Dr. Aiai Wang | Deep Learning | Best Researcher Award
Doctorate at University of Science and Technology Beijing, China
Profiles
Early Academic Pursuits
Dr. Aiai Wang began her academic journey with a Bachelor of Science in Mining Engineering from the School of Mining Engineering, North China University of Science and Technology (2017โ2021). Her solid foundation in mining principles led her to pursue a Masterโs degree in Civil Engineering at the University of Science and Technology Beijing (USTB), School of Civil and Resource Engineering (2021โ2024). Her postgraduate studies were marked by rigorous research and an emphasis on digital mining and intelligent mining technologies.
Professional Endeavors
In her current role as Secretary of the 16th Party Branch, Dr. Wang exemplifies leadership in academic and organizational settings. She is actively engaged in digital transformation projects in mining, bringing innovation to tailings sand cementation and filling physical dynamics. Her work bridges academic research with practical applications, emphasizing smart mining technologies for safe and efficient resource extraction.
Contributions and Research Focus
Dr. Aiai Wang has significantly contributed to the field of cementitious tailings fills and mining support systems. Her research interests include pore structure characterization, CT image reconstruction, nano-cellulose reinforcement, and intelligent modeling of mine systems. Notably, she co-authored several peer-reviewed articles exploring dynamic behaviors of backfills, including:
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“Effect of height to diameter ratio on dynamic characteristics…” in Construction and Building Materials (2022).
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“Influence of nano cellulose on cementitious tailings backfill…” in Construction and Building Materials (2022).
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“Quantitative analysis of pore characteristics…” in Journal of Materials Research and Technology (2023).
Impact and Influence
Her scientific contributions are well-recognized, garnering 10+ citations and influencing sustainable and safe practices in mining engineering. Through co-authored patents and software copyrights, Dr. Wang has developed intelligent systems for mining tunnel support, lithology identification, and strength prediction of fill media. These innovations are revolutionizing safety measures and process optimization in deep mining operations.
Academic Cites and Honors
Dr. Aiai Wang is a decorated scholar. She was named one of USTBโs โTop Ten Academic Starsโ in 2023 and has received multiple accolades, including the National Scholarship for Master’s Students, Taishan Iron and Steel Scholarship, and First-Class Academic Scholarships for consecutive academic years. Her consistent performance has also earned her recognition as an Outstanding Three-Good Graduate Student at USTB.
Technical Skills and Certifications
Dr. Aiai Wang holds technical certifications in English proficiency, including CET4 and CET6, and is proficient in developing predictive models and intelligent systems for mining processes. She has co-developed several copyrighted software systems, such as:
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Macro Strength Prediction System for Tail Sand Cementation
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Comprehensive Tunnel Roof Support Classifier
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Automatic Lithology Identifier & Flexible Support Designer
Teaching and Mentorship
While primarily research-focused, Dr. Wang is involved in guiding junior peers within the School of Civil and Resource Engineering. Her involvement in academic committees and student organizations reflects her mentorship spirit and dedication to nurturing future mining engineers.
Legacy and Future Contributions
Dr. Aiai Wangโs work lays a crucial foundation for the integration of AI, digital modeling, and nanomaterials in mine engineering. Her patented methodologies for non-blasting mining, mesh-supported fill reinforcement, and automated support design are paving the way for next-generation, sustainable, and high-precision mining operations. As she advances her academic career, Dr. Wang is poised to be a key thought leader in intelligent and green mining technologies.
Publications
Quantitative Analysis of Pore Characteristics of Nanocellulose Reinforced Cementitious Tailings Fills Using 3D Reconstruction of CT Images
- Authors: Wang, Aiai; Cao, Shuai; Yilmaz, Erol
Journal: Journal of Materials Research and Technology
Year: 2023