Liangjun Chen | Metallurgical | Best Researcher Award

Published on 10/03/202510/03/2025 by TOT Awards

Dr. Liangjun Chen | Metallurgical | Best Researcher Award

Lecturer at School of Metallurgical Engineering, Anhui University of Technology, China.

Dr. Liangjun Chen is a distinguished researcher and lecturer at the School of Metallurgical Engineering, Anhui University of Technology. With a Ph.D. from the University of Science and Technology Beijing and the University of Toronto, he has dedicated his career to advancing intelligent metallurgical processes. His expertise spans AI-driven process optimization, solid waste utilization, and industrial automation. Over the years, Dr. Chen has made significant contributions to modern metallurgical engineering, publishing more than 23 SCI-indexed papers and securing prestigious research funding, including the National Natural Science Foundation (Youth Program). His research focuses on intelligent process control in steel manufacturing, aiming to enhance efficiency and sustainability. In recognition of his groundbreaking work, he has received multiple accolades, including a Bronze Award in the Anhui Postdoctoral Innovation and Entrepreneurship Competition. Additionally, he holds 12 patents, five of which have been authorized. His collaborations with leading industry players, such as Baosteel and Jiangsu Yonggang, reinforce his role as a pioneer in modern metallurgical engineering, bridging academic research with practical industrial applications.

Professional Profile

Sci Profile

ORCID

Education 🎓

Dr. Liangjun Chen pursued his Ph.D. at the University of Science and Technology Beijing in collaboration with the University of Toronto. His academic journey was marked by intensive research in metallurgical engineering, focusing on optimizing sintering processes, intelligent process control, and sustainable metallurgical practices. Throughout his doctoral studies, he worked on AI-driven industrial process innovations that have since become integral to steel manufacturing. His studies provided him with a strong foundation in metallurgy, computational modeling, and automation, equipping him with the knowledge necessary to solve critical challenges in industrial metallurgy. His interdisciplinary approach allowed him to combine theoretical knowledge with practical applications, making his research highly relevant to both academia and industry. His dedication to metallurgical research has led to significant advancements in process efficiency and waste reduction, reinforcing his reputation as a forward-thinking scientist in the field.

Work Experience 💼

Dr. Chen has accumulated extensive experience in metallurgical engineering through both academic and industry-focused research. Currently, he serves as a lecturer at Anhui University of Technology, where he teaches metallurgical engineering while actively engaging in research projects. Prior to his current role, he completed a postdoctoral fellowship at the same institution, where he played a key role in multiple industry-sponsored research initiatives. His work has led to groundbreaking advancements in sintering efficiency, AI-driven industrial automation, and the comprehensive utilization of metallurgical solid waste. Additionally, Dr. Chen has collaborated with leading steel manufacturers, including Baosteel and Shandong Nuode Energy, applying his research findings to real-world industrial settings. Beyond academia, he has contributed to industrial consulting, providing expertise in optimizing steel manufacturing processes, improving fuel consumption efficiency, and reducing emissions. His work continues to have a profound impact on the field, bridging theoretical research with practical applications in metallurgy.

Research Interests 🔬

Dr. Chen’s research primarily focuses on intelligent and informatized metallurgical processes, leveraging artificial intelligence to optimize steel manufacturing and industrial automation. His work is centered on developing AI-driven process control systems to improve sintering efficiency, reduce energy consumption, and enhance the comprehensive utilization of metallurgical solid waste. By integrating advanced modeling techniques, his research contributes to smart manufacturing, predictive analytics, and real-time process monitoring. His studies in sustainable metallurgy aim to reduce industrial emissions and enhance waste recycling in steel production. A key aspect of his research is the development of intelligent sintering leak detection and steel slag recycling technologies, which significantly improve environmental sustainability and cost-effectiveness in metallurgical processes. His work not only advances theoretical knowledge but also has direct industrial applications, bridging the gap between scientific research and real-world metallurgical innovations.

Awards & Achievements 🏆

Dr. Chen’s innovative contributions to metallurgical engineering have earned him several prestigious awards and honors. He won the Bronze Award in the Anhui Postdoctoral Innovation and Entrepreneurship Competition, highlighting his ability to translate academic research into industrial innovations. His research excellence has been further recognized through a National Natural Science Foundation (Youth Program) Grant, which supports his cutting-edge investigations into intelligent process control and metallurgical waste management. He also received the Silver Prize at the Metallurgical Innovation Forum for his advancements in AI-driven sintering process optimization. As a researcher, Dr. Chen has successfully led eight industry-sponsored projects, securing funding and industry partnerships that have enhanced metallurgical manufacturing efficiency. Additionally, he has been awarded 12 patents, five of which have been officially authorized, further demonstrating his commitment to innovation. His expertise is widely recognized, and he serves as a Youth Editorial Board Member of Sintering and Pelletizing, as well as a reviewer for Ironmaking & Steelmaking and Steel Research International.

Conclusion

Dr. Liangjun Chen is a strong candidate for the Best Researcher Award due to his outstanding contributions to metallurgical engineering, extensive industry collaborations, and innovative research in AI-driven process optimization. While he has already demonstrated excellence in research, further efforts in increasing citations, professional memberships, and international outreach could further strengthen his candidacy. His contributions significantly impact both academia and industry, making him well-suited for this prestigious recognition.

Top Noted Publications 📚

“Research progress on prediction of FeO content in sinter based on intelligent algorithm”

Authors: Xin-Yu Zhang, Da-Lin Xiong, Meng Xie, Liang-Jun Chen, Hong-Ming Long, Alexander McLean

Year: 2025

“Development and application of an intelligent thermal state monitoring system for sintering machine tails based on CNN–LSTM hybrid neural networks”

Authors: Da-Lin Xiong, Xin-Yu Zhang, Zheng-Wei Yu, Xue-Feng Zhang, Hong-Ming Long, Liang-Jun Chen

Year: 2024

“A Predictive Model for Sintering Ignition Temperature Based on a CNN-LSTM Neural Network with an Attention Mechanism”

Authors: Da-Lin Xiong, Hou-Yin Ning, Meng Xie, Liang-Jun Chen, Zheng-Wei Yu, Hong-Ming Long

Year: 2024

“Dephosphorization of Hot Metal Containing High Phosphorus Using F-free CaO–SiO₂–Al₂O₃–Fe₂O₃ Slag”

Authors: Haimeng Xue, Jie Li, Yunjin Xia, Yong Wan, Liangjun Chen, Changji Lv

Year: 2021

“Mechanism of Phosphorus Enrichment in Dephosphorization Slag Produced Using the Technology of Integrating Dephosphorization and Decarburization”

Authors: Haimeng Xue, Jie Li, Yunjin Xia, Yong Wan, Liangjun Chen, Changji Lv

Year: 2021

“A New Method for Plasticization of Inclusions in Saw-Wire Steel by NaF Addition”

Authors: Liangjun Chen, Yong Wan, Jie Li, Weiqing Chen, Yindong Yang, Alexander McLean

Year: 2020

“Effect of Final Electromagnetic Stirring Parameters on Central Cross-Sectional Carbon Concentration Distribution of High-Carbon Square Billet”

Authors: Yong Wan, Menghua Li, Liangjun Chen, Jie Li, Hongbo Pan, Wei Zhong

Year: 2019

“Refractory/steel/inclusion interactions in Al-deoxidised valve spring steel treated with Na₂CO₃”

Authors: Liangjun Chen, Weiqing Chen, Wei Yan, Yindong Yang, Alexander McLean

Year: 2019

“Effects of K₂CO₃ Addition on Inclusions in High-Carbon Steel for Saw Wire”

Authors: Liangjun Chen, Weiqing Chen, Yang Hu, Zhaoping Chen, Yingtie Xu, Wei Yan

Year: 2018

Qing Liu | Metallurgy | Best Researcher Award

Published on 17/01/202517/01/2025 by TOT Awards

Prof. Dr. Qing Liu | Metallurgy | Best Researcher Award

Former Deputy Director at University of Science and Technology Beijing, China

Prof. Dr. Qing Liu is a renowned metallurgical engineer and professor at the University of Science and Technology Beijing (USTB), where he also serves as the Deputy Director of the State Key Laboratory of Advanced Metallurgy. A leader in the field of steelmaking and metallurgical engineering, he has made significant contributions to process optimization, quality control, and intelligent manufacturing in steel production. Dr. Liu has earned multiple prestigious awards, including the National Business Science and Technology Progress Award and the World Scientist Grand Award. His extensive academic and research career, paired with numerous leadership roles, solidifies his status as an influential figure in the global metallurgy community. As a visiting professor and member of several international associations, his work bridges global collaborations with advanced metallurgical practices. 🌍🏅

professional profiles

Scopus Profile

Education

Prof. Dr. Qing Liu completed his Bachelor’s degree in Metallurgical Engineering at USTB in 1989. He continued his academic journey with a Master’s degree in Metallurgical Engineering from USTB (1995) and later earned a Ph.D. in Metallurgical Engineering from the same university in 2002. He expanded his global academic exposure as a visiting scholar at Latrobe University in Australia in 2005. His education laid the foundation for his successful career in metallurgical research and engineering. Liu’s expertise spans across steelmaking, continuous casting processes, and metallurgical process optimization, contributing significantly to the advancements in the industry. 📚

work Experience

Prof. Dr. Qing Liu has held several prestigious positions at USTB. Since 2007, he has been a professor, and from 2013 to 2019, he served as the Deputy Director of the State Key Laboratory of Advanced Metallurgy. His administrative experience includes roles such as Deputy Director of the Office of Scientific Research and Development at USTB and Vice Dean of the School of Metallurgical Engineering. Additionally, he has served as a lecturer and teaching assistant during the earlier years of his career. Liu’s leadership extends to numerous influential committees in metallurgical technology, such as the Continuous Casting Committee of the Chinese Society for Metals, highlighting his wide-reaching impact on the field. 👨‍🏫

Awards and Honors

Prof. Dr. Qing Liu has received numerous accolades for his groundbreaking work in the field of metallurgy. In 2024, he was awarded the National Business Science and Technology Progress Award (First Place) for the development and application of intelligent smelting technology. He also received the National Metallurgical Science and Technology Award (First Place, Second Class) for advancements in solidification cooling processes in continuous casting. Liu’s expertise has earned him the 60th Advanced Materials Congress Scientist Medal Award and the World Scientist Grand Award (Golden Scientist Grand Award), both of which recognize his contributions to the optimization of steelmaking technologies. These honors reflect his leadership and innovation in metallurgical research. 🏅

Research Focus

Prof. Dr. Qing Liu’s research interests primarily revolve around the optimization of metallurgical processes, focusing on steelmaking and continuous casting technologies. He is particularly passionate about enhancing quality control and efficiency in steel production through intelligent manufacturing systems. His work in multiscale modeling and simulation aims to improve the sustainability and high-efficiency utilization of metallic resources. Liu also explores collaborative manufacturing strategies that integrate advanced technologies for quality steel production, paving the way for smarter, more resource-efficient metallurgical processes. His research continues to shape the future of metallurgical engineering. 🔧

Skills

Prof. Dr. Qing Liu possesses a diverse skill set in metallurgy, process optimization, and industrial engineering. His expertise includes advanced simulation and modeling techniques, intelligent manufacturing systems, and the optimization of continuous casting processes. Additionally, he has extensive leadership and project management skills, honed through years of administrative roles and research direction. Liu is also proficient in fostering international collaborations and mentoring the next generation of metallurgists. His broad technical skills and academic leadership make him a prominent figure in the field of metallurgical engineering. 🛠️

Conclusion

Prof. Dr. Qing Liu is a highly accomplished researcher and a deserving candidate for the Best Researcher Award. His pioneering contributions to metallurgical engineering, particularly in steelmaking intelligence and process optimization, demonstrate an exceptional commitment to advancing science and technology. Recognized globally for his expertise and leadership, Prof. Liu’s work has a lasting impact on both academia and industry. Addressing the areas for improvement—such as enhancing public outreach and diversifying research applications—could further solidify his position as a leading figure in his field.

Publications to Noted

Large eddy simulation of novel EMBr effect on flow pattern in thin slab casting mold with multi-port SEN and ultra-high casting speed

Authors: Cui, H., Sun, J., Zhang, J., Wang, G., Liu, Q.

Citations: 0

Year: 2025

Journal: Journal of Manufacturing Processes

Study on Influencing Factors and Their Combined Effects on Multiphase Behavior in Tundish Pouring Zone

Authors: Qin, B., Zhang, J., Yang, C., Yang, S., Liu, Q.

Citations: 0

Year: 2025

Journal: Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science

Prediction of Ladle Furnace Refining Endpoint Temperature Based on Particle Swarm Optimization Algorithm and Long Short-Term Memory Neural Network

Authors: Wang, H., Wang, M., Liu, Q., Yang, Z., Xing, L.

Citations: 0

Year: 2025

Journal: JOM

Explainable machine learning model for predicting molten steel temperature in the LF refining process

Authors: Xin, Z., Zhang, J., Peng, K., Zhang, B., Liu, Q.

Citations: 0

Year: 2024

Journal: International Journal of Minerals, Metallurgy and Materials

Effect of Deoxidation Sequence on Inclusions in Oriented Silicon Steel

Authors: Liu, Q., Wang, M., Pang, W., Xing, L., Bao, Y.

Citations: 0

Year: 2024

Journal: JOM

Numerical Modeling and Plant Trial on the Optimization of SEN Designs in a Large Round Billet Mold

Authors: Qin, B., Zhang, J., Yang, S., Zuo, X., Liu, Q.

Citations: 0

Year: 2024

Journal: Metallurgical and Materials Transactions B: Process Metallurgy and Materials Processing Science

Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost

Authors: Xu, J., Xin, Z., Lan, M., Zhang, B., Liu, Q.

Citations: 0

Year: 2024

Journal: Gongcheng Kexue Yu Jishu/Advanced Engineering Sciences

Steelmaking–Continuous Casting Scheduling Model Based on Grey Wolf Algorithm with “Furnace–Caster Matching” Mode

Authors: Chen, B., Shao, X., Zhang, J., Li, H., Liu, Q.

Citations: 0

Year: 2024

Journal: Gongcheng Kexue Yu Jishu/Advanced Engineering Sciences

Preparation and Properties of Thick Tungsten Coating Electrodeposited from Na2WO4-WO3-KCl-NaF Molten Salt System

Authors: Li, Y., Dong, X., Liu, Q., Gao, Z., Zhang, Y.

Citations: 0

Year: 2024

Journal: Coatings

Microstructure and high temperature tribological behavior of nickel-based superalloy with addition of revert

Authors: Zhang, K., Zhang, J., Zhao, P., Liu, Q., Yang, S.

Citations: 2

Year: 2024

Journal: Journal of Materials Research and Technology

Jue Tang | Metallurgical Engineering | Best Faculty Award

Published on 17/12/202417/12/2024 by TOT Awards

Dr. Jue Tang | Metallurgical Engineering | Best Faculty Award

Associate professor at Northeastern University, China

Dr. Jue Tang, an Associate Professor at Northeastern University in the School of Metallurgy, exemplifies excellence in teaching, research, and innovation. With a Doctorate in Ferrous Metallurgy and over seven years of academic experience, Dr. Tang has contributed significantly to low-carbon ironmaking and metallurgical innovations. Her accomplishments include supervising research projects, publishing over 50 high-impact papers, authoring books, and obtaining 20 patents. Additionally, she has played a pivotal role in projects focusing on hydrogen-based metallurgy and digital twin systems for blast furnaces. Dr. Tang’s exceptional track record and leadership in academia make her a standout candidate for the Best Faculty Award.

professional profiles

Scopus Profile

Education

Dr. Tang’s academic journey began at Northeastern University, where she earned a Bachelor’s degree in Metallurgical Engineering in 2010. She continued her studies at the same institution, obtaining a Master’s degree in 2012. Pursuing her passion for ferrous metallurgy, she completed her Doctorate in 2017. Her education has been the cornerstone of her expertise, emphasizing advanced methodologies in low-carbon and intelligent ironmaking. This solid academic foundation has positioned her as a leading researcher in metallurgical innovations, blending theoretical knowledge with practical applications to redefine the field.

work Experience

Dr. Tang joined the School of Metallurgy at Northeastern University as a Lecturer in 2017, progressing to Associate Professor in 2022. She has been supervising Master’s students since 2021 and has played a key role in groundbreaking projects like the pilot production of low-carbon blast furnaces. As a reviewer for renowned journals such as MMTB and JCLP, she contributes to the global academic community. Her expertise extends to managing national and enterprise-funded projects, fostering innovation through collaborative research. Dr. Tang’s professional journey exemplifies dedication to advancing metallurgy through teaching, research, and industry partnerships.

Awards and Honors 🏆

Dr. Tang’s contributions have been widely recognized with multiple accolades, including the prestigious first prize for scientific and technological transformation in Liaoning Province and the Jianlong Group’s contribution prize for scientific cooperation. She has also received the Rongcheng Xiangqing Scientific Research Innovation Award and the Fushun New Iron and Steel Technological Innovation Pacesetter Award. These honors underscore her impact on both academic and industrial fronts, reflecting her commitment to sustainability and innovation in metallurgy.

Research Focus

Dr. Tang’s research emphasizes sustainable metallurgical processes, particularly low-carbon blast furnace development, hydrogen-based shaft furnaces, and intelligent ironmaking. Her projects aim to integrate digital twin systems into blast furnace operations, combining data analytics with advanced metallurgical techniques. Additionally, she explores the comprehensive utilization of vanadium-titanium magnetite, aligning her work with global efforts to enhance resource efficiency. Dr. Tang’s research embodies a vision for a greener, smarter metallurgical industry.

Skills

Dr. Tang’s skill set includes expertise in low-carbon metallurgy, project management, and advanced research methodologies. Her technical prowess spans hydrometallurgy, digital twin technology, and the utilization of vanadium-titanium resources. Proficient in academic publishing, she is a seasoned reviewer and collaborator in international research networks. Her leadership and problem-solving abilities have been instrumental in driving innovation in metallurgy, fostering sustainable practices, and mentoring the next generation of engineers.

Conclusion

Dr. Jue Tang’s remarkable contributions to research and innovation in ferrous metallurgy position her as an outstanding candidate for the Best Faculty Award. Her pioneering work in low-carbon and hydrogen-based processes, combined with her academic accomplishments and leadership roles, highlights her as a leader in sustainable metallurgy. While enhancing community engagement and teaching outreach could further strengthen her impact, Dr. Tang’s achievements already make her a beacon of academic excellence and innovation.

Publications to Noted

Reduction Behavior of Lump Ore and Its Applicability During Hydrogen-Based Shaft Furnace Process

Authors: Zhao, Z., Tang, J., Chu, M., Li, F., Yuan, L.

Year: 2024

Citations: 0

Density Functional Theory Study on the Interaction of H₂ and CO with Fe₂O₃ Based on Hydrogen-Based Shaft Furnace Process

Authors: Liu, X., Tang, J., Chu, M., Liu, J., Tang, Z.

Year: 2024

Citations: 2

Process Metallurgy and Data-Driven Prediction and Feedback of Blast Furnace Heat Indicators

Authors: Shi, Q., Tang, J., Chu, M.

Year: 2024

Citations: 1

Slag-Hanging Capacity of Numerical Simulation and Analysis of Blast Furnace Copper Cooling Plate Based on ANSYS ‘Birth–Death Element’

Authors: Zhang, Z., Tang, J., Chu, M., Shi, Q., Wang, C.

Year: 2024

Citations: 1

Smelting Characteristics of Nickel‑Chromium‑Manganese Bearing Prereduced Pellets for the Preparation of Nickel Saving Austenite Stainless Steel Master Alloys

Authors: Tian, H., Chu, M., Pan, J., Yang, C., Tang, J.

Year: 2024

Citations: 1

Effect of Manganese Ore and Basicity on the Enhanced Reduction and Consolidation Characteristics of Nickel–Chromium Bearing Reduced Pellets

Authors: Tian, H., Chu, M., Pan, J., Zhu, D., Tang, J.

Year: 2024

Citations: 0

Effect of V₂O₅ During Oxidation Roasting of Pellet: Non-Isothermal Kinetic Analysis and Microstructure Evolution

Authors: Feng, J., Tang, J., Wang, X., Zhao, Z., Chu, M.

Year: 2024

Citations: 0

Sticking Behavior of Burdens During Reduction Process in Gas-Based Shaft Furnaces

Authors: Zhao, Z., Tang, J., Wang, X., Liu, Z., Li, L.

Year: 2024

Citations: 3

Effect of TiO₂ During Oxidation Roasting Process of Pellet: Kinetic Mechanism and Microstructure

Authors: Feng, J., Tang, J., Wang, X., Liu, Z., Li, L.

Year: 2024

Citations: 1

Effect of Manganese Ore and Basicity on the Consolidation Characteristic of Nickel‑Chromium Iron Ore Pellets

Authors: Tian, H., Chu, M., Pan, J., Tang, J., Li, F.

Year: 2024

Citations: 3

Liangjun Chen | Metallurgical | Best Researcher Award

Dr. Liangjun Chen | Metallurgical | Best Researcher Award

Professional Profile

Education 🎓

Work Experience 💼

Research Interests 🔬

Awards & Achievements 🏆

Conclusion

Top Noted Publications 📚

Qing Liu | Metallurgy | Best Researcher Award

Prof. Dr. Qing Liu | Metallurgy | Best Researcher Award

professional profiles

Education

work Experience

Awards and Honors

Skills

Jue Tang | Metallurgical Engineering | Best Faculty Award

Dr. Jue Tang | Metallurgical Engineering | Best Faculty Award

professional profiles

Education

work Experience

Awards and Honors 🏆

Research Focus

Skills

Conclusion

Publications to Noted

RECOMMENDED

Mail us