The members of the Gradient Institute team have deep expertise in machine learning research and engineering as well as commercial technology consulting and technology deployment. They also have specific and rare experience in developing ethically-aware machine learning systems.
The team is motivated to bring about a world in which ethics are an integral part of data science and machine learning systems, and ensure this new ethical machine learning technology works to make the world fairer and more sustainable.
Bill has spent more than 20 years building teams of researchers, software engineers and product designers to develop novel techniques, technologies and products and get these into widespread use.
He started as a software engineer and research assistant in machine learning (ML), working on the c4.5 library, one of the world’s first ML technologies used commercially. He has led R&D for global technology companies (Canon and Unisys) and government-funded research institutions (CSIRO and NICTA) and been on the executive teams of three leading Australian science and technology organisations (CiSRA, NICTA and CSIRO’s Data61).Most recently, he has been Director of Engineering and Design at Data61 where he led a team of 100 data scientists, engineers, user experience designers and product managers, developing new techniques, technologies and products. This included work in areas incuding ML (including ethically-aware ML), data privacy, computational law, geospatial systems and more.
He designed and taught a Masters course in IT Innovation at University of Sydney for seven years to 2016 covering topics such as technology life cycles, disruptive innovation, open innovation, open source strategies, organisational culture for innovation and innovation ecosystems. He has sat on several government data-related committees influencing approaches to data sharing, data privacy, data analytics and open data as well as advisory groups at two Australian universities. He has degrees in computer science, history of art and cognitive science.
Tiberio has spent the last 20 years working on machine learning in numerous roles as a student, researcher, academic, entrepreneur and practitioner. He started his research career in theoretical physics as an undergraduate, following with a degree in electrical engineering and a PhD in computer science.
He has published extensively in top-tier academic journals and conferences in machine learning, graduated numerous PhD students, and collaborated widely with researchers from across the world. He held research positions in Brazil, Canada, France, and Australia, including adjunct academic appointments at the ANU, UNSW, and University of Sydney. He spent 10 years at NICTA, where he worked as a researcher, research leader, and research group manager in the machine learning group.
In 2012 he co-founded Ambiata, a data science NICTA spin-off focusing on applying rigorous scientific methodologies for personalised decision-making using machine learning, causal inference and randomised controlled trials. As Ambiata’s Chief Scientist, he led the design of decision-making algorithms that have touched millions of consumers across several industries, including banking, telecommunications, media, insurance, and retail, spanning personalised decisions from pricing and credit scoring to advertisement and product configuration.Tiberio believes the path to a more ethical world is through a deeper understanding of the cause and effect relationships between actions and wellbeing. He is a proponent of the rigorous application of scientific thinking and methods beyond academia and into all areas of industry, government and society more broadly.
A number of eminent experts from the above disciplines have agreed to be on the Gradient Institute Advisory Board and the names will be announced shortly.