Zicheng Xin | intelligentialization | Best Researcher Award

Dr. Zicheng Xin | intelligentialization | Best Researcher Award

postdoctor, University of Science and Technology Beijing, China

Zicheng Xin is a renowned researcher and visiting professor at the Korea Invention Academy. He is affiliated with the University of Science and Technology Beijing (USTB) and has made significant contributions to the field of metallurgical engineering. His research focuses on metallurgical process engineering, intelligence, and simulation.

Profile

scopus

Education šŸŽ“

Ph.D. in Metallurgical Engineering, State Key Laboratory of Advanced Metallurgy, University of Science and Technology Beijing (USTB) (2018-2022)

Experience šŸ§Ŗ

Visiting Professor, Korea Invention Academy (current) Ā Researcher, State Key Laboratory of Advanced Metallurgy, USTB (current)

Awards & HonorsšŸ†

ā€œMultiscale modeling and collaborative manufacturing for steelmaking plantsā€, the 10th World Scientist Grand Award ā€” Golden Scientist Grand Award (Second Place, International Federation of Inventors’ Associations, 2023) ā€œMultiscale modeling and collaborative manufacturing for steelmaking plantsā€, the 10th World Scientist Grand Awardā€” Science & Technology Grand

Research Focus šŸ”

Metallurgical process engineering and intelligence Ā Simulation and optimization of metallurgical process

PublicationsšŸ“š

1. Analysis of multi-zone reaction mechanisms in BOF steelmaking and comprehensive simulation [J]. Materials, 2025, 18(5): 1038. – Zicheng Xin, Qing Liu, Jiangshan Zhang, et al.
2. Modeling of LF refining process: a review [J]. Journal of Iron and Steel Research International, 2024, 31(2): 289-317. – Zicheng Xin, Jiangshan Zhang, Kaixiang Peng, et al.
3. Explainable machine learning model for predicting molten steel temperature in LF refining process [J]. International Journal of Minerals, Metallurgy and Materials, 2024, 31(12): 2657-2669. – Zicheng Xin, Jiangshan Zhang, Kaixiang Peng, et al.
4. Predicting temperature of molten steel in LF refining process using IF-ZCA-DNN model [J]. Metallurgical and Materials Transactions B, 2023, 54(3): 1181-1194. – Zicheng Xin, Jiangshan Zhang, Junguo Zhang, et al.
5. Predicting the alloying element yield in a ladle furnace using principal component analysis [J]. … – Zicheng Xin, Jiangshan Zhang, Yu Jin, et al.

Conclusion

Zicheng Xin’s academic excellence, research focus, and international recognition make him a strong candidate for the Best Researcher Award. While there are areas for improvement, his strengths and achievements demonstrate his potential to make significant contributions to the field of metallurgy.

Sabum Jung | Smart factory | Best Researcher Award

Mr. Sabum Jung | Smart factory | Best Researcher Award

Research engineer, Lg energy solution,South Korea

Sabum Jung is a seasoned Data Scientist and Machine Learning Engineer with over 23 years of expertise in predictive modeling, deep learning, and AI-driven optimization. His career spans LG Energy Solution, SK Holdings, and LG Production Engineering Research Institute, where he pioneered AI applications in high-tech manufacturing, including semiconductor, battery, and display industries. A former Military Intelligence Analyst for the U.S. Army, he has authored research papers and books on AI, machine learning, and Industry 4.0. Fluent in English, Korean, and Japanese, he continues to drive AI innovations in industrial applications.

Profile

šŸŽ“ Education

Sabum Jung holds a B.A. (3.9/4.5) and an M.S. (4.2/4.5) in Industrial Engineering from Sung Kyun Kwan University, South Korea. His academic journey focused on advanced analytics, AI-driven optimization, and industrial process improvements. His research contributions in artificial intelligence, reliability engineering, and digital transformation have shaped his expertise in machine learning, deep learning, and predictive modeling, positioning him as a leader in AI applications for manufacturing and industrial systems.

šŸ’¼ Experience

Currently a Data Scientist at LG Energy Solution, Sabum Jung leads AI-driven innovations in virtual metrology, predictive maintenance, and defect analysis. Previously at SK Holdings, he optimized renewable energy predictions, semiconductor material discovery, and AI-powered industrial operations. His 20-year tenure at LG Production Engineering Research Institute saw groundbreaking work in machine learning for smart appliances, battery systems, and industrial automation. His early career as a Military Intelligence Analyst in the U.S. Army honed his analytical prowess, setting the foundation for his AI-driven problem-solving approach.

šŸ† Awards & Honors

Sabum Jung has been recognized for his contributions to AI, machine learning, and industrial automation. His accolades include leadership in AI-driven manufacturing optimization, predictive maintenance, and reinforcement learning applications. He has received industry recognition for his research and innovation in deep learning, active learning, and process optimization in high-tech sectors, further cementing his influence in AI-driven industrial advancements.

šŸ”¬ Research Focus:

Sabum Jung specializes in AI applications for high-tech manufacturing, focusing on predictive maintenance, virtual metrology, and defect detection. His research spans deep learning, reinforcement learning, and AI-driven industrial process optimization. Notable contributions include renewable energy prediction, semiconductor material discovery, and advanced statistical modeling. His expertise in machine learning has been instrumental in developing AI solutions for smart manufacturing, Industry 4.0, and digital transformation.

Publications

Recent progress of LG PDP: High efficiency & productivity technologies Citations1

Conclusion

Sabum Jung is a strong candidate for the Best Researcher Award, given his vast industry experience, research excellence, and technological contributions to AI and machine learning in manufacturing. Enhancing academic collaborations and increasing research dissemination could further elevate his impact and recognition.

Manar Hamza | Computer Science Data mining | Best Researcher Award

Dr. Manar Hamza | Computer Science Data mining | Best Researcher Award

professor atĀ  Prince Sattam bin Abd El Aziz University, China

šŸ‘©ā€šŸ« Experienced Computer Science Lecturer since 2005 with expertise in data mining, text mining, and information security. šŸ’» Holds a strong track record in research and academia, leveraging innovation and teamwork. Aims to thrive in challenging, dynamic, and team-oriented environments that foster growth. šŸŒ Based in Sudan and Saudi Arabia, dedicated to academic excellence and community impact.

Professional Profiles:

scopus

Education šŸŽ“

Ph.D. in Computer Science from Omdurman Islamic University, Sudan (2018ā€“2021). šŸŽ“ Masterā€™s Degree in Computer Science from Sudan University of Science and Technology (2003ā€“2005). šŸŽ“ B.Sc. in Computer Science from Omdurman Islamic University, Sudan (1995ā€“1999). šŸ“š Comprehensive training in research skills, academic advising, and IT tools like Mendeley, Latex, and iThenticate.

Experience šŸ–„ļø

Lecturer in Computer Science at Prince Sattam bin Abdul-Aziz University, Saudi Arabia (2013ā€“present). šŸ‘©ā€šŸ’¼ Supervisor and Coordinator roles in quality, academic advising, and measurement (2014ā€“2020). šŸ‡øšŸ‡© Lecturer at Omdurman Islamic University, Sudan (2005ā€“2012). šŸ‘©ā€šŸ”¬ E-teaching and training specialist with Arab Board experience (2023).

Awards and Honors šŸ†

Certificates of Appreciation from PSAU for contributions to quality, development, and academic planning. šŸ™Œ Recognized for voluntary services, including extracurricular activities and technical support for students and staff. ā­ Esteemed arbitrator in scientific and innovation conferences. šŸ“œ Active contributor to enhancing the learning environment with innovative solutions.

Research Focus šŸ”

Data mining, text mining, and information security are core research areas. šŸ“Š Interested in qualitative research, outcome-based education, and e-learning systems. šŸŒ Advocates for advancing academic IT tools like Prezi, Mendeley, and iThenticate. šŸ›”ļø Exploring cybersecurity methods and their application in education and industry.

āœļøPublications Top Note :

1. Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living

Published in: SN Computer Science, 2024, 5(5), 549

Summary: This paper proposes a novel classification model for urban-related tweets using arithmetic optimization integrated with deep learning to support sustainable urban living solutions.

2. Enhancing Traffic Flow Prediction in Intelligent Cyber-Physical Systems

Published in: IEEE Transactions on Consumer Electronics, 2024, 70(1), pp. 1889ā€“1902

Summary: Introduces a Bi-LSTM approach enhanced with a Kalman filter for accurate traffic flow prediction, addressing challenges in intelligent cyber-physical systems.

Citations: 5

3. Deer Hunting Optimization with Deep Learning-Driven Automated Fabric Defect Detection and Classification

Published in: Mobile Networks and Applications, 2024, 29(1), pp. 176ā€“186

Summary: Utilizes the Deer Hunting Optimization algorithm with deep learning to achieve high accuracy in detecting and classifying fabric defects.

Citations: 1

4. Automatic Recognition of Cyberbullying in the Web of Things and Social Media Using Deep Learning Framework

Published in: IEEE Transactions on Big Data, 2024

Summary: Develops a deep learning-based framework to detect and prevent cyberbullying within social media and IoT environments.

5. Artificial Rabbit Optimizer with Deep Learning for Fall Detection in IoT Environment

Published in: AIMS Mathematics, 2024, 9(6), pp. 15486ā€“15504

Summary: Introduces the Artificial Rabbit Optimizer combined with deep learning to enhance fall detection systems for disabled individuals in IoT environments.

Citations: 1

6. Computational Linguistics-Based Arabic Poem Classification and Dictarization Model

Published in: Computer Systems Science and Engineering, 2024, 48(1), pp. 98ā€“114

Summary: Proposes a computational linguistics model to classify Arabic poems and enhance their dictarization process.

7. Abstractive Arabic Text Summarization Using Hyperparameter Tuned Denoising Deep Neural Network

Published in: Intelligent Automation and Soft Computing, 2024, 38(2), pp. 153ā€“168

Summary: Develops a deep neural network with hyperparameter tuning for effective abstractive summarization of Arabic texts.

Citations: 1

8. Chaotic Equilibrium Optimizer-Based Green Communication With Deep Learning Enabled Load Prediction in IoT Environment

Published in: IEEE Access, 2024, 12, pp. 258ā€“267

Summary: Presents a Chaotic Equilibrium Optimizer combined with deep learning to improve green communication and load prediction in IoT systems.

Citations: 2

9. Land Use and Land Cover Classification Using River Formation Dynamics Algorithm With Deep Learning on Remote Sensing Images

Published in: IEEE Access, 2024, 12, pp. 11147ā€“11156

Summary: Leverages the River Formation Dynamics algorithm integrated with deep learning for efficient land use and land cover classification using remote sensing data.

Citations: 4

10. Prediction of Sleep Quality Using Wearable-Assisted Smart Health Monitoring Systems

Published in: Journal of King Saud University – Science, 2023, 35(9), 102927

Summary: Utilizes wearable technology and statistical data to predict sleep quality, providing insights into personalized smart health monitoring systems.

Citations: 1

Conclusion

The candidateā€™s extensive experience, academic qualifications, and contributions to computer science, particularly in data mining and information security, make them a strong contender for the Research for Best Researcher Award. With some strategic enhancements to highlight impactful research and global contributions, their profile could exemplify the qualities of an award-winning researcher in computer science.

Prof. Yang Zhao | Meteorology Artificial Intelligence | Young Scientist Award

Prof. Yang Zhao | Meteorology Artificial Intelligenc | Young Scientist Award

Prof. Yang Zhao, Ocean University of China, China

Prof. Yang Zhao is academic and researcher in the field of renewable energy, holds a PhD in Bio systems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

Professional Profiles:

Educational BackgroundšŸŽ“

2016.09 ā€“ 2019.06: Ph.D. in Meteorology Chinese Academy of Meteorological Sciences, China & Nanjing University ofĀ  Science & Technology, Ch Supervisor: Prof. Xiangde Xu 2013.09 ā€“ 2016.06: Master of Science in Meteorology Chinese Academy of Meteorological Sciences, China Supervisor: Prof. Xiangde Xu 2009.09 ā€“ 2013.06: Bachelor of Science in Atmospheric Science Chengdu University ofĀ  Technology, China

Honors and Major AwardsšŸ†

Outstanding Graduate Student, Chinese Academy of Meteorological Sciences (2019)Outstanding Graduate Student, Nanjing University ofĀ  Science & Technology (2019)Presidential Scholarship, Nanjing University of Science & Technology (2018)
National Scholarship, Nanjing University ofĀ  Science & Technology (2018) First Class Scholarship for Ph.D. Student, Nanjing UniversityofĀ  Science & Technology (2018) The First Prize of Outstanding Graduate Student Award, China Meteorological Administration (2017) Excellent Organization Award of Summer School, Chinese Academy of Meteorology (2015)

šŸ”¬ Research Area:Ā 

Synoptic-scale Atmospheric Dynamics (Jet, Front, Storm Tracks, Cyclones, Rossby waves) Ā Atmospheric Water Cycle (Moisture sources, Moisture channel, Atmospheric Rivers) Machine Learning and Deep Learning (Atmospheric Rivers) Climate Dynamics; Future precipitation prediction (ENSO-Volcano; CMIP6)

šŸ“– PublicationsĀ  Top Note :

The third atmospheric scientific experiment for understanding the earthā€“atmosphere coupled system over the Tibetan Plateau and its effects

Authors: P Zhao, X Xu, F Chen, X Guo, X Zheng, L Liu, Y Hong, Y Li, Z La, H Peng, …

Bulletin of the American Meteorological Society, 99(4), 757-776, 2018

Spatiotemporal variation in the impact of meteorological conditions on PM2.5 pollution in China from 2000 to 2017

Authors: Yanlin Xu, Wenbo Xue, Yi Lei, Qing Huang, Yang Zhao, Shuiyuan Cheng, Zhenhai …

Atmospheric Environment, 77, 2020

Impact of Meteorological Conditions on PM2.5 Pollution in China during Winter

Authors: Y Xu, W Xue, Y Lei, Y Zhao, S Cheng, Z Ren, Q Huang

Atmosphere, 9(11), 429, 2018

Effect of the Asian Water Tower over the Qinghai-Tibet Plateau and the characteristics of atmospheric water circulation

Authors: X Xu, L Dong, Y Zhao, Y Wang

Chin. Sci. Bull, 64(27), 2830-2841, 2019

Vertical structures of dust aerosols over East Asia based on CALIPSO retrievals

Authors: D Liu, T Zhao, R Boiyo, S Chen, Z Lu, Y Wu, Y Zhao

Remote Sensing, 11(6), 701, 2019

Trends in observed mean and extreme precipitation within the Yellow River Basin, China

Authors: Y Zhao, X Xu, W Huang, Y Wang, Y Xu, H Chen, Z Kang

Theoretical and applied climatology, 136, 1387-1396, 2019

Enhancement of the summer extreme precipitation over North China by interactions between moisture convergence and topographic settings

Authors: Yang Zhao, Deliang Chen, Jiao Li, Dandan Chen, Yi Chang, Juan Li, Rui Qin

Climate Dynamics, 38, 2020

Extreme precipitation events in East China and associated moisture transport pathways

Authors: Y Zhao, XD Xu, TL Zhao, HX Xu, F Mao, H Sun, YH Wang

Science China Earth Sciences, 59, 1854-1872, 2016

The largeā€scale circulation patterns responsible for extreme precipitation over the North China plain in midsummer

Authors: Y Zhao, X Xu, J Li, R Zhang, Y Kang, W Huang, Y Xia, D Liu, X Sun

Journal of Geophysical Research: Atmospheres, 124(23), 12794-12809, 2019

Are precipitation anomalies associated with aerosol variations over eastern China?

Authors: X Xu, X Guo, T Zhao, X An, Y Zhao, J Quan, F Mao, Y Gao, X Cheng, …

Atmospheric Chemistry and Physics, 17(12), 8011-8019, 2017