Zhenzhong Hu

    He received both his BE and PhD degree in the Department of Civil Engineering at Tsinghua University, China. He was a visiting researcher in Carnegie Mellon University.
    He is now the associate professor in Shenzhen International Graduate School, Tsinghua University, and also the secretary general of the BIM Specialty Committee of the China Graphics Society.
    His research interests include information technologies in civil and marine engineering, building information modeling (BIM) and digital disaster prevention and mitigation.
  • TOP-1

    The research group will recruit several PHD and master students and 2 postdocs.

    There are three requirements for doctoral and master students  enrollment: (1) Applicants should have an engineering background and have a strong interest in information technology. Applicants should have obtained a relevant bachelor's or master's degree; (2) Strong technical background, including but not limited to research experiences in BIM/GIS, Internet, digital twin, artificial intelligence, etc. Candidates with research or practical experiences in algorithms, and the development of large-scale software systems or Web/App will be preferred; (3) Highly self-motivated, good written and oral English communication skills, and independent working ability.

    Postdoctoral recruitments should also meet the following two points: (1) The applicant should be under the age of 35 and have obtained a doctoral degree no more 3 years; (2) The research directions are civil engineering information technology, Marine environmental information modeling and application, data-driven knowledge discovery and application, etc. (Note: postdoctoral candidates are required to present a half-hour academic presentation, including the main research works during PHD period and future postdoctoral work plans).

    If you are interested, please send your resume, transcripts and work plan to the email: hu.zhenzhong@sz.tsinghua.edu.cn. For details, please see: PHD Master Recruitment and Postdoctoral Recruitment.

  • TOP-2

    26 November 2021, Discharge of treated Fukushima nuclear accident contaminated water: macroscopic and microscopic simulations has been published on National Science Review, which is a full affirmation of the students and teachers of the subject group who are generous and rigorous in their learning! NSR officer micro-push high-quality and efficient, reflecting China's outstanding leading journals of the super-class level! Thanks to the director of singhua University's Institute for Ocean Engineering (IOE), Zhang Jianmin's guidance and support, thanks to the editorial department and reviewers for their high evaluation!

    The results of this study are of great significance for the prediction of long-term spread of pollutants, the rational response of nuclear wastewater discharge plans and the monitoring of subsequent radioactive material concentrations. In the future, we will continue to deepen our research, Further explore the long-term impact of the discharge of nuclear waste water on the whole ocean and mankind, and provide important decision support for the country and the world to deal with the nuclear wastewater crisis!

    Note: National Science Review , whose impact factor in 2021 is 17.275, is the top journal in the multi-discipline domain. For more information, please see the introduction video.

  • 2026-01-22

    The paper "Multiscale investigation of ternary precursor proportioning in engineered geopolymer composites: Effects of silica fume replacement ratio and GGBS content" has been published in the journal Construction and Building Materials

    To reduce cement consumption and promote eco-friendly construction materials, engineered geopolymer composites (EGC) have been developed as sustainable alternatives to engineered cementitious composites (ECC). This study systematically investigates the effects of precursor tailoring, specifically silica fume (SF) replacement ratio (5–15 %) and ground granulated blast-furnace slag (GGBS) content (20–80 %), on the mechanical properties, microstructure, and sustainability of EGC. The results show that appropriate precursor composition enables a wide strength coverage, with compressive strengths ranging from 48 to 117 MPa, meeting the requirements of different structural applications. Digital image correlation (DIC) and in-situ crack analysis reveal stable multiple cracking behavior, with ultimate tensile strains consistently exceeding 8 % and effective crack width control within 120 μm. These findings confirm the achievement of multiple cracking and high tensile ductility through coordinated fibre/matrix interaction and tailored precursor design. Additionally, microstructural characterizations (XRD, FTIR, TGA) show that higher GGBS contents promote C-(N)-A-S-H gel formation and a degree of geopolymerization, leading to matrix densification and enhanced mechanical properties. Moderate SF replacement also contributes to pore filling, further increasing the matrix compactness. From a sustainability perspective, a cradle-to-gate life cycle assessment (LCA), using typical M45-ECC as a benchmark, shows that the developed EGC achieve approximately 50 % lower embodied carbon while maintaining comparable manufacturing feasibility. Overall, this study demonstrates that precursor-tailored EGC can simultaneously satisfy structural performance criteria and sustainability targets, highlighting their potential for low-carbon practical applications.

    Note: Construction and Building Materials is a top journal in the field of engineering and technology in Q1, with an impact factor of 8.0 in 2025. The first author of the paper is doctoral student Wan Feihong, and Professor Guo Yutao is the corresponding author. The research results were funded by the Shenzhen Science and Technology Program and the National Natural Science Foundation of China.

  • 2026-01-10

    The paper "Low-carbon remediation of contaminated marine mud sediment for efficient in-situ recycling and application" has been published in the journal ENGINEERING Environment

    This study addresses the issue of difficult disposal of contaminated marine sediment and its constraints on waste management by proposing a low-carbon solidification treatment using aluminosilicate raw materials to achieve in-situ resource utilization as engineering backfill material. By incorporating a mixture of 25% ordinary Portland cement, fly ash, slag, and 5% river sand, the unconfined compressive strength of the solidified body can reach up to 8.69 MPa, and it can efficiently stabilize heavy metals, making the product comply with environmental safety standards in both China and the United States. XRD analysis reveals that the material is mainly composed of SiO₂, with the formation of secondary phases such as calcium carbonate, iron-manganese oxides, and complex silicates, which collectively endow it with excellent structural mechanical properties. This technology not only provides a feasible path for the large-scale recycling and utilization of contaminated marine silt but also helps improve resource efficiency, protect the environment, and support the realization of carbon reduction and carbon neutrality goals. 

    Note: ENGINEERING Environment, formerly known as Frontiers of Environmental Science & Engineering, is a journal in the Q1 zone of the field of environmental science and ecology, with an impact factor of 6.4 in 2025. Dr. Dassekpo is the corresponding author. The research results were supported by the  Guangdong  Basic and  Applied  Basic  Research  Foundation.

  • 2026-01-15

    The rule-based information extraction for mechanical-electrical-plumbing-specific semantic web has been cited 100 times in Google Scholar.

    In view of the strong professionalism and scarcity of labeled data in the building mechanical, electrical and plumbing (MEP) field, which makes it difficult to effectively apply traditional deep learning information extraction methods, this paper proposes a rule-based MEP information extraction method. This method builds a large-scale corpus through a "snowball" strategy and uses suffix matching and dependency path matching algorithms to achieve efficient entity recognition and relationship extraction, respectively. At the same time, the "meta-link" and "path filtering" mechanisms are introduced to mine information beyond complex patterns. Experimental results show that the constructed MEP semantic network achieves good results in terms of entity and relationship extraction accuracy, and significantly outperforms several classic deep learning models in extraction precision. 

    Note: Automation in Construction is the most influential journal in the field of civil engineering information technology, classified as a Q1 SCI journal with an impact factor of 11.5 in 2025. The first author of the paper is Wu Langtao, a master's student from the Department of Civil Engineering at Tsinghua University, and I am the corresponding author.