Zhiyao Zhang | Engineering | Best Researcher Award

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Prof. Zhiyao Zhang | Engineering | Best Researcher Award

Professor University of Electronic Science and Technology of China

Zhiyao Zhang is a Professor at the University of Electronic Science and Technology of China (UESTC), specializing in microwave photonics and high-speed optoelectronic devices. He earned his Ph.D. in Optical Engineering from UESTC in 2010. Currently, he serves in the School of Optoelectronic Science and Engineering and the Research Center for Microwave Photonics (RC-MWP). He was a Visiting Scholar at the University of Ottawa in 2017. His research contributions include opto-electronic oscillators, photonic analog-to-digital converters, and microwave photonic radars, with over 150 peer-reviewed journal papers published.

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Scopus

πŸŽ“ Education

  • Ph.D. in Optical Engineering – University of Electronic Science and Technology of China (UESTC), 2010
  • Visiting Scholar – Microwave Photonics Research Laboratory, University of Ottawa, 2017

πŸ’Ό Experience

  • Professor, School of Optoelectronic Science and Engineering, UESTC
  • Researcher, Research Center for Microwave Photonics (RC-MWP), UESTC
  • Visiting Scholar, Microwave Photonics Research Laboratory, University of Ottawa (2017)
  • Industry Collaboration, Partnered with Huawei Technologies Co. Ltd to develop next-generation broadband wireless base stations using Radio-over-Fiber (RoF) technology

πŸ”¬ Research Interests

  • Microwave Photonics
  • High-speed Optoelectronic Devices
  • Opto-electronic Oscillators (OEOs)
  • Photonic Analog-to-Digital Converters
  • Microwave Photonic Radars

πŸ† Awards

  • Award Nomination: Best Researcher Award
  • Research Impact: Over 960 citations
  • Patents: 20 patents (published/under process)
  • Professional Membership: Chinese Society of Optical Engineering

πŸ“š Publications Top Notes:

Zhang, Z., et al. (2023). “Ultra-wideband chaotic signal generation using nonlinear optoelectronic oscillators.” Journal of Lightwave Technology. πŸ”— Link (Cited by 45 articles)

Zhang, Z., et al. (2022). “Photonic Analog-to-Digital Conversion with Enhanced Resolution.” Optics Express. πŸ”— Link (Cited by 38 articles)

Zhang, Z., et al. (2021). “Externally-triggered ultra-wideband pulse generation in broadband nonlinear OEOs.” IEEE Transactions on Microwave Theory and Techniques. πŸ”— Link (Cited by 50 articles)

Zhang, Z., et al. (2020). “Actively Mode-Locked Optoelectronic Oscillators for Short Microwave Pulse Generation.” Nature Communications. πŸ”— Link (Cited by 72 articles)

Frequency Response Enhancement of Photonic Sampling Based on Cavity-Less Ultra-Short Optical Pulse Source

Self-referenced electro-optic response measurement of dual-parallel Mach-Zehnder modulators employing single-tone level control and low-frequency bias swing

Self-calibrated characterization of high-speed photodetectors based on slowly-varying-envelope photonic sampling

Linearization in the digital domain for photonic sampling analog-to-digital conversion

Externally-excited Short Pulse Train Generation in a Broadband Nonlinear Optoelectronic Oscillator

Optical Frequency Comb Generation Based on Single-chip Integrated LNOI Intensity and Phase Modulators

 

huayu qi | Engineering | Best Researcher Award

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Mr. huayu qi | Engineering | Best Researcher Award

Shandong University of Technology China

Qi Huayu is a dedicated researcher and master’s student at Shandong University of Technology. With a strong focus on particle morphology quantification, Qi has contributed significantly to developing innovative methods for characterizing particle structures. Through rigorous research, Qi aims to advance scientific understanding and practical applications in the field of particle analysis.

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Orcid

Education πŸŽ“

  • Master’s Degree | Shandong University of Technology

Experience πŸ‘¨β€πŸ”¬

  • Engaged in research on particle morphology quantification and regeneration.
  • Published multiple papers in high-impact scientific journals.
  • Developed quantitative analysis methods for particle characterization.

Research Interests πŸ”¬

  • Particle Morphology Quantification
  • Triangle Side Ratio Method for Angularity Characterization
  • Multi-scale Particle Morphological Analysis
  • Application of Morphology Analysis in Engineering and Material Science

Awards πŸ†

  • Best Researcher Award (Nominee, 2025)
  • Recognition for innovative contributions in particle morphology quantification.

Publications Top Notes: πŸ“š

“Particle morphology quantification and regeneration based on triangle side ratio”

Granular Matter (2025)

DOI: 10.1007/s40571-025-00919-y

Cited by: Pending citation data

“Triangle Side Ratio Method for Particle Angularity Characterization: From Quantitative Assessment to Classification Applications”

Granular Matter (2024)

DOI: 10.1007/s10035-024-01449-9

Cited by: Pending citation data

“Multi-scale morphological quantification of particle based on altitude-to-chord ratio”

 

ABDUL SAMI | Engineering | Young Scientist Award

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Mr. ABDUL SAMI | Engineering | Young Scientist Award

Lecturer Numl University Hyderabad Pakistan

Engr. Abdul Sami Shaikh is a seasoned software engineering professional with a diverse portfolio in academia, research, and freelancing. His career is marked by significant contributions to IT education, cutting-edge research, and innovative development practices. Based in Hyderabad, Sindh, Abdul Sami is driven by a passion for leveraging technology to address real-world challenges and enhance learning.

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Orcid

Education πŸŽ“

Abdul Sami Shaikh has a strong academic foundation with a Master of Engineering in Information and Communication Engineering from Harbin Engineering University, China (2013-2016), achieving an impressive 3.77 CGPA. His undergraduate degree in Computer System Engineering from Mehran University of Engineering and Technology, Jamshoro (2005-2009), laid the groundwork for his technical expertise. Earlier, he pursued Pre-Engineering at Govt. Boys Degree College, Qasimabad, Hyderabad, and completed his schooling at the Model School of Sindh University.

Experience πŸ’Ό

Abdul Sami has an extensive teaching and research background, having served as a lecturer at Isra University, National University of Modern Languages (NUML), and other prestigious institutions. His professional journey includes roles such as Research Associate at Mehran UET, Program Coordinator for the National Freelance Training Program, and editorial assistant for the Mehran UET Research Journal. He also gained valuable industrial experience through internships with organizations like Sui Southern Gas Company and Microsoft.

Research Interests πŸ”¬

His research focuses on machine learning, data visualization, deep learning, and their applications in healthcare and cybersecurity. He has explored innovative solutions in image analysis, mobile app automation for Industry 4.0, and advanced threat detection systems. Abdul Sami also delves into challenges in spatial crowdsourcing and IoT-based systems.

Awards and Recognitions πŸ†

While Abdul Sami has not listed specific awards, his academic and professional milestones, coupled with his impactful publications, position him as a strong candidate for recognition in research and innovation.

Publications Top Notes: πŸ“š

Acoustic Propagation and Transmission Loss Analysis in Shallow Water

Automated Classification of Pneumonia from Chest X-Ray Images using EfficientNet-B0

 

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

πŸŽ“ 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

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

Professional Experience

πŸ›  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

πŸ”¬ 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

πŸ† 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

πŸ“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 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 Internallyβˆ’ 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 (ηŽ‹ε¨ηΊ) 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

πŸŽ“ 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

πŸ‘©β€πŸ”¬ 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

πŸ”¬ 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

πŸ† First Prize: National Finals at RAICOM, 2024.
πŸ… 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

Brahim El Boudani | Engineering | Best Researcher Award

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Dr. Brahim El Boudani | Engineering | Best Researcher Award

Lecturer London South Bank University United Kingdom

πŸŽ“ Dr. Brahim El Boudani is a passionate researcher and educator specializing in deep learning, virtual reality, and 5G technologies. With a robust technical background in programming and data analysis, he has dedicated his career to academic excellence and innovative research. Currently, a sessional lecturer at London South Bank University, Dr. El Boudani combines teaching with impactful research in fields such as augmented reality and artificial intelligence.

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Education

πŸ“š Dr. Brahim El Boudani earned his Bachelor of Arts in Modern Letters from Hassan II University, Morocco, and later pursued advanced studies at London South Bank University. He holds a Bachelor of Science in Business Intelligence (First Class Honours) and is completing a Ph.D. on deep learning applications in 5G localization, expected by Summer 2023. His academic journey reflects a commitment to interdisciplinary excellence.

Experience

πŸ’Ό Dr. El Boudani has diverse professional experience, including roles as Workshop Supervisor at Camara Education LTD and Business Intelligence Analyst at London South Bank University. Since 2017, he has been a sessional lecturer, excelling in teaching deep learning, mobile computing, and software development while mentoring students and leading innovative extracurricular projects.

Research Interests

πŸ”¬ Dr. El Boudani’s research focuses on integrating deep learning with 5G IoT networks, indoor 3D positioning, and VR applications. His interests also include data warehousing, big databases, and the interplay of AI in mobile computing, highlighting his drive to innovate and address real-world challenges.

Awards and Achievements

πŸ† Dr. El Boudani’s exemplary academic performance, including achieving First Class Honours in Business Intelligence, has earned him accolades. His impactful research, particularly on deep learning architectures for 5G networks, has positioned him as a thought leader in his domain.

Publications Top Notes:Β 

πŸ“„ Dr. El Boudani has contributed significantly to peer-reviewed journals and conferences. His publications include:

Implementing deep learning techniques in 5G IoT networks for 3D indoor positioning (Sensors, 2020) – Cited by 50 articles.

Positioning as Service for 5G IoT Networks (ConfTELE, IEEE, 2021) – Cited by 20 articles.

SO-KDN: A Self-Organised Knowledge Defined Networks Architecture for Reliable Routing (International Conference on Information Science, 2021) – Cited by 25 articles.