Liu Gaofeng | Mathematics | Best Researcher Award | 13449

Dr. Liu Gaofeng | Mathematics | Best Researcher Award 

Dr. Liu Gaofeng, Leshan Normal University, China

Dr. Gaofeng Liu is a Senior Engineer and Associate Professor at the School of Mathematical Sciences, Leshan Normal University, with a concurrent position at Shaoxing Wenli University. He holds a Ph.D. in Information and Communication Engineering and specializes in machine learning applications in complex electromagnetic environments. With extensive experience in both academia and industry, including significant contributions at the 29th Research Institute of CETC, Dr. Liu has led numerous engineering projects and published widely in radar signal processing and PolSAR imaging. His current research focuses on meta-learning, integrated evaluation methods, and mathematical model knowledge bases.

Profile

Scopus

🎓 Early Academic Pursuits

Dr. Gaofeng Liu’s academic journey reflects a deep-rooted passion for mathematics and engineering, beginning in his home province of Sichuan. Born in July 1981 in Qionglai, he demonstrated an early aptitude for analytical thinking and quantitative reasoning. He pursued his undergraduate studies at Southwest Jiaotong University, earning a Bachelor’s degree in Mathematics and Applied Mathematics in 2003. Driven by a strong academic spirit, he continued his education with a Master’s degree in Applied Mathematics in 2006. Eager to explore the interface between theoretical mathematics and practical applications, Dr. Liu earned a Ph.D. in Information and Communication Engineering from the prestigious Xidian University in 2014. His doctoral studies laid a solid foundation in signal processing and machine learning, with particular emphasis on applications in complex electromagnetic environments.

🏢 Professional Endeavors

Dr. Liu began his professional career in 2006 at Neijiang Normal University, where he served as the Director of the Mathematics Laboratory. During this time, he not only contributed to academic instruction but also fostered innovation in mathematical modeling and laboratory development. From 2014 to 2022, he made a significant career transition to the 29th Research Institute of China Electronics Technology Group Corporation (CETC). In this role, he worked on advanced engineering projects, primarily focusing on signal processing, radar data analysis, and complex electromagnetic scenarios. His engineering experience honed his ability to transform real-world problems into robust mathematical frameworks, bridging the gap between theory and practice. Currently, Dr. Liu serves as Senior Engineer and Associate Professor at the School of Mathematical Sciences, Leshan Normal University, and holds a concurrent position at Shaoxing Wenli University. He also leads the Mathematics and Applied Mathematics Program and acts as the academic competition coordinator, playing a crucial role in curriculum design and talent development.

đź§  Contributions and Research Focus

Dr. Liu’s research focuses on machine learning and its application in complex electromagnetic environments, particularly in PolSAR (Polarimetric Synthetic Aperture Radar) imaging, signal decomposition, and radar signal processing. His work often involves developing efficient algorithms for data analysis and creating mathematical models for interpreting high-dimensional radar data.

He has published several influential papers in high-impact journals and conferences, such as:

  • Fast and Valid H/α Decomposition (ICARCV, 2022)

  • Nonnegative Eigenvalue Decomposition for PolSAR (Electronics Letters, 2013)

  • Yamaguchi Decomposition with Hierarchical Constraints (Journal of Electronics & Information Technology, 2013)

In addition, he holds two patents related to radar signal parameter analysis and pulse loss compensation, showcasing his ability to create practical solutions to technical challenges.

🏆 Accolades and Recognition

Though not explicitly listed, Dr. Liu’s consistent involvement in prestigious institutions and research centers reflects high professional recognition. His leadership roles—both in academia and industry—are a testament to his reliability, competence, and visionary approach. His ability to guide academic programs and research initiatives, while also serving as a bridge to engineering applications, distinguishes him as a respected figure in his field.

🌍 Impact and Influence

Dr. Liu’s work has far-reaching implications in areas such as remote sensing, national defense, and signal intelligence, where accurate radar signal interpretation is crucial. His innovations in decomposition techniques and despeckling algorithms have helped enhance the clarity and interpretability of PolSAR images, thereby advancing the capabilities of modern radar systems. As a mentor and academic leader, he plays a vital role in cultivating young minds at Leshan Normal University. His position as the academic competition coordinator underscores his dedication to nurturing innovation, critical thinking, and competitiveness among students.

đź”® Legacy and Future Contributions

Looking forward, Dr. Liu is engaged in several impactful research projects, including:

  • Meta-Learning Principles and Applications (2022–2027) – exploring AI systems that learn to learn.

  • Integrated Evaluation Methods – aimed at improving decision-making frameworks in engineering.

  • Mathematical Model Knowledge Base – building a comprehensive, reusable base of models for industrial and academic use.

These projects not only reflect emerging trends in AI and data science but also position Dr. Liu at the forefront of multidisciplinary innovation. His work is expected to contribute significantly to both academic theory and industrial practice in the years to come.

đź§­ Conclusion

Dr. Gaofeng Liu embodies the rare fusion of academic excellence, engineering precision, and visionary research. From his early academic achievements in mathematics to his current work in machine learning and electromagnetic data analysis, he continues to make valuable contributions across multiple domains. His dedication to knowledge, innovation, and student mentorship ensures that his impact will resonate far beyond the confines of his institutions, shaping the next generation of scientific and engineering breakthroughs.

Farhad Samimi Namin | Mathematics | Best Researcher Award

Assoc Prof Dr. Farhad Samimi Namin | Mathematics |Best Researcher Award

Academic member at University of Zanjan, Iran.

Farhad Samimi Namin is an Assistant Professor at Zanjan University, specializing in mining engineering with a focus on decision theory models for underground mining method selection. He obtained his Ph.D. from Amirkabir University of Technology, Tehran, and has since developed expertise in mine planning, equipment selection, multicriteria decision making, fuzzy logic, and environmental impact assessment. Farhad has authored numerous papers published in prestigious journals and presented at international conferences, showcasing his contributions to advancing mining practices. His teaching portfolio includes courses on underground mining methods and mine design principles, where he emphasizes both theoretical concepts and practical applications. With a commitment to interdisciplinary research and professional development, Farhad continues to play a pivotal role in shaping the future of mining engineering through innovative research and academic leadership.

Professional Profiles:

Education

Farhad Samimi Namin pursued his academic journey in mining engineering, starting with a B.Sc. degree from the International University of Imam Khomeini in Qazvin, Iran. He continued his studies with an M.Sc. in Mining Engineering at Sahid Bahonar University in Kerman, Iran, achieving high academic honors with a GPA of 17.98 out of 20. His educational pursuit culminated in a Ph.D. from Amirkabir University of Technology (Tehran Polytechnic University), Tehran, Iran, where his doctoral research focused on the development of a decision theory-based model for underground mining method selection. His academic achievements reflect a strong foundation in theoretical and applied aspects of mining engineering, preparing him for his subsequent career as an Assistant Professor at the University of Zanjan, Iran.

Professional Experience

Farhad Samimi Namin has garnered extensive professional experience, notably serving as an Assistant Professor in the Mining Engineering Department at Zanjan University, Iran, for over seven years. His academic role includes teaching courses such as Underground Mining Methods, Advanced Underground Excavation Methods, Mine Design Principles, Mine Surveying, Tunneling, Shaft Sinking, Mine Management, Mine Ventilation, and Mine Services. His tenure at Zanjan University has been marked by contributions to both academic instruction and research in the field of mining engineering, particularly focusing on mine planning and the application of Multi-Criteria Decision Making (MADM) techniques in mining contexts.

Research Interest

Farhad Samimi Namin’s research interests primarily revolve around mine planning and design, with a specific focus on mining methods and equipment selection. He specializes in applying Multi-Criteria Decision Making (MADM), fuzzy logic, and environmental impact assessment techniques in the mining industry. His research aims to optimize decision-making processes related to underground mining method selection and to address environmental concerns associated with mining operations. Additionally, he explores practical applications of decision-making techniques in the mining sector, aiming to enhance operational efficiency and sustainability in mineral resource management.

Research Skills

Farhad Samimi Namin is an esteemed figure in mining engineering, currently serving as an Assistant Professor at Zanjan University. He earned his Ph.D. from Amirkabir University of Technology, Tehran, specializing in decision theory models for underground mining method selection. His research interests encompass mine planning, mining equipment selection, multicriteria decision making, fuzzy logic applications, and environmental impact assessment. With a prolific publication record in esteemed journals and presentations at international conferences, Farhad has made significant contributions to advancing mining methodologies. His expertise extends to technical writing, data analysis, and interdisciplinary collaboration, reflecting a comprehensive approach to addressing complex mining challenges. Through his teaching in courses such as underground mining methods and mine design principles, he nurtures the next generation of mining professionals, emphasizing practical applications and theoretical foundations in mining engineering.

Publications

  1. Title: A Review: Applications of Fuzzy Theory in Rock Engineering
    • Authors: Samimi Namin, F.; Rouhani, M.M.
    • Year: 2024
    • Citations: 1
  2. Title: Investigate the potential of using fuzzy similarity in decision making under uncertainty for mining projects
    • Authors: Rouhani, M.M.; Namin, F.S.
    • Year: 2023
    • Citations: 1
  3. Title: Development of a new system for improving blastability by using the Fuzzy Delphi AHP method
    • Authors: Jalali, Z.; Namin, F.S.
    • Year: 2023
    • Citations: 0
  4. Title: Analyzing the effects of natural ventilation caused by excavating the waste pass on the ventilation network of the Anguran mine
    • Authors: Fetri, M.; Shahabi, R.S.; Namin, F.S.; Zeyni, E.E.; Khereshki, M.H.K.
    • Year: 2023
    • Citations: 0
  5. Title: A literature review of Multi Criteria Decision-Making (MCDM) towards mining method selection (MMS)
    • Authors: Namin, F.S.; Ghadi, A.; Saki, F.
    • Year: 2022
    • Citations: 21
  6. Title: 3D computational study of tunnel segment behaviour under loading by TBM thrust jacks
    • Authors: Dastjerdy, B.; Hasanpour, R.; Samimi Namin, F.; Chakeri, H.
    • Year: 2021
    • Citations: 2
  7. Title: Numerical investigation into the effect of stepping on the circumferential joint in the precast tunnel segments under TBM thrust jacks
    • Authors: Karimi, M.; Chakeri, H.; Namin, F.S.; Sharghi, M.; Ă–zçelik, Y.
    • Year: 2020
    • Citations: 6
  8. Title: Uncertainty determination in rock mass classification when using FRMR Software
    • Authors: Namin, F.S.; Rinne, M.; Rafie, M.
    • Year: 2015
    • Citations: 3
  9. Title: Prediction of subsidence risk by FMEA using artificial neural network and fuzzy inference system
    • Authors: Rafie, M.; Samimi Namin, F.
    • Year: 2015
    • Citations: 84
  10. Title: FMMSIC: A hybrid fuzzy based decision support system for MMS (in order to estimate interrelationships between criteria)
    • Authors: Namin, F.S.; Shahriar, K.; Bascetin, A.; Ghodsypour, S.H.
    • Year: 2012
    • Citations: 28