World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
50
Citations
7398
World Ranking
4174
National Ranking
837

Overview

Chongchong Qi is affiliated with Central South University in China and has contributed to research primarily within the fields of Engineering and Environmental Science. Their work spans several subfields, including Civil and Structural Engineering, Mechanical Engineering, Building and Construction, Artificial Intelligence, and Mechanics of Materials.

The primary topics addressed in Qi's research focus on various aspects related to mineral processing, geochemistry, and environmental considerations in engineering contexts. These topics include:

  • Mineral Processing and Grinding
  • Tailings Management and Properties
  • Geochemistry and Geologic Mapping
  • Concrete and Cement Materials Research
  • Rock Mechanics and Modeling
  • Coal and Its By-products
  • Mine drainage and remediation techniques

Qi's recent publications reflect an engagement with data-driven and computational methods in geotechnical and environmental engineering. Notable papers include:

  • "A spatially explicit deep learning neural network model for the prediction of landslide susceptibility," 2020, published in CATENA
  • "Big data management in the mining industry," 2020, published in International Journal of Minerals Metallurgy and Materials
  • "Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping," 2020, published in CATENA
  • "Permeability prediction of porous media using a combination of computational fluid dynamics and hybrid machine learning methods," 2020, published in Engineering With Computers
  • "Co-disposal of magnesium slag and high-calcium fly ash as cementitious materials in backfill," 2020, published in Journal of Cleaner Production

The researcher collaborates frequently with several co-authors, including Qiusong Chen, Mengting Wu, Qinli Zhang, Xinhang Xu, and Tao Hu. These collaborations indicate a networked research approach within the relevant engineering and materials science communities.

Qi's work is published in a variety of academic venues, indicating a multidisciplinary interest. The most frequent publication venues are:

  • International Journal of Minerals Metallurgy and Materials
  • Construction and Building Materials
  • SSRN Electronic Journal
  • Environmental Research
  • Journal of Cleaner Production

Across these contributions, Chongchong Qi's research employs modern analytical techniques including machine learning, computational fluid dynamics, and big data management. The focus on material properties, environmental impacts of mining, and engineering applications situates the researcher within applied science disciplines addressing industrial and environmental challenges.

Best Publications

  • Cemented paste backfill for mineral tailings management: Review and future perspectives

    Chongchong Qi;Andy Fourie

  • Recycling phosphogypsum and construction demolition waste for cemented paste backfill and its environmental impact

    Qiusong Chen;Qiusong Chen;Qinli Zhang;Chongchong Qi;Andy Fourie

  • A spatially explicit deep learning neural network model for the prediction of landslide susceptibility

    Dong Van Dao;Abolfazl Jaafari;Mahmoud Bayat;Davood Mafi-Gholami

  • Neural network and particle swarm optimization for predicting the unconfined compressive strength of cemented paste backfill

    Chongchong Qi;Andy Fourie;Qiusong Chen

  • A strength prediction model using artificial intelligence for recycling waste tailings as cemented paste backfill

    Chongchong Qi;Andy Fourie;Qiusong Chen;Qinli Zhang

  • Experimental investigation on the relationship between pore characteristics and unconfined compressive strength of cemented paste backfill

    Lang Liu;Lang Liu;Zhiyu Fang;Chongchong Qi;Bo Zhang

  • Big data management in the mining industry

    Chong chong Qi;Chong chong Qi

  • A new procedure for recycling waste tailings as cemented paste backfill to underground stopes and open pits

    Hongjian Lu;Chongchong Qi;Qiusong Chen;Deqing Gan

  • An experimental study on the early-age hydration kinetics of cemented paste backfill

    Lang Liu;Lang Liu;Pan Yang;Chongchong Qi;Bo Zhang

  • Coupling RBF neural network with ensemble learning techniques for landslide susceptibility mapping

    Binh Thai Pham;Trung Nguyen-Thoi;Chongchong Qi;Tran Van Phong

  • Experimental investigation on the strength characteristics of cement paste backfill in a similar stope model and its mechanism

    Qiu-song Chen;Qiu-song Chen;Qin-li Zhang;Andy Fourie;Xin Chen

  • An intelligent modelling framework for mechanical properties of cemented paste backfill

    Chongchong Qi;Qiusong Chen;Andy Fourie;Qinli Zhang

  • Co-disposal of magnesium slag and high-calcium fly ash as cementitious materials in backfill

    Lang Liu;Lang Liu;Shishan Ruan;Chongchong Qi;Chongchong Qi;Bo Zhang

  • Permeability prediction of porous media using a combination of computational fluid dynamics and hybrid machine learning methods

    Jianwei Tian;Chongchong Qi;Yingfeng Sun;Zaher Mundher Yaseen

  • Numerical study on the pipe flow characteristics of the cemented paste backfill slurry considering hydration effects

    Lang Liu;Lang Liu;Zhiyu Fang;Chongchong Qi;Bo Zhang

  • Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq

    Khabat Khosravi;Prasad Daggupati;Mohammad Taghi Alami;Salih Muhammad Awadh

  • A Novel Hybrid Soft Computing Model Using Random Forest and Particle Swarm Optimization for Estimation of Undrained Shear Strength of Soil

    Binh Thai Pham;Chongchong Qi;Lanh Si Ho;Trung Nguyen-Thoi

  • Towards Intelligent Mining for Backfill: A genetic programming-based method for strength forecasting of cemented paste backfill

    Chongchong Qi;Xiaolin Tang;Xiangjian Dong;Qiusong Chen

  • Prediction of evaporation in arid and semi-arid regions : a comparative study using different machine learning models

    Zaher Mundher Yaseen;Anas Mahmood Al-Juboori;Ufuk Beyaztas;Nadhir Al-Ansari

  • Immobilization and leaching characteristics of fluoride from phosphogypsum-based cemented paste backfill

    Qiu-song Chen;Shi-yuan Sun;Yi-kai Liu;Yi-kai Liu;Chong-chong Qi

  • Pressure drop in pipe flow of cemented paste backfill: Experimental and modeling study

    Chongchong Qi;Qiusong Chen;Qiusong Chen;Andy Fourie;Jianwen Zhao

  • Mechanics and safety issues in tailing-based backfill: A review

    Xu Zhao;Andy Fourie;Chong chong Qi

Frequent Co-Authors

Andy Fourie
Andy Fourie University of Western Australia
Zaher Mundher Yaseen
Zaher Mundher Yaseen King Fahd University of Petroleum and Minerals
Mohamed Elchalakani
Mohamed Elchalakani University of Western Australia
Indra Prakash
Indra Prakash Geological Survey of India
Nadhir Al-Ansari
Nadhir Al-Ansari Luleå University of Technology
Vijay P. Singh
Vijay P. Singh Texas A&M University
Dieu Tien Bui
Dieu Tien Bui University of South-Eastern Norway
Shamsuddin Shahid
Shamsuddin Shahid University of Technology Malaysia
Sinan Q. Salih
Sinan Q. Salih IEEE Computer Society
Guowei Ma
Guowei Ma University of Western Australia

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