BRIGHT SPARKS LECTURE - THIRD WORKSHOP ON THE FUTURE OF MACHINE LEARNING IN GEOTECHNICS (3FOMLIG), FLORENCE, ITALY
The YMPG in collaboration with the Organising Committee for Third Workshop on the Future of Machine Learning in Geotechnics (3FOMLIG) in Italy 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 15-17 October 2025.
Ze Zhou WANG, Marie Sklodowska-Curie Fellow, University of Cambridge
Bright Spark Lecture Title: "Machine Learning in Geotechnical Engineering: Opportunity or Overstated Hype? "
Yuanqin TAO, Dr. / Lecturer, Zhejiang University of Technology
Bright Spark Lecture Title: "Data assimilation and machine learning in braced excavations"
Monica LÖFMAN, Geotechnical Specialist & University Teacher, Ramboll Finland Ltd & Aalto University
Bright Spark Lecture Title: "Data-driven geotechnical design-Bridging the gap between research and practice"
Meng LU, Postdoctoral Fellow, Tongji University
Bright Spark Lecture Title: "Resilience-informed design of highway slopes against rainfall infiltration using generative machine learning"
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
Ze Zhou WANG
Dr. Ze Zhou Wang is a Marie Sktodowska-Curie fellow at the University of Cambridge and a core member of a European Commission-funded research project on smart materials for sustainable road infrastructure. Prior to Cambridge, he earned both a bachelor's degree in civil engineering and a doctorate from the National University of Singapore. Utilizing a combination of numerical simulations, machine learning, data- driven methods, and stochastic optimization, Dr. Wang's research aims to combine knowledge of material spatial heterogeneity with subsurface conditions to inform system-level simulations of geosystem-human-environment interactions and leverage field observations to calibrate numerical and data-driven models for knowledge discovery. His research has led to 28 journal articles and contributed to several research initiatives funded by the European Commission and the National Research Foundation of Singapore. He was the recipient of the Best Student Paper Award at the8th International Symposium for Geotechnical Safety & Risk held in Australia. Dr. Wang also actively engages with the academic community as a member of ISSMGE TC304 and TC309 and serves on editorial boards. Beyond his academic contributions, he has supported industry innovations through developing software applications employed by the government sector for ongoing underground infrastructure projects.
Yuanqin TAO
Dr. Yuanqin Tao is a lecturer in the College of Civil Engineering,Zhejiang University of Technology, China. She received her BEng degree in Hydraulic and Hydropower Engineering from Wuhan University in 2017 and her PhD degree in Geotechnical Engineering from Zhejiang University in 2022. Her research interests include data-driven methods for deep excavations, probabilistic inverse analysis of geotechnical structures, and quantification of soil spatial variability. She has served as the principal investigator for four research grants and seven industrial projects in geotechnical engineering. She has published more than 20 papers in journals such as Can. Geotech. J., Int. J. Numer. Anal. Met. Geomech., and Eng. Geol., and has co-authored one book. She holds five authorized patents or software copyrights. Dr. Tao has delivered presentations at seven academic conferences and has participated in organizing four workshops and conferences as a secretary or session chair. She currently serves as an early-career editorial board member for three journals and as an active reviewer for more than ten journals. She has received the Second Prize of the Science and Technology Award from the Zhejiang Society for Soil Mechanics and Geotechnical Engineering(2023).
Monica LÖFMAN
Dr. Monica Löfman works as a geotechnical specialist at Ramboll Finland Ltd and as a part- time university teacher at Aalto University. Dr. Löfman received her geotechnical engineer- ing PhD degree from Aalto University in 2022 Since then, she has actively worked to bridge the gap between industry and academia by sharing her time between Ramboll, Aalto Uni- versity and also Finnish Geotechnical Society. Her research interests include data-driven and probabilistic methods for site characterization and geotechnical assessment, compiling geodatabases to train ML/AI models, and Python programming. At Ramboll, she has led multiple R&D projects related to data-analysis andML/AI applications in geotechnics.She has worked as an educator not only at the university but also in the industry offering internal training, workshops and seminar talks. She has authored over 33 publications, from which 8 are journal papers and 15 are conference articles. She has co-authored the Eurocode guideline Reliability-based verification of limit states for geotechnical structures due to her expertise on soil statistics. She has peer reviewed papers for four scientific journals and cur- rently serves as a young editorial board member of the GEOAI journal, early career member of the FOMLIG council and secretary of the of the organizing committee of 3FOMLIG.
Meng LU
Dr Meng Lu is currently a postdoctoral fellow at the Department of Geotechnical Engineering, Tongji University, China. His research interests include intelligent prediction and resilience assessment of soil slopes against rainfall infiltration. Dr Lu was a visiting Ph.D. student at the University of Padua, Italy, from February2022 to February2023.He received his Ph.D.degree from Tongji University, China in September 2023. Dr Lu proposed the finite element material point numerical strategy for the entire process simulation of rainfall-induced landslides, which has been adopted by the open-source MPM platform Anura3D. Based on this, Dr Lu further constructed machine learning models to predict the runout of rainfall- induced landslides. His doctoral thesis was recognized by the International Consortium on Geo-disaster Reduction(ICGdR) as an excellent doctoral thesis. Dr Lu is now contributing to the generative Al-based prevention and mitigation of rainfall-induced landslides. He has used the generative machine learning to design anchor cables for slope reinforcement. Dr Lu has published 16 papers in prestigious geotechnical journals and is the host of 6 national and provincial projects. He is honored by the Shanghai Magnolia Talent Plan Pujiang Project(2024) and the Shanghai Postdoctoral Excellence Program(2024).
