Dr. Mojtaba Ahmadieh khanesar | Metrology | Best Researcher Award

Dr. Mojtaba Ahmadieh khanesar | Metrology | Best Researcher Award 

Dr. Mojtaba Ahmadieh khanesar | Metrology | University of Nottingham | United Kingdom

Dr. Mojtaba Ahmadieh Khanesar is a distinguished research fellow in optical metrology and machine learning at the Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham. He holds a Ph.D. in Control Engineering from K. N. Toosi University of Technology and has extensive experience in metrology, robotics, control systems, artificial intelligence, and machine learning. Throughout his career, Dr. Khanesar has contributed to internationally recognized projects funded by EPSRC, including Robodome imaging for high-performance aerostructures, HARISOM for precise industrial robot manipulation, and Chattyfactories for next-generation industrial systems, demonstrating proficiency in experimental design, data acquisition, and real-time control using advanced robotics platforms such as UR5, Baxter, Sawyer, and laser tracking systems. He has also supervised Ph.D. and undergraduate students, providing mentorship in control, robotics, and machine learning projects, and delivered lectures on Bayesian learning and reinforcement learning at the University of Nottingham. Dr. Khanesar has held research and teaching positions across Denmark, Turkey, Iran, and the United Kingdom, reflecting his global research engagement and collaborative approach. His research has been widely published, with 112 documents, 2,377 citations, and an h-index of 25, including publications in high-impact journals such as IEEE Transactions, Robotics, Mechanism and Machine Theory, and Sensors. His professional affiliations include SMIEEE, MIET, and MASME, highlighting his recognized standing in international technical communities.

Professional Profile: ORCID | Scopus

Selected Publications 

  1. Ahmadieh Khanesar, M. (2025). Inkjet printing of ZIF-67 based-polymer composite membranes. Separation and Purification Technology. 0 citations.

  2. Ahmadieh Khanesar, M. (2025). Multi-Objective Intelligent Industrial Robot Calibration Using Meta-Heuristic Optimization Approaches. Robotics. 0 citations.

  3. Ahmadieh Khanesar, M. (2025). Virtual Instrument for a Multi-illumination Dome System. Conference Paper. 0 citations.

  4. Ahmadieh Khanesar, M. (2023). Precision Denavit–Hartenberg Parameter Calibration for Industrial Robots Using a Laser Tracker System and Intelligent Optimization Approaches. Sensors, Basel, Switzerland. 25 citations.

  5. Ahmadieh Khanesar, M. (2023). A Neural Network Separation Approach for the Inclusion of Static Friction in Nonlinear Static Models of Industrial Robots. IEEE ASME Transactions on Mechatronics. 9 citations.

Dr. Yuyin Ma | Industrial Internet Awards | Best Innovation Award

Dr. Yuyin Ma | Industrial Internet Awards | Best Innovation Award 

Dr. Yuyin Ma, Beijing Jiaotong University, China

Ma Yuyin is a dedicated Ph.D. candidate in Information and Communication Engineering at Beijing Jiaotong University, with an anticipated graduation date in July 2025. Shandong Province, he has a strong academic foundation, having completed his undergraduate studies in Software Engineering at China University of Petroleum (Beijing). As a member of the Communist Party of China, he actively engages in innovative projects for graduate students at central universities, contributing significantly to national key R&D plans and major natural projects. Notably, he led a team in a National Nature Focus project that developed a new industrial internet architecture, demonstrating his expertise in designing collaborative clustering methods and optimizing network resource management through digital twin technology. With a robust programming background, he has produced substantial contributions to research, including over 2,000 lines of Python code and extensive data analysis. Ma possesses strong self-motivation and execution abilities, solid writing skills, and effective communication and coordination capabilities, making him a valuable asset in the fields of computer networking, technology, and scientific research.

Professional Profile:

SCOPUS

Suitability for the Research for Best Innovation Award: Ma Yuyin

Ma Yuyin demonstrates exceptional qualifications for the Research for Best Innovation Award through his extensive academic and project experience in information and communication engineering. His educational journey at Beijing Jiaotong University, where he is pursuing a Doctorate in Electronic Information Engineering, and his foundational studies in Software Engineering at the China University of Petroleum (Beijing), showcase a strong technical background essential for innovative research.

🎓 Education

  • Beijing Jiaotong University
    Doctor of Information and Communication Engineering
    September 2020 – July 2025
  • China University of Petroleum (Beijing)
    Undergraduate Course in Software Engineering
    September 2016 – June 2020

💼 Work Experience

  • Project Leader
    In charge of innovative projects for graduate students at central universities
    – Successfully completed major national projects with a funding of 15 million yuan, collaborating with Academician Zhang Hongke as the project leader.
    – Led national key R&D plans and major natural projects under the supervision of a tutor.
    – Developed a new industrial Internet architecture with controllable performance across multiple scenarios.

🌟 Achievements

  1. National Nature Focus – No: 62072030
    • Developed a new industrial Internet architecture for various applications, contributing approximately 2,000 lines of Python code and collecting nearly 160,000 pieces of data.
  2. Research Contributions
    • Designed a collaborative clustering method for heterogeneous terminals to ensure low power consumption and reliable data transmission.
    • Proposed an intelligent collaborative clustering method that outperformed competitors in over 10,000 experiments.
  3. Privacy and Security Research
    • Developed an adaptation mapping simulation platform to identify security vulnerabilities in service response time, implementing a multi-node confusion mechanism.

🏆 Awards and Honors

  • Excellent Completion Award
    • For leading innovative projects with outstanding results.
  • Recognition for Contributions to National Key R&D Plans
    • Acknowledged for significant contributions to the field of digital twins and resource optimization in network management.

Publication Top Notes:

ScaIR: Scalable Intelligent Routing based on Distributed Graph Reinforcement Learning

Adaptive Service Provisioning for Dynamic Resource Allocation in Network Digital Twin

Smart Collaborative Evolvement for Virtual Group Creation in Customized Industrial IoT

Exploring Reliable Decentralized Networks with Smart Collaborative Theory

Security Association Model: Interdisciplinary Application of 5G Positioning Technology and Social Network

Smart Collaborative Contract for Endogenous Access Control in Massive Machine Communications