Kenichi Soga

Donald H. McLaughlin Chair in Mineral Engineering
Chancellor's Professor
Research Interests
Infrastructure sensing and modeling, Energy Geotechnics, Fundamentals of soil behavior, Geotechnical structures, Ground engineering, Soil & granular mechanics

447 Davis Hall

Office Hours

Tuesdays, 4-5pm

Thursdays, 4-5pm

Soga headshot

Kenichi Soga is the Donald H. McLaughlin Professor in Mineral Engineering and a Chancellor’s Professor at UC Berkeley. Soga is also the Director of the Berkeley Center for Smart Infrastructure, a faculty scientist at Lawrence Berkeley National Laboratory, and serves as a Special Advisor to the Dean of the College of Engineering for Resilient and Sustainable Systems. 

Soga’s research focuses on infrastructure sensing, performance-based design and maintenance of infrastructure, energy geotechnics, and geomechanics. He has published more than 450 journal and conference papers and is the co-author of "Fundamentals of Soil Behavior" with Professor James K Mitchell.

He is a member of the National Academy of Engineering, a fellow of the UK Royal Academy of Engineering, the Institution of Civil Engineers (ICE), the American Society of Civil Engineers (ASCE), and the Engineering Academy of Japan. 

He is the recipient of several notable awards, including the George Stephenson Medal and Telford Gold Medal from ICE in 2006, the Walter L. Huber Civil Engineering Research Prize from ASCE in 2007, and the UCB Bakar Prize for his work on commercialization of smart infrastructure technologies in 2022.

For more details, please go to



Ph.D., University of California, Berkeley, 1994         

M.Eng., Kyoto University, Japan, 1989

B.Eng., Kyoto University, Japan, 1987

Kenichi’s research focuses on infrastructure sensing through distributing optics sensing, wireless sensor network, energy harvesting, and computer vision. He also focuses on energy geotechnics, city-scale modeling of infrastructure systems, performance-based design and maintenance of underground structures, and geotechnics from micro to macro. Soga’s research group is interested in developing new monitoring technologies, which will provide insight into the behavior of infrastructure, detect anomalies, and provide data for performance analyses. They are also conducting research on city-scale modeling and simulations to evaluate the value of sensing for better management of infrastructure during operation as well as for better response during and after natural disasters such as earthquakes and wildfires. Here are a few of the research projects Soga is currently working on below: 

  • Sensing Technologies - Sensor technologies and methodologies are developed to transform the future of infrastructure and geomechanics through smart information. The data gathered permits an assessment of the behavior of the infrastructure in its environment and allows performance analyses. The group develops, tests, and delivers new robust, resilient, and adaptable technologies, such as distributed fiber optic sensors (DFOS), wireless sensor network (WSN), energy harvesting, and computer vision. 
  • City-Scale Modeling - In the city-scale modeling group, Soga’s team develops scientific simulation models to capture the behaviors of infrastructures and integrate them into a “system of systems” model to obtain insights. Wildfire is a recurring natural disaster in California and many parts of the world. The pathway to improve the current planning and operation is a complex socio-technical process that spans the environment, the organization, and communications structures, as well as the human behaviors before, during, and after emergency situations. In this theme, Soga’s research group has developed/deployed three interconnected models on the fire progression, communications process, and traffic evacuations. We have teamed up with designers, game developers, social scientists, fire and traffic agencies, as well as local communities to achieve a streamlined process from academic research to social impacts.
  • Computational Geomechanics - Soga’s team conducts research in the field of computational geomechanics utilizing a variety of methods, including the Material point method (MPM), Finite element method (FEM), and Lattice element method (LEM) in research and consulting applications such as landslides, slope failures, tunneling, soil-pipeline interactions, geothermal energy, and deep borehole drilling.
  • Shallow Geothermal Energy - Shallow geothermal energy is an emerging renewable green energy that can provide heating and cooling for buildings in a safe, non-emitting, and affordable way, thus reducing the dependence on natural gas. Soga’s research group is exploring the potential of shallow geothermal energy through in-situ geothermal investigation, city-scale geothermal simulation and optimization, and the development of an advanced energy delivery system. 
  • Machine Learning for Construction and Infrastructure - Soga's team utilizing and developing data analytics techniques to better understand and solve complex problems in underground construction and infrastructure.


No mentions in Spotlights