Office: 431 Davis Hall
Email: dayu ‘dot’ apoji ‘at’ berkeley ‘dot’ edu
Dayu Apoji is a PhD Candidate in Civil & Environmental Engineering (CEE) with a designated emphasis in Computational and Data Science Engineering (CDSE), University of California at Berkeley. He is currently working on the implementation of machine learning on earth pressure balance shield machine (EPBM) tunneling data. The research goal is to develop a fundamental framework for autonomous tunnel boring machine (TBM) systems. This can be achieved by enabling the machine to (i) perceive its geologic environment, (ii) control the tunneling excavation processes (iii) control the ground stability and displacement, as well as (iv) control the shield attitude and trajectory.
Dayu is also a certified geotechnical engineer (Indonesia). Prior to joining UC Berkeley, he worked for Soil Mechanics Lab – ITB in Bandung, RHDHV in Jakarta, and AECOM in Singapore. He has more than 8 years of work experience in the industry and has been involved in various building and infrastructure projects (e.g. high-rise & industrial buildings, elevated & underground railways, ports & marine structures, airports, etc.) across Southeast Asia region, such as Indonesia, Singapore, Malaysia, Vietnam, and Timor Leste.
Dayu obtained his B.Eng and M.Eng in Civil Engineering (with specialization in Geotechnical Engineering) from ITB, Indonesia. He also pursued his postgraduate diploma (DIC) and M.Sc in Earthquake Engineering from Imperial College London, UK.
– Supervised and unsupervised interpretation of the encountered geologic conditions during tunneling based on TBM operation data
– Exploring feature interactions and modeling EPBM excavation processes using Bayesian Networks
– Connecting tunneling data from satellite, ground instruments, and TBM sensors
– Prediction and control of TBM trajectory