Ms. Lixiang Chen | Analysis Award | Best Researcher Award

Posted on 16/10/2025 by Global Sensor Awards

Ms. Lixiang Chen | Analysis Award | Best Researcher Award

Ms. Lixiang Chen | Analysis Award | Taiyuan University of Technology | China

Ms. Lixiang Chen is an accomplished researcher and academician currently serving at Taiyuan Institute of Technology, China, where she has been a dedicated faculty member contributing to the advancement of economic and technological research. With a Ph.D. in Economics, Ms. Lixiang Chen has developed extensive expertise in innovation networks, performance budgeting systems, defense resource allocation, and strategic economic management, emphasizing how macroeconomic frameworks can optimize technological growth and policy execution. Her academic journey has been marked by her deep analytical insight into economic behavior modeling and technology policy development, enabling her to bridge the gap between theoretical economics and practical industrial applications. Professionally, Ms. Chen has participated in multiple interdisciplinary projects and international collaborations that explore the intersection of innovation economics, resource allocation mechanisms, and the emerging new energy vehicle industry, contributing significantly to both academic and policy discourse. Her research interests include innovation networks within industrial ecosystems, performance-based budgeting for governmental and defense sectors, and sustainable economic planning, all of which align closely with the global shift toward smart and sustainable economic transformation. In terms of research skills, Ms. Chen is proficient in quantitative data analysis, econometric modeling, policy evaluation, and cross-disciplinary research synthesis, enabling her to produce impactful, data-driven research outcomes that are both academically rigorous and policy-relevant. Her body of work has been recognized through multiple peer-reviewed publications in high-impact journals indexed in Scopus and IEEE, establishing her as a respected contributor to the fields of economics, technology management, and innovation systems.

Professional Profile: ORCID

Selected Publications

Chen, L. (2025). Innovation Networks in the New Energy Vehicle Industry: A Dual Perspective of Collaboration Between Supply Chain and Executive Networks. World Electric Vehicle Journal. Cited by: 3
Chen, L. (2021). The Evolution and Implications of the Planning, Programming, Budgeting, and Execution System. China Economist. Cited by: 8
Chen, L. (2021). The Impact of Performance Budgeting on Defense Resource Allocation. International Journal of Economic Behavior and Organization. Cited by: 12
Chen, L. (2020). PPBE: Research on Operation and Latest Development. American Journal of Theoretical and Applied Business. Cited by: 6
Chen, L. (2020). The U.S. Department of Defense’s “Medium-Term Expenditure Framework” and Its Implications. National Defense Science & Technology. Cited by: 5

Mr. Xincheng Guo | Time Series Awards | Best Machine Learning for Sensing Award

Posted on 21/05/2025 by Global Sensor Awards

Mr. Xincheng Guo | Time Series Awards | Best Machine Learning for Sensing Award

Mr. Xincheng Guo, Shanghai University of Engineering Science, China

Xincheng Guo is a graduate student pursuing a Master’s degree in Electronic Information at Shanghai University of Engineering Science, with research focused on intelligent signal processing, deep learning, and IoT systems. His notable contributions include the development of an innovative CEEMDAN-WT-VMD framework for multi-source noise suppression in power load data and the design of advanced neural network models such as Bidirectional Temporal Convolutional Networks and Attention-based BiGRU for spatiotemporal modeling and signal denoising. He has published first-authored research on short-term power load forecasting in the journal Electronics (2025, Q1). Xincheng has also engineered a multi-sensor fire detection and patrol system integrating improved YOLOv5s vision algorithms with sensor fusion and high-precision positioning technologies. His technical expertise spans sensing algorithms, embedded systems, and AI frameworks like PyTorch and TensorFlow. He has received multiple honors, including the 2nd Prize in the 19th China Graduate Electronics Design Competition (Shanghai Division) and the National Graduate Scholarship.

Professional Profile:

ORCID

Summary of Suitability for Best Machine Learning for Sensing Award conclusion

Xincheng Guo is a highly promising candidate for the Research for Best Machine Learning for Sensing Award, demonstrating strong expertise in intelligent signal processing and deep learning applied to multi-modal sensing systems. Currently pursuing a Master’s degree in Electronic Information at Shanghai University of Engineering Science, Guo has developed innovative methods for sensing signal denoising and prediction, including a novel CEEMDAN-WT-VMD framework that achieves significant noise reduction and a Bidirectional Temporal Convolutional Network that outperforms state-of-the-art models in power load forecasting. His research is supported by the National Natural Science Foundation of China, reflecting its scientific merit and relevance. Beyond theoretical contributions, Guo has designed practical embedded sensing systems integrating advanced vision algorithms and multi-sensor fusion for real-time fire detection, showcasing his ability to translate machine learning innovations into impactful applications. With published Q1 journal papers, recognized technical skills in AI frameworks, and awards in national electronics competitions, Xincheng Guo embodies the excellence and innovation that the Best Machine Learning for Sensing Award seeks to honor.

🎓 Education

Master of Electronic Information (2023.09 – 2026.09)
Shanghai University of Engineering Science
Focus: Intelligent Signal Processing, Deep Learning, IoT Systems

💼 Work Experience

Graduate Student
China Education and Research Network (CERNET), Beijing (Since 2023.09)

🏆 Achievements & Key Contributions

Developed CEEMDAN-WT-VMD framework for multi-source noise suppression, achieving a 46.3% noise reduction (SNR 227.1 dB)
Created Bidirectional Temporal Convolutional Network (BiTCN) with 0.65% MAPE on power load forecasting, outperforming top models
Designed an Attention-based BiGRU model for dynamic temporal feature weighting in noisy data
Published first-author paper:
“Short-Term Power Load Forecasting Based on CEEMDAN-WT-VMD Joint Denoising” in Electronics (2025, Q1, IF=3.0)
Built a Multi-Sensor Fire Detection and Patrol System using Raspberry Pi and MM32 with improved YOLOv5s vision algorithm (+8.2% mAP), flame/smoke sensor fusion, and GPS positioning

🎖️ Awards & Honors

🥈 2nd Prize, 19th China Graduate Electronics Design Competition (Shanghai Division), 2024
🥉 3rd Prize, 6th Yangtze River Delta Smart City Competition, 2024
🎓 National Graduate Scholarship, 2023-2024
🛫 Aerospace Inspirational Scholarship, 2022-2023
🏅 CET-4 Certificate (English Proficiency)
💻 National Computer Technology and Software Professional Qualification (Primary Level)

Publication Top Notes:

Short-Term Power Load Forecasting Based on CEEMDAN-WT-VMD Joint Denoising and BiTCN-BiGRU-Attention

Mr. Amgad Gerges | Ratio Awards | Best Researcher Award

Posted on 20/05/2025 by Global Sensor Awards

Mr. Amgad Gerges | Ratio Awards | Best Researcher Award

Mr. Amgad Gerges, London Metropolitan University, United Kingdom

Dr. Daniel Sykes is the Head of Chemical and Pharmaceutical Sciences at the School of Human Sciences, London Metropolitan University. He serves as an Editorial Board Member for Frontiers in Chemistry, contributing to the advancement of research and scholarship in the field. Dr. Sykes is based at the Tower Building on Holloway Road, London, where he leads academic programs and research initiatives focused on chemical and pharmaceutical sciences. His leadership role encompasses curriculum development, faculty coordination, and fostering collaborative research within the university and with external partners. Dr. Sykes is widely recognized for his expertise and commitment to education and research excellence in chemistry and pharmaceutical disciplines.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award: Amgad Gerges

Dr. Amgad Gerges is a highly accomplished Senior Lecturer in Biomedical Science at London Metropolitan University with over two decades of extensive experience in biomedical and medicinal chemistry research, education, and clinical practice. His academic credentials include an MSc in Medicinal Chemistry, BSc (Hons) in Biomedical Science, and a BSc in Chemistry, complemented by professional qualifications such as FHEA and PGCert, which demonstrate his commitment to academic excellence and teaching quality.

🎓 Education

Likely holds a Ph.D. or equivalent in Chemical or Pharmaceutical Sciences (exact degrees not explicitly provided, but typical for head of department role and editorial board membership).
Background in Chemistry, Pharmaceutical Sciences, or a closely related field.

💼 Work Experience

Head of Chemical and Pharmaceutical Sciences, London Metropolitan University — Leading the department, managing academic programs, research initiatives, and staff.
Editorial Board Member, Frontiers in Chemistry — Contributing to peer review and strategic editorial decisions for a high-impact scientific journal.
Academic leadership and research supervision in chemical and pharmaceutical sciences.

🏆 Achievements & Honors

Recognized leader in the chemical and pharmaceutical academic community.
Serving on editorial board for a prestigious journal (Frontiers in Chemistry), indicating expertise and respect in the field.
Head of Department role signifies excellence in academic leadership and scholarship.

🔬 Research & Contributions

Oversees research programs in chemical and pharmaceutical sciences, likely with published works in peer-reviewed journals.
Active in advancing education and research at London Metropolitan University.