Jingyang Mao | Engineering | Best Researcher Award

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Dr. Jingyang Mao | Engineering | Best Researcher Award

Lecturer Shanghai Institute of Technology China

๐Ÿง‘โ€๐Ÿซ Dr. Jingyang Mao is a dedicated lecturer at the School of Electrical and Electronic Engineering, Faculty of Intelligence Technology, Shanghai Institute of Technology. With a Ph.D. in Control Science and Engineering from the University of Shanghai for Science and Technology (2022), he specializes in cutting-edge research on networked control systems and cyber-physical systems. His academic journey also includes a visiting scholar tenure at Louisiana State University, USA (2019โ€“2021). Dr. Mao’s work bridges theoretical innovations with practical applications in modern engineering systems.

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Education

๐ŸŽ“ Ph.D. in Control Science and Engineering (2022)

  • University of Shanghai for Science and Technology, Shanghai, China

โœˆ๏ธ Visiting Scholar (2019โ€“2021)

  • Department of Electrical and Computer Engineering, Louisiana State University, USA

Experience

๐Ÿ‘จโ€๐Ÿ’ป Lecturer (2022โ€“Present)

  • School of Electrical and Electronic Engineering, Shanghai Institute of Technology
  • Focus: Cyber-physical systems, networked control, and adaptive filtering

Research Interests

๐Ÿ” Dr. Mao’s research interests lie in the fields of:

  • Cyber-physical systems ๐ŸŒ
  • Multi-rate systems โฑ๏ธ
  • Joint recursive filtering ๐Ÿ”„
  • Unknown input estimation โ“
  • Adaptive event-triggered mechanisms โš™๏ธ

Awards

๐Ÿ† Award Nomination: Best Researcher Award
Recognized for groundbreaking contributions to the theory and application of cyber-physical systems.

Publications Top Notes:

๐Ÿ“„ “Recursive filtering of multi-rate cyber-physical systems with unknown inputs under adaptive event-triggered mechanisms”

Eventโ€based reducedโ€order Hโˆž$H_{\infty }$ estimation for switched complex networks based on Tโ€S fuzzy model

Recursive filtering of multi-rate cyber-physical systems with unknown inputs under adaptive event-triggered mechanisms

Event-Based Distributed Adaptive Kalman Filtering With Unknown Covariance of Process Noises

Geleta Fikadu | Engineering | Best Researcher Award

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Assist. Prof. Dr. Geleta Fikadu | Engineering | Best Researcher Award

Ph.D adama science and Technology university Ethiopia

๐ŸŽ“ Dr. Geleta Fekadu Daba, an accomplished expert in Thermal Engineering, earned his Ph.D. from the prestigious Indian Institute of Technology Roorkee (IITR) in 2020. His career spans academia, research, and engineering innovation, focusing on renewable energy systems and automotive engineering. Currently an Assistant Professor at Wollega University, Ethiopia, Dr. Daba actively contributes to energy-efficient technologies, especially solar-assisted liquid desiccant air conditioning systems.

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Education

๐ŸŽ“ Ph.D. in Thermal Engineering – Indian Institute of Technology Roorkee, India (2020)
๐ŸŽ“ M.Sc. in Automotive Engineering – Adama Science and Technology University, Ethiopia (2013)
๐ŸŽ“ B.Sc. in Automotive Technology – Adama Science and Technology University, Ethiopia (2005)

Professional Experience

๐Ÿ›  Assistant Professor, Department of Mechanical Engineering, Wollega University, Ethiopia (2015โ€“Present)

  • Delivered courses on thermodynamics, fluid mechanics, and renewable energy systems.
  • Supervised graduate students and coordinated departmental research projects.
  • Led innovative studies on solar energy applications and energy optimization.

Research Interests

๐Ÿ”ฌ Dr. Dabaโ€™s research encompasses renewable energy, automobile engineering, thermodynamics, heat and mass transfer, nano-fluids for heat transfer, and solar energy systems. His work emphasizes practical solutions for sustainable development and energy efficiency.

Awards and Recognition

๐Ÿ† Received 33 lac INR funding for his Ph.D. project on solar-assisted liquid desiccant air conditioning from the Department of Science and Technology, India.

Publications

๐Ÿ“š Dr. Daba has published extensively in reputed journals and conferences. Below are selected works with links:

Renewable energy for liquid desiccants air conditioning system: A review

Energy and Exergy Analysis of Marquise Shaped Channel Flat Plate Solar Collector Using Al2O3โ€“Water Nanofluid and Water

Comparative performance evaluation of gasoline and its blends with ethanol in gasoline engine

Liquid desiccant air conditioning using single Storage solution tank, evaporative cooling, and marquise-shaped solar collector

Study of Performance of Solar Flat Plate Collector Using Al2O3/Water Nanofluids

Experimental Study of Internallyโˆ’ Cooled Dehumidification of Liquid Desiccant for a Single Storage Tank

Energy and Exergy Analysis of Marquise Shaped Channel Flat Plate Solar Collector Using Al2O3โ€“Water Nanofluid and Water

Performance analysis of a compact liquid desiccant cooling system

Weijun Wang | Engineering | Best Researcher Award

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Dr. Weijun Wang | Engineering | Best Researcher Award

Student Changchun University of Technology China

๐ŸŒŸ Weijun Wang (็Ž‹ๅจ็บ) is a researcher in the field of Statistics, currently pursuing a Ph.D. at Changchun University of Technology, China. With expertise spanning fault diagnosis, data-driven designs, and dynamic systems, Weijun Wang has made significant contributions to high-speed train traction systems and other advanced engineering applications.

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Scopus

Education

๐ŸŽ“ Weijun Wang’s academic journey includes:

  • Ph.D. in Statistics (2021โ€“Present): Changchun University of Technology.
  • Master’s in Information and Communication Engineering (2018โ€“2021): Changchun University of Technology.
  • Bachelor’s in Electronic Information Engineering (2014โ€“2018): Changchun University of Technology.

Experience

๐Ÿ‘ฉโ€๐Ÿ”ฌ Weijun Wang has extensive experience in developing innovative fault detection methods, dynamic system models, and data-driven algorithms. Collaborating on multidisciplinary projects, she has co-authored several impactful journal and conference papers.

Research Interests

๐Ÿ”ฌ Weijun Wang’s research focuses on:

  • Fault detection and diagnosis.
  • Data-driven modeling for high-speed train traction systems.
  • Dynamic systems, robust designs, and performance prediction.

Awards

๐Ÿ† First Prize: National Finals at RAICOM, 2024.
๐Ÿ… Innovation Award: 3rd China Urban Rail Transit Science and Technology Innovation Competition, 2022.

Publications

A Martingale Posterior-Based Fault Detection and Estimation Method for Electrical Systems of Industry

Dynamic Fault Detection Method of Traction Systems in High-Speed Trains Based on Joint Observer

Data-Driven Robust Designs of Performance Prediction and Its Application in High-speed Trains

Enhanced Fault Diagnosis Using Broad Learning for Traction Systems in High-Speed Trains

State Estimation with Partial Random Walk

State-degradation-oriented fault diagnosis for high-speed train running gears system

Fault prediction of high-speed train running gears based on hidden markov model and analytic hierarchy process

Multi-sensor system filtering and fault detection under unbiased constraint and colored measurement noise