BRIGHT SPARKS LECTURE - 5TH INTERNATIONAL SYMPOSIUM ON MACHINE LEARNING AND BIG DATA IN GEOSCIENCE (5ISMLG), HONG KONG, CHINA
The YMPG in collaboration with the Organising Committee for 5th International Symposium on Machine Learning and Big Data in Geoscience (5ISMLG) in Hong Kong would like to announce the winners of the Bright Spark Lecture Award to four distinguished young geotechnical engineers/academics listed below. They were invited to give keynote lectures on 10-13 May 2026.
Tongming Qu, Full Professor, Wuhan University
Bright Spark Lecture Title: "From Pixels to Physics: Machine Learning-Enabled Spatial Intelligence for Geotechnical Engineering Digital Twins"
Xin Liu, Full Professor, Wuhan University
Bright Spark Lecture Title: "Simultaneous Bayesian Learning of Multi-Source Data"
Andreas-Nizar Granitzer, Andreas-Nizar Granitzer, Norwegian Geotechnical Institute
Bright Spark Lecture Title: "Unlocking the Potential of Data-Centric Geotechnics: A Cross-Disciplinary Perspective"
Jian He, Research Assistant Professor, The Hong Kong University of Science and Technology
Bright Spark Lecture Title: "Regional rain-induced landslide risk assessment and management"
The Bright Spark Lecture Award was established to promote young members of the ISSMGE to play a major role in various international and regional conferences. Recipients of this award are invited to give a keynote lecture at ISSMGE conferences. All Technical Committee conference organisers and Member Society conference organisers are encouraged to select Bright Spark Lecturers at their conferences. Details regarding the award can be found on the ISSMGE website: https://www.issmge.org/the-society/awards/bright-spark-lecture-award.
We invite everyone, especially young geotechnical engineers, to come and enjoy the lectures. We hope these lectures can inspire and motivate us further to excel in our beloved field, geotechnical engineering.
Winners Bio
Tongming Qu
Dr. Tongming Qu is a full Professor at the Institute of Water Engineering Sciences, Wuhan University (2025.09-). He obtained his Ph.D. in Civil Engineering from Swansea University, UK (2018.01-2021.12). Prior to his current role, he served as a Research Assistant Professor (2023.05-2025.08) and Postdoc Fellow (2022.05-2023.05) at the Hong Kong University of Science and Technology (HKUST).
His research specializes in computational geomechanics, focusing on integrating machine learning and big data into geotechnical engineering. Dr. Qu has secured several competitive grants as Principal Investigator, including awards from the National Natural Science Foundation of China (NSFC) and the Hong Kong Research Grants Council (GRF). He also contributes as a Co-Investigator on major projects, such as an RGC Theme-based Project with funding of HK$62.9 million.
He has published over 70 journal papers in leading journals such as Computer-Aided Civil and Infrastructure Engineering. His work has been recognized with honors including the First Prize of the Science and Technology Progress Award (2024) and the Best PhD Thesis award from Swansea University (2022). He also holds 13 patents in China and actively serves as a reviewer for nearly 60 international journals.
Xin Liu
Dr. Liu is a full Professor at the State Key Laboratory of Water Resource Engineering at Wuhan University (WHU). He earned two PhD degrees respectively from WHU and City University of Hong Kong (CityU) in 2020 and conducted three years of post-doctoral research at CityU. His research focuses on data fusion and machine learning, development of geotechnical digital twins, and geotechnical risk assessment. He has published over fifteen journal papers as the first author, including two highly cited papers (>100 citations). One of his first-author papers published on Computers and Geotechnics was awarded the Scott Sloan Best Paper Award in 2025. In the last three years, he has secured seven research grants with a total amount over RMB 7 million yuan (approximately US$1M). He was granted the Excellent Young Scientists Fund (Overseas) from National Science Foundation of China in 2023. He earned the Special Prize of Science and Science and Technology Progress Award (2025) from Changjiang Water Resources Commission of China for pioneering geotechnical digital twin research and applications. He teaches Soil Mechanics to undergraduates. As a member of ISSMGE and Chinese Institution of Soil Mechanics and Geotechnical Engineering, he actively engages in various activities in the global geotechnical community.
Andreas-Nizar Granitzer
Andreas-Nizar Granitzer holds three MSc degrees in Mining & Tunnelling, Industrial Management & Business Administration, and Data Science & Intelligent Analytics. He completed his PhD at Graz University of Technology in 2024 under the supervision of Prof. Franz Tschuchnigg. His doctoral research, conducted in collaboration with Seequent -The Bentley Subsurface Company in Delft, focused on the development of the Embedded Finite Element with implicit interaction surface, a novel finite element type scheduled for release in the finite element software PLAXIS 3D.
He has received several awards for his teaching and scientific achievements, including the Austrian State Prize for Academic Teaching (2023) and for PhD Theses (2024). Since May 2025, he has been working as a Research and Project Engineer at the Norwegian Geotechnical Institute (NGI).
His research interests lie at the interface of geotechnics, data science, and computational mechanics, with a particular focus on data-centric geotechnics. His current work includes surrogate modelling for automated design optimization, multi-agent systems for monitoring data processing, and climate-adaptive design for infrastructure projects. A detailed overview of his background, research activities and publications is provided in the attached CV.
Jian He
Dr. Jian He is a Research Assistant Professor at the Hong Kong University of Science and Technology. His research focuses on advanced geohazard risk assessment and management. With over 30 publications in leading international journals, his work has garnered more than 1,200 citations and an h-index of 17. His research has secured more than HK$ 5 million in funding from the Hong Kong Innovation and Technology Commission as well as industry partners. He developed the first regional landslide risk assessment method, enabling real-time analysis and nowcasting of landslide risk, directly supporting emergency management operations. He also pioneered a novel landslide catastrophe model for landslide insurance risk management. These innovations have been implemented by government agencies and a major power supply company in Hong Kong, enhancing the regions resilience to geohazards in the face of climate change.
