Evidence-based Computational Solutions for Infrastructure Industry Challenges
Malaysian Theatre, Basement B121
Glyn Davis Building (Melbourne School of Design)
Guest seminar by Dr Negin Yousefpur, ARUP
Throughout the past two decades, the fast progression of high-performance computing systems together with cloud storage and computing technology for large databases, have led to enormous potential of evidence based computational methods to unfold in various fields of engineering including infrastructures. This seminar will discuss some of these data-driven computational technics and how they are developed and implemented to address key geotechnical challenges in the infrastructure industry. Implementation of artificial intelligence and machine learning technics together with Bayesian probabilistic methods for specific geotechnical problems subjected to risk and uncertainty are presented. This includes bridge scour forecast and monitoring, and evaluation of bridges with unknown foundation, among other problems.
Dr Negin Yousefpour, Senior Geotechnical Engineer
Dr Negin Yousefpour
Senior Geotechnical Engineer
Dr. Negin Yousefpour received her PhD at Texas A&M University in 2013, where she worked on deterministic and probabilistic computational modelling in geotechnics. Upon graduation she joined Arup as a geotechnical engineer, where she has been working on challenging research and industry projects across the world in infrastructure, building, and oil and gas sectors. Negin’s main areas of expertise are applied artificial intelligence and machine learning, Bayesian probabilistic and stochastic methods, and advanced numerical analyses for predictive modelling, risk and uncertainty assessments, and performance simulation in geotechnics. Negin has led various research projects collaborating with government agencies, universities and research institutions across the US, UK, and Australia. She has also published and presented her research in numerous wellrespected journals and conferences.