Sara Shirowzhan

UNSW Sydney

Dr. Sara Shirowzhan is a lecturer at the School of Built Environment (BE), University of New South Wales (UNSW), Sydney, Australia, where she teaches the City Analytics and Construction programs. She also serves as the co-chair of BE\'s Smart Cities and Infrastructure Cluster. Dr. Shirowzhan works as tomorrow\'s leading champion for the Chartered Institute of Building (CIOB). Her research interests include sensing technologies, enhanced GIS, BIM, digital twins, and artificial intelligence in technologies pertinent to BE informatics. She teaches and supervises students at UNSW in the areas of GIS, BIM, digital twins, AI, machine learning, city analytics, urban informatics, smart cities, infrastructure, construction informatics, and other relevant topics. She now serves on the editorial boards of the journals MDPI and Advances in Civil Engineering. She is also a topic board member of the ISPRS International Journal of Geo-Information as well as Buildings. Dr. Shirowzhan received her Ph.D. in Geomatics Engineering from the School of Civil and Environmental Engineering, UNSW.

Sara Shirowzhan

2books edited

4chapters authored

Latest work with IntechOpen by Sara Shirowzhan

Real-time, web-based, and interactive visualisations are proven to be outstanding methodologies and tools in numerous fields when knowledge in sophisticated data science and visualisation techniques is available. The rationale for this is because modern data science analytical approaches like machine/deep learning or artificial intelligence, as well as digital twinning, promise to give data insights, enable informed decision-making, and facilitate rich interactions among stakeholders.The benefits of data visualisation, data science, and digital twinning technologies motivate this book, which exhibits and presents numerous developed and advanced data science and visualisation approaches. Chapters cover such topics as deep learning techniques, web and dashboard-based visualisations during the COVID pandemic, 3D modelling of trees for mobile communications, digital twinning in the mining industry, data science libraries, and potential areas of future data science development.

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