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.

2026-03-26

The paper "Typhoon-Induced Risk Evolution in Wind Farms: From Disaster-Inducing Factors Identification to Domino Effect Assessment" has been published in the journal Reliability Engineering & System Safety. 

In response to the technical accidents caused by typhoons in the complex waters of the South China Sea, this study proposes a Disaster-Inducing and Risk Evaluation (DIRE) framework. This framework integrates two modules: the Disaster Inducing Factor Extraction Model (DIFEM), which identifies the key environmental driving factors that cause damage to wind turbines through a hybrid physical-data fusion analysis; and the Hierarchical Analytical Domino Evaluation System (HADES), which realizes systematic hazard classification, hierarchical structuring, probability assessment, and consequence assessment. Through the analysis of five typhoon-induced disaster events in the South China Sea, this study not only identified the common and specific disaster-causing factors that cause damage to wind turbines, but also quantified the cascading disaster risks. The findings of this study provide reliable data and decision-making support for disaster prevention and mitigation on wind farms.

Note: "Reliability Engineering & System Safety" is a top journal in the field of engineering technology in the Q1 zone, with an impact factor of 11.0 in 2025. The first author of the paper is doctoral student Li Yilin and postdoctoral researcher Li Yihong, and I am the corresponding author. The research results were supported by the National Key R&D Program of China, the Guangdong Basic and Applied Basic Research Foundation, the Shenzhen Science and Technology Program, and the Shuimu Tsinghua Scholar Program.

2026-03-25

The paper "Digital disaster prevention for ocean engineering: Current progress and future directions" has been published in the journal Ocean Engineering. 

The increasing frequency of typhoons and other extreme climate events has intensified the risks of natural hazard-triggered technological accidents (Natech). Traditional disaster-prevention approaches, largely dependent on static analyses, are no longer sufficient for real-time risk identification or proactive mitigation in ocean engineering. This review synthesizes recent progress in digital disaster prevention, focusing on three core areas: disaster-inducing factor identification, disaster mechanism modeling, and structural safety assessment. The paper integrates physics-based numerical modeling, data-driven simulation, and system dynamics to analyze hazard triggers and cascading failures. It highlights applications of digital twins and deep learning in scenario-based risk analysis and early-warning systems, particularly for offshore wind farms. Furthermore, it proposes a forward-looking digital technology system that integrates environmental sensing, interpretable modelling, and resilience-oriented decision support. Overall, digital disaster prevention provides a significant pathway toward more adaptive, predictive, and resilient safety management in ocean engineering.

Note: Ocean Engineering is a top journal in the field of engineering technology, classified in Q1, with an expected impact factor of 5.5 in 2025. I am the first author and corresponding author of the paper. The research was funded by the Shenzhen Science and Technology Program and the Guangdong Basic and Applied Basic Research Foundation.

2026-03-05

The paper titled “Dynamics-Based Adaptive Scheduling for Large-Scale Edge Computing Networks in Smart Cities” has been published in  IEEE Internet of Things Journal.

Addressing the critical challenge of real-time and efficient task scheduling in large-scale distributed edge computing networks caused by the exponential growth of task requests from the rapid proliferation of IoT devices in smart cities, this paper proposes a novel Dynamics-based Adaptive Scheduling (DAS) method. By innovatively transforming the complex task scheduling problem into a two-dimensional geometric model and leveraging the principles of forward dynamics simulation, DAS achieves efficient and non-iterative task assignment, successfully reducing computational complexity to O(n log n). Simulation results demonstrate that the DAS method significantly outperforms existing benchmark strategies: it reduces service response time by 9% to 15%, improves system load balance by 93% to 98%, and decreases overall energy consumption by 2% to 12%. This solution effectively resolves scheduling efficiency and reliability issues in large-scale edge computing environments.

Note: The IEEE Internet of Things Journal is a top journal in the field of engineering and technology, ranked in the Q1 zone, with an impact factor of 8.9 in 2025. The first author of the paper is Master's student Feng Yixiao, and Professor Ren Zhengru from Shanghai Jiao Tong University serves as the corresponding author. The research was supported by the National Key R&D Program of China.