAM (Reliability, Availability, Maintainability), safety and security standards, and the verification and validation of novel railway traffic management applications.

Awards and Professional Engagements

Dr. Liu’s contributions to transport research have been recognised with several prestigious awards and professional memberships. Notably, he is the recipient of the Michael Beverley Innovation Fellowship, the International Researcher Mobility Fund, and has served as a guest speaker at the Birmingham Decarbonisation Summer School. His academic impact is evidenced by his selection as a Program Committee Member for the AI4RAILS 2023 conference and as a session chair at the IEEE ITSC 2023. He also plays a significant role in collaborative transportation initiatives, serving as the Early Career Researcher representative for the Network for Innovative Sustainable Transportation Co-Simulation. Furthermore, his work has been acknowledged among the top ten most downloaded papers of 2023 in his field.

Dr. Liu is an Associate Fellow of the UK’s Higher Education Academy and maintains an active publishing profile, with his research appearing in prestigious journals such as Applied Sciences, IET Intelligent Transport Systems, and Journal of Rail Transport Planning & Management. His research output includes notable work on reinforcement learning applications in train scheduling, system validation in virtual environments, and the assessment of railway operation impacts under hazardous conditions. Through his ongoing projects with European and UK stakeholders—such as Shift2Rail, Network Rail, and the EPSRC—Dr. Liu continues to contribute meaningfully to shaping the future of sustainable, intelligent, and resilient transportation systems.

Publications

A Multi-agent Based Approach for Railway Traffic Management Problems

Authors: J. Liu, L. Chen, C. Roberts, Z. Li, T. Wen
Journal/Conference: 2018 International Conference on Intelligent Rail Transportation (ICIRT)
Year: 2019

Algorithm and peer-to-peer negotiation strategies for train dispatching problems in railway bottleneck sections

Authors: J. Liu, L. Chen, C. Roberts, G. Nicholson, B. Ai
Journal: IET Intelligent Transport Systems
Year: 2019

Use cases for obstacle detection and track intrusion detection systems in the context of new generation of railway traffic management systems

Authors: P. Hyde, C. Ulianov, J. Liu, M. Banic, M. Simonovic, D. Ristic-Durrant
Journal: Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
Year: 2021

Novel approach for validation of innovative modules for railway traffic management systems in a virtual environment

Authors: J. Liu, C. Ulianov, P. Hyde, A. L. Ruscelli, G. Cecchetti
Journal: Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
Year: 2022

Formalization and Processing of Data Requirements for the Development of Next Generation Railway Traffic Management Systems

Authors: A. Magnien, G. Cecchetti, A. L. Ruscelli, P. Hyde, J. Liu, S. Wegele
Journal: Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification (Book/Conference Proceedings)
Year: 2022

Asifa Yesmin | Robust controller in resource constraint scenario | Excellence IN Research

Published on by Research Data Analysis

Asifa Yesmin | Excellence in Research Award Winner 2023  🏆

Dr. Asifa Yesmin : Robust controller in resource constraint scenario

Dr. Asifa Yesmin, Congratulations on being awarded the Excellence in Research Award for your work on "Robust Controller in Resource Constraint Scenario." Your outstanding contributions have earned you international recognition at the Research Data Analysis Excellence Awards. Well-deserved honor!

Professional profile:

Early Academic Pursuits:

Asifa Yesmin embarked on her academic journey with a Bachelor's in Power Electronic & Instrumentation from Jorhat Institute of Science & Technology in 2013, securing an impressive 81.2%. Following this, she pursued a Master's in Electronic Design and Technology at Tezpur University, achieving a notable percentage of 89.7 in 2016. Her academic prowess continued with a Ph.D. in Control System and Application at the National Institute of Technology Silchar, culminating in 2021.

Professional Endeavors:

With a solid academic foundation, Asifa delved into research and academia. She served as a Post Doctoral Fellow at the SysCon, Indian Institute of Technology Bombay, contributing to projects like Software-In-The-Loop validation of super twisting-based sliding mode control for quadcopters. Her expertise extended to designing sliding mode controllers for quadcopters, exploring various methodologies and conducting software-in-the-loop simulations.

During her tenure as a Research Scholar at the National Institute of Technology Silchar, Asifa contributed significantly to projects involving event-triggered sliding mode controllers. Her work spanned topics such as reaching law-based event-triggered sliding mode control, dynamic event-triggered sliding mode control, and static event-triggered integral sliding mode control.

As a PG Student at Tezpur University, Asifa showcased her practical skills by designing a GSM-based automatic cooking machine with a frying feature. Her undergraduate project involved creating an automatic parking system, highlighting her versatility in both hardware and software-based projects.

Contributions and Research Focus:

Asifa Yesmin's research primarily centers around control systems, with a specific focus on sliding mode controllers, event-triggered control, multi-agent systems, unmanned aerial vehicles, path planning, and robotics. Her expertise extends to areas such as linear control theory, network theory, nonlinear systems, and digital and analog electronics.

Her contributions include the design and performance analysis of sliding mode controllers for quadcopters, exploring various sliding mode controller designs for multi UAVs, and investigating dynamic triggering mechanisms for sliding mode control.

Accolades and Recognition:

Asifa's academic journey has been marked by achievements such as securing the 1651st rank in GATE 2016 and being a recipient of the Research Fellowship from MHRD, Government of India, from 2016 to 2021. She also received the Student Travel Fund (IRC-STF) from IEEE Region 10 in 2019.

Her contributions as a reviewer for prestigious journals like European Journal of Control, Fuzzy Sets and Systems, Neural Network, Scientific Reports, and Isa Transaction underscore her standing in the academic community.

Impact and Influence:

Asifa's impact is evident not only through her research but also in her teaching roles. As a Teaching Assistant at NIT Silchar, she contributed to courses in control system, industrial process control, and virtual instrumentation, showcasing her commitment to knowledge dissemination.

Her involvement in organizing national workshops and workshops on topics like homogeneity-based design of sliding mode controllers and robustness control demonstrates her dedication to fostering academic growth beyond her research.

Legacy and Future Contributions:

Asifa Yesmin's legacy lies in her multifaceted contributions to academia and research. Her work on sliding mode controllers and event-triggered control sets a foundation for future advancements in control system theory and applications. With her diverse skill set and extensive research experience, she is poised to continue making significant contributions to the field, leaving a lasting impact on control systems and related domains.

Notable publication :