Home
News
Research
Publications
Grants
Teaching
Group
Codes


Professor Javen Qinfeng Shi


Director, Causal AI Group
Areas of interest: Causation, AI, Mind, Metaphysics, and Probabilistic Graphical Models
Professor, School of Computer and Mathematical Sciences (CMS) and Australian Institute for Machine Learning (AIML), University of Adelaide

Email: javen.shi at adelaide.edu.au
Tel: +61-8-8313-0324

Research Mission

We try to understand and causally influence the underlying distributions and processes to help and serve humanity.

Our world is undergoing inevitable and tumultuous changes. Causality, operating beneath the veneer of cause and effect, is essentially the way of change. Our causal AI methods can identify the root causes, discover latent variables, build immunity from spurious correlations, improve generalistion to diverse domains and distribution shifts, model the consequence of interventions, and answer What-If counterfactual questions. More importantly, causal AI holds the key to answer the reverse question: What is the ideal sequence of interventions, given resources or budgets, to optimise future outcomes?

Consulting?

Yes, we do consulting too.

Bio

Professor Javen Qinfeng Shi is the Founding Director of Causal AI Group at the University of Adelaide, and one of the directors at Australian Institute for Machine Learning (AIML). His research interests include causation, AI, mind and metaphysics. Google Scholar ranks him 7th globally in probabilistic graphical models, and 4th in causation. He served as a panellist for the Responsible AI Think Tank from 2022 to 2024 and currently holds the position of an AI Industry Forum panellist from 2024 onward, actively contributing to the cultivation of the national and state AI ecosystem. He has transferred his research to diverse industries including material discovery, agriculture, mining, sport, manufacturing, bushfire, health and education.

Recent awards include: 1) 1st place at Open Catalyst Challenge at NeurIPS AI for Science 2023, using AI to discover energy material; 2) Won AUS/NZ Bushfire Data Quest 2020 using AI to predict fire spread, which led to winning a Citizen Science Grant in 2021, and released a bushfire app NOBURN in 2023 (over 50 media coverages); 3) Finalist of SA Department of Energy and Mining Gawler Challenge 2020 (over 2k participants from 100+ countries) with his team's work being considered as ''The most innovative modelling'' by the judge panel; 4) 2nd place in Explorer Challenge 2019 (over 1k entries from 62 countries); 5) 1st place at SAIC Volkswagen Logistics Innovation Day for Smart Manufacturing 2019.

News