Frits is a world-class optimisation scientist working where reinforcement learning meets real-world constraints. Formerly with CSIRO and Monash, he’s built autonomous systems that plan, adapt, and improve under pressure - from smart cities to complex supply chains and rostering systems.
At RabbitHawk, Frits unites forecasting and optimisation into a living partnership - creating self-learning decision loops that continuously refine themselves.
His obsession: systems that don’t just solve problems once, but keep getting smarter every day.
Frits' Google Scholar page is here.
Christoph is one of the world’s leading forecasting researchers. His models are used by Google, Meta, and Walmart ... and now, RabbitHawk.
A Senior Research Fellow at Monash University (Australia) and Senior Fellow in Computer Science & AI at the University of Granada (Spain), Christoph has spent his career designing architectures that make forecasting adaptive, explainable, and genuinely useful.
He brings mathematical precision and global credibility to RabbitHawk - but pairs it with a rare bias toward simplicity: a drive to make the complex understandable and the abstract practical.
At RabbitHawk, Christoph is building the forecasting core that helps companies see the future clearly—then change it.
Find out more on his website, or find his publications on Google Scholar
Abi is a machine-learning scientist who turns chaos into pattern. His research in multimodal and graph AI explores how connected data - transactions, conversations, behaviours - reveals cause and effect.
At RabbitHawk, Abi gives forecasting purpose: not just predicting what might happen, but mapping how to get from today’s “A” to tomorrow’s “B.”
He’s the architect behind RabbitHawk’s ability to reason across structured, unstructured, and contextual data - the intelligence that connects numbers to meaning, and foresight to action.
Find his publications on Google Scholar
Paul has spent two decades turning advanced analytics into tools that humans actually use.
A strategist-founder by background, he’s led cross-disciplinary teams in the US, Australia, and New Zealand - translating insight into action for retail, tech, and growth-stage companies.
Paul has helped startups, enterprises, and even struggling organisations move from a myriad of starting points to goals not many dared to think possible.
At RabbitHawk, Paul designs the UX and product architecture that allows teams to harness the depth of Christoph, Abi, and Frits’ technology and reach their possibly impossible goals.
Paul's LinkedIn page is here.
Peter J. Stuckey is a Professor in the Faculty of Information Technology at Monash University, and project leader in the Data61 CSIRO laboratory.
Prof. Stuckey is a pioneer in constraint programming, the science of modeling and solving complex combinatorial problems.
With a Google Scholar h-index of 69, his research interests include: discrete optimization; programming languages, in particular declarative programming languages; constraint solving algorithms; bio-informatics; and constraint-based graphics. He enjoys problem solving in any area, having publications in e.g. databases, timetabling, and system security, and working with companies such as Oracle and Rio Tinto. Prof. Stuckey received a B.Sc and Ph.D both in Computer Science from Monash University in 1985 and 1988 respectively.
In 2009 he was recognized as an ACM Distinguished Scientist. In 2010 he was awarded the Google Australia Eureka Prize for Innovation in Computer Science for his work on lazy clause generation. He was awarded the 2010 University of Melbourne Woodward Medal for most outstanding publication in Science and Technology across the university. In 2019 he was elected as a Fellow of the Association for the Advancement of Artificial Intelligence.
Prof. Stuckey's Google Scholar profile is here.
Professor Wray Buntine is Australia’s foremost scholar for the statistical analysis of text and related structured content and their predictive modelling. His global reputation was built over several decades of state of the art machine learning, generative AI and large language model research.
Professor Buntine has authored 18 book chapters, 48 journal articles, and 81 refereed conference papers. His work includes several software products and two patents, with over 13,000 citations and a Google Scholar h-index of 51, reflecting his significant impact on the fields of data science and machine learning.
Professor Buntine is currently Director of the Computer Science Program at VinUniversity. He is set to serve as the General Chair for the 2024 Asian Conference on Machine Learning in Hanoi. He co-edits the ACM Transactions on Probabilistic Machine Learning and serves on editorial boards for several other journals. He has worked on projects for the Helsinki Institute for Information Technology, NASA Ames Research Center, University of California, Berkeley, and Google. His active involvement in the academic community includes senior program committee roles at top conferences like IJCAI, UAI, AAAI, EMNLP, ICLR, ACML, and NeurIPS. Previously, he was the founding director of the Master of Data Science program at Monash University, where he also directed the Machine Learning Group.
With respect to large language models, he has published with Dr. Ehsan Shareghi of Monash University on use of LLMs in contexts requiring uncertainty or the resort to external knowledge resources. At VinUniversity he works with Dr. Le Duy Dung on recommender systems and has published with Dr. Nguyen Quoc Dat of VinAI, co-developer of PhoGPT, and students on the application of LLMs for a variety of applications including healthcare. He also co-developed the MTP multimedia dataset published at ACL 2024 and is a member of Meta’s Open Innovation AI Research Community, where he works with a small community of scientists furthering educational applications of Generative AI and Llama in particular.
Dr Buntine's Google Scholar profile is here.
