Soroush Zare | Engineering | Best Researcher Award

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Dr. Soroush Zare | Engineering | Best Researcher Award

Greadaute Research Assistant University of Virginia United States

📚 Soroush Zare is a dedicated Ph.D. Candidate in Mechanical and Aerospace Engineering at the University of Virginia. With expertise in robotics, soft exoskeletons, and Brain-Computer Interface (BCI) technologies, he specializes in designing advanced systems for rehabilitation and assistive applications. His research integrates AI-driven controls with cutting-edge mechanical design.

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Education

🎓 University of Virginia (2023–Present)

  • Ph.D. in Mechanical and Aerospace Engineering (GPA: 4.0/4.0)
  • Focus: EEG-based motor imagery for wearable textile robotics under an NSF-funded project.

🎓 University of Tehran (2018–2021)

  • M.S. in Mechanical Engineering (GPA: 3.9/4.0)
  • Thesis: Deep Reinforcement Learning Control of Suspended Cable-Driven Robots.

🎓 Shiraz University (2014–2018)

  • B.S. in Mechanical Engineering (GPA: 3.6/4.0)
  • Thesis: Modeling and analysis of bladeless wind turbines.

Experience

💼 Research Assistant, University of Virginia (2023–Present)

  • Developed wearable soft rehabilitation exoskeletons integrating EEG technologies.
  • Innovated reinforcement learning frameworks for intuitive robotic control.

💼 Research Assistant, York University (2022–2023)

  • Led projects on robotic grasping using deep reinforcement learning.

💼 Research Assistant, University of Tehran (2018–2022)

  • Advanced control techniques for Cable-Driven Parallel Robots (CDPRs).

Research Interests

🔬 Robotics, soft exoskeletons, Brain-Computer Interface (BCI) technologies, deep reinforcement learning, EEG-based motor imagery classification, and AI-driven assistive technologies.

Awards

🏆 Honors & Achievements

  • NSF Student Travel Award, IEEE/ACM CHASE (2024)
  • GRADESTAR Fellowship (2023, 2024)
  • Chairperson’s Fellowship (2023)
  • Ranked 2nd among solid design students at Shiraz University.

Publications Top Notes: 

📄 Recent Publications

NeuroMotion: EEG-Based Motor Imagery Control of Wearable Exoskeleton (In preparation).

Kinematic analysis of an under-constrained cable-driven robot using neural networks

Wearable upper limb robotics for pervasive health: A review

Experimental study on the control of a suspended cable-driven parallel robot for object tracking purpose

Reconstructing 3-D Graphical Model Using an Under-Constrained Cable-Driven Parallel Robot

Understanding Human Motion Intention from Motor Imagery Eeg Based on Convolutional Neural Network

A Low-Cost Wearable Exoskeleton for Sitting and Standing Assistance

EEG Motor Imagery Classification using Integrated Transformer-CNN for Assistive Technology Control

MIMO Dynamic Control of a Suspended Underactuated Cable Robot Using Genetic Algorithm

 

 

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

🎓 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

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

Professional Experience

🛠 Assistant Professor, Department of Mechanical Engineering, Wollega University, Ethiopia (2015–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

🔬 Dr. Daba’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

🏆 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

📚 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 Al2O3–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 Internally− Cooled Dehumidification of Liquid Desiccant for a Single Storage Tank

Energy and Exergy Analysis of Marquise Shaped Channel Flat Plate Solar Collector Using Al2O3–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

🌟 Weijun Wang (王威珺) 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

🎓 Weijun Wang’s academic journey includes:

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

Experience

👩‍🔬 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

🔬 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

🏆 First Prize: National Finals at RAICOM, 2024.
🏅 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

Yusuf Alper KAPLAN | Engineering | Best Researcher Award

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Prof. Yusuf Alper KAPLAN | Engineering | Best Researcher Award

Prof. Osmaniye Korkut Ata Unv. Turkey

Dr. Yusuf Alper Kaplan is a Professor of Energy Systems Engineering at Osmaniye Korkut Ata University in Turkey. He has a distinguished career in renewable energy, specializing in solar and wind energy modeling, estimation, and system performance. With over two decades of experience, Dr. Kaplan has contributed to advancing energy systems through innovative methodologies and predictive models.

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Education 🎓

  • Bachelor’s in Electrical and Electronics Engineering, Gaziantep University, 2002
  • Master’s in Electrical and Electronics Engineering, Çukurova University, 2008
  • Ph.D. in Electrical and Electronics Engineering, Anadolu University, 2014

Professional Experience 💼

  • Lecturer (2004-2009) at Çukurova University
  • Research Assistant (2010-2014) at Anadolu University
  • Assistant Professor (2014-2018), Associate Professor (2018-2023), and Professor (2023-present) at Osmaniye Korkut Ata University
  • Head of Department of Energy Systems Engineering (2019-2020)
  • Director of the Continuing Education Centre (2020-present)

Research Interests 🔬

Dr. Kaplan’s research focuses on renewable energy, especially solar and wind energy systems. His work involves developing statistical and computational models for solar radiation forecasting, wind energy assessment, and performance optimization of renewable energy sources in varying environmental conditions.

Awards and Recognitions 🏆

Dr. Kaplan has been honored for his contributions to renewable energy and academic excellence. His achievements include national and international recognitions for advancements in energy system performance modeling and contributions to sustainable energy solutions.

Publications Top Notes: 📚

Kaplan, Y. A. (2024). Forecasting of global solar radiation: A statistical approach using simulated annealing algorithm. Engineering Applications of Artificial Intelligence, 136, 109034. (Cited by 15)

Kaplan, A. G., & Kaplan, Y. A. (2024). Using of the Weibull distribution in developing global solar radiation forecasting models. Environmental Progress & Sustainable Energy. (Cited by 10)

Kaplan, Y. A. (2023). Development of backpropagation algorithm for estimating solar radiation: A case study in Turkey. Revue Roumaine des Sciences Techniques, 68(3), 313-316. (Cited by 8)