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Scientific Computing in an AI World

11 May 2023
6.30pm – 7.30pm AEST
Colombo Theatre B (B16), UNSW Sydney Kensington campus
This event has ended

Scientific computing – loosely defined as model-based computation – is everywhere (even if often hidden) in the modern world, from weather forecasts to smart phone design. In this public event scientific computing meets the modern world of artificial intelligence, which can be a data-driven, model-free zone. In this conversation experts from a range of disciplines will explore the connections and challenges, and chart a way forward.

Join the panellists Prof. Mike Giles (University of Oxford), Prof. Ian Sloan (UNSW), Dr Sahani Pathiraja (UNSW) and Prof. Wenjie Zhang (UNSW), in a conversation on Scientific Computing in an AI world, chaired by Robyn Williams AO.

This event is part of  the Nexus initiative of the School of Mathematics and Statistics, UNSW. The Nexus lectures (from the Latin word to bind together) have been established by the School to promote outstanding research in fundamental mathematics and to further future collaborations across different mathematical fields.

Photo of Robyn Williams

Robyn Williams AO


Robyn Williams AO, one of Australia's best-known broadcasters, has presented science programs on ABC radio and televisions since 1972. Early in his career he made guest appearances on The GoodiesMonty Python's Flying Circus, and Doctor Who. The author of 16 books, he is the first journalist to be elected a fellow of the Australian Academy of Science. He was a visiting fellow at Balliol College, Oxford, and is a visiting professor at the University of New South Wales and the University of Queensland.

Photo of Prof. Mike Giles

Professor Mike Giles (Professor of Scientific Computing, University of Oxford)


Mike Giles is a Professor of Scientific Computing in the Mathematical Institute of Oxford University. After 25 years developing and analysing methods for Computational Fluid Dynamics, in collaboration with Rolls-Royce, he has spent the past 15 years developing and analysing Multilevel Monte Carlo methods for a range of applications. He also has extensive research interests in high performance computing, particularly on GPUs. He became a Fellow of SIAM in 2018, and was head of department 2018-2022.

Photo of Prof. Ian Sloan

Professor Ian Sloan AO (School of Mathematics & Statistics, UNSW)


Ian Sloan is a leading Australian mathematician, well known for his research in computational mathematics and theoretical physics. He is a Fellow of the Australian Academy of Science and of SIAM, and the recipient of many awards, including the Lyle Medal of the Academy of Science and the Szekeres Medal of the Australian Mathematical Society. He has been President of both the Australian Mathematical Society and the International Council for Industrial and Applied Mathematics.

Photo of Prof. Wenjie Zhang

Professor Wenjie Zhang (School of Computer Science & Engineering, UNSW)


Wenjie Zhang is a Professor, ARC Future Fellow, Deputy Head of School (Research and Operations) and Head of Data and Knowledge Research Group in School of Computer Science and Engineering, University of New South Wales Australia. Her research interests lie in developing efficient (e.g., real-time) and scalable techniques for data-intensive applications. She has published over 220 research papers in leading international journals and conferences. Her research has been supported by 12 Australian Research Council funded projects and several industry projects. Wenjie is the recipient of the Australasian CORE Chris Wallace Research Award in 2019. Her works receive the ACM SIGMOD Research Highlight Award 2021, one of the Best Papers in SIGMOD 2020, ICDE 2013/2012/2010, and several Best (Student) Paper Awards from international conferences.

Photo of Sahani Pathiraja

Dr Sahani Pathiraja (School of Mathematics & Statistics, UNSW)


Sahani Pathiraja is a Lecturer (tenure track assistant professor) in Data Science in the School of Mathematics and Statistics, UNSW Sydney. She is a Chief Investigator in the Australian Research Council Industrial Transformation Training Centre on Data Analytics for Resources and Environment (DARE) and co-lead of the Fundamental Data Science Theme at the UNSW Data Science Hub. Her broad research interests lie in the theory and application of data science methods. One of her overarching goals is to develop stronger connections between the mathematical & statistical foundations of data science methods and their applications, particularly in solving environmental and biomedical problems. After completing her PhD at UNSW Sydney in Environmental Engineering, she took up a postdoctoral position in the Institute of Mathematics at the University of Potsdam, Germany as part of a collaborative research centre on Data Assimilation.