Jianbin Chen | Engineering | Best Researcher Award

Mr. Jianbin Chen | Engineering | Best Researcher Award

Chief Technology Officer | Guangdong Titans Intelligent Power Company Ltd | China

Mr. Jianbin Chen is a distinguished engineering professional with more than 11 years of expertise in digital signal design, iterative coding, data storage and communication systems, and the integration of power and wireless communication technologies in the Internet of Things (IoT). He currently serves as the Executive Vice President and R&D Director at Guangdong Titan Intelligent Power Co., Ltd., in addition to holding roles as a Senior Engineer, IEEE member, off-campus master’s mentor at Nanchang Institute of Technology, and Visiting Associate Professor at Guangdong Polytechnic of Science and Technology. Mr. Chen earned his bachelor’s degree from North Central University in 2011 and completed his Ph.D. at the University of Macau in 2021. Throughout his career, he has led and executed numerous high-impact projects, including intelligent air conditioning energy control systems, IoT-based smart street lighting systems, and advanced energy consumption control platforms for major infrastructure. He has overseen several provincial and municipal innovation programs, demonstrating strong leadership in research and technology development. Mr. Chen has secured 30 patents and 28 software copyrights, with many of his innovations being successfully commercialized and widely recognized. His outstanding contributions have earned him multiple prestigious honors such as the Zhuhai Talent Program, the Best Software Technology Innovation Product Awards, and national innovation competition prizes. Academically, he has published influential research papers and a book, with his work featured in SCI-indexed journals, covering topics like power electronics, intelligent control systems, and smart cities. His ability to combine advanced research with industrial applications has significantly contributed to the development of smart energy and IoT technologies in China. Mr. Chen’s visionary leadership, technical excellence, and dedication to innovation position him as a key figure in advancing intelligent infrastructure and sustainable technology solutions for the future.

Profile: ORCID
Featured Publications
  1. Chen, J., Yang, C., Zou, J., & Chen, K. (2025). Multiplier operated controller for CCM boost PFC converter with regulated input impedance and improved power factor. IEEE Access. DOI: 10.1109/ACCESS.2025.3548096

  2. Chen, J., Yang, C., & Zou, J. (2025). Optimization control strategy of wide ZVS range and automatic Euler angle for bi-directional wireless power transfer system by TPS. International Journal of Electrical Power & Energy Systems. DOI: 10.1016/j.ijepes.2025.111133

  3. Chen, J., Yang, C., & Zou, J. (2022). Robust enhanced voltage range control for industrial robot chargers. IEEE Access. DOI: 10.1109/ACCESS.2022.3229688

  4. Chen, J., Yang, C., Tang, S., & Zou, J. (2021). A high power interleaved parallel topology full-bridge LLC converter for off-board charger. IEEE Access. DOI: 10.1109/ACCESS.2021.3130051

  5. Chen, J. (2017). SMT物料种类与标准. 电子工业出版社. ISBN: 978-7-121-31740-8

João Felipe C L Costa | Engineering | Best Research Article Award

Prof. João Felipe C L Costa | Engineering | Best Research Article Award

Professor at Federal University of Rio Grande do Sul, Brazil

Dr. João Felipe Costa 🎓 is a distinguished Professor of Mining Engineering at the Federal University of Rio Grande do Sul, Brazil, with over four decades of expertise in geostatistics, mineral exploration, and mine planning ⛏️. He holds a PhD in Geostatistics from the University of Queensland and has published 300+ peer-reviewed papers 📚. A respected mentor, he has guided over 110 theses and dissertations and received multiple teaching accolades, including the prestigious John Cedric Griffiths Teaching Award 🏅. As head of the mineral exploration lab for 30+ years and an active member of leading international mining societies 🌍, Dr. Costa has led significant resource estimation projects globally, especially in phosphate deposit modeling. His career exemplifies academic excellence, innovation, and impactful contributions to mining sciences and education 🔍.

Professional Profile

🎓 Education

Dr. João Felipe Costa earned his BSc (1983) and MSc (1992) in Mining Engineering from the Federal University of Rio Grande do Sul 🇧🇷, where he currently serves as Professor. He advanced his academic journey by earning a PhD in Geostatistics from the University of Queensland, Australia 🇦🇺 in 1997. His education bridges deep technical knowledge with applied innovation, particularly in geological modeling and statistical data analysis 📊. His foundation in mining engineering and specialization in geostatistics has positioned him as an expert in both practical and academic settings. Dr. Costa’s education reflects a strong commitment to continuous learning and excellence in the evolving field of mineral resources and spatial data science 🧠.

💼 Professional Experience

Dr. Costa began his career as a mining engineer at a major coal operation in southern Brazil, where he optimized unit operations using early computer applications in the 1980s 🖥️⛏️. He joined the Federal University of Rio Grande do Sul in 1986 and has served as a Professor in the Mining Engineering Department ever since. His professional journey includes roles as Department Head, research lab coordinator, and consultant on numerous mineral resource evaluation projects 🌐. With over 30 years of teaching and field experience, he has balanced academic leadership with applied industrial insight, making significant contributions to both sectors. His dedication to education, project execution, and resource modeling showcases his deep engagement with both theory and practice ⚙️📘.

🔬 Research Interest

Dr. João Felipe Costa’s core research interests lie in geostatistics, mineral resource estimation, mine planning, and phosphate deposit modeling 📈. He is especially known for developing robust techniques for spatial data analysis, resource classification, and geological uncertainty evaluation. His work extends to a variety of geological settings, including sedimentary and carbonatite phosphate formations in Brazil and Peru 🌍. Passionate about data-driven solutions, his research integrates statistical modeling with software tools to improve decision-making in exploration and mining processes 💡. As a leading voice in mathematical geosciences, Dr. Costa’s interdisciplinary research not only enhances mining efficiency but also supports sustainable resource management 🔎🧭.

🏅 Awards and Honors

Dr. Costa has been honored multiple times throughout his career. Most notably, he received the John Cedric Griffiths Teaching Award in 2014 from the International Association for Mathematical Geosciences, recognizing his excellence in geoscience education 🎖️. He has also been named Distinguished Professor by graduating classes over the past 20 years, reflecting his lasting impact on student learning 👨‍🏫. As an esteemed member of professional societies like AusIMM, IAMG, SME (USA), and SAIMM (South Africa), his global contributions have earned widespread recognition 🌐. His leadership in Brazil’s mineral resources committee further reinforces his influence in shaping mining policy and academic standards 🏆.

🛠️ Research Skills

Dr. Costa possesses advanced research skills in geostatistical modeling, orebody evaluation, spatial data interpretation, and mineral resource classification 🔍. He is proficient in using industry-relevant software for data simulation, variography, and risk assessment 🖥️📊. His methodological rigor is evident in over 300 peer-reviewed publications and advisory roles in complex exploration projects worldwide 🌎. As the head of a leading mine planning lab for three decades, he has cultivated a dynamic research environment integrating computational tools with field data. His skills also include thesis supervision, technical writing, and collaborative research management, making him a versatile and highly capable scientific contributor 🔧📘.

Publications Top Note 📝

Title: Localized conditional simulation to integrate production data in grade control models
Authors: R. L. Silva, J. F. C. L. Costa, D. M. Marques
Year: 2021
Source: Computers & Geosciences
Citation: Computers & Geosciences, Vol. 150, 104722

Title: Uncertainty in the modeling of lateritic nickel ores by multiple indicator kriging
Authors: A. L. F. Duarte, J. F. C. L. Costa
Year: 2016
Source: Ore Geology Reviews
Citation: Ore Geology Reviews 73, 223–233

Title: Conditional simulation of iron ore deposit grades using co-simulation with proportional correction
Authors: J. F. C. L. Costa, R. H. Rubio, D. M. Marques
Year: 2018
Source: Revista Escola de Minas
Citation: Rev. Esc. Minas 71(4), 531–538

Title: Application of indicator kriging to define cutoff grades for iron ore
Authors: J. F. C. L. Costa, D. M. Marques
Year: 2013
Source: Revista Escola de Minas
Citation: Rev. Esc. Minas 66(1), 37–43

Title: Geostatistical conditional simulation to define grade control strategy for a bauxite mine
Authors: D. M. Marques, J. F. C. L. Costa
Year: 2015
Source: J. South African Institute of Mining and Metallurgy
Citation: J. SAIMM 115(6), 533–540

Title: Geostatistical simulation of mineral grades using multiple-point statistics
Authors: F. G. da Silva, J. F. C. L. Costa
Year: 2016
Source: Computers & Geosciences
Citation: Computers & Geosciences 94, 1–12

Title: Simulation of grade control based on inverse distance weighting
Authors: D. M. Marques, J. F. C. L. Costa
Year: 2018
Source: Revista Escola de Minas
Citation: Rev. Esc. Minas 71(1), 123–129

Title: Geostatistical modeling in lateritic nickel ore: A comparative study between ordinary kriging and indicator kriging
Authors: A. L. F. Duarte, J. F. C. L. Costa
Year: 2015
Source: Natural Resources Research
Citation: Nat. Resour. Res. 24(2), 213–225

Title: Use of stochastic simulation to support mining strategy selection
Authors: D. M. Marques, J. F. C. L. Costa
Year: 2016
Source: Journal of the Southern African Institute of Mining and Metallurgy
Citation: J. SAIMM 116(7), 669–676

Title: Comparison of multivariate conditional simulation techniques for iron ore grade modeling
Authors: R. H. Rubio, J. F. C. L. Costa
Year: 2017
Source: Computers & Geosciences
Citation: Computers & Geosciences 101, 1–12

Conclusion

Dr. João Felipe Costa is a world-class academic and professional in mining engineering and geostatistics, blending education, research, and leadership with remarkable consistency 🌟. His impact spans over 40 years of scholarly excellence, with hundreds of publications, international collaborations, and influential teaching. A mentor, innovator, and geoscience leader, he continues to shape the future of mineral exploration and resource evaluation 🔬🧭. With his global recognition, research depth, and technical command, Dr. Costa stands as a compelling candidate for top honors in scientific research and academic excellence 🎓🏅.