Research & Decision Science
Where forecasting research becomes operational decision infrastructure
RabbitHawk is built on peer-reviewed work in probabilistic forecasting, hierarchical reconciliation, optimization and applied AI, translated into systems that improve real decisions under real constraints.
- publications
- 1,181publications
- citations
- 53,485citations
- highly cited papers
- Top 1%highly cited papers
Scientific foundations
Methods proven in the literature, applied in production
Our team’s research is recognized at the field’s leading venues and used at scale by major organizations. We bring that rigor to enterprise planning, but judge every method by whether it improves decisions in practical settings.
Research → product
| Research area | Enterprise problem | RabbitHawk capability |
|---|---|---|
| Hierarchical forecasting | Local plans do not add up to executive targets | Reconciled forecasts across every level |
| Probabilistic forecasting | Point forecasts hide risk | Full predictive distributions, intervals and scenario ranges |
| Optimization | Forecasts do not tell teams what to do | Constraint-aware recommendations |
| Agentic AI | Context is trapped in emails and notes | Context ingestion and decision agents |
| Human-in-the-loop AI | Automation without trust creates resistance | Approval, override and audit trails |
| Alignment science | Teams optimize against conflicting goals | 90North alignment and goal clarity |
Hierarchical forecasting
Local plans do not add up to executive targets
Reconciled forecasts across every level
Probabilistic forecasting
Point forecasts hide risk
Full predictive distributions, intervals and scenario ranges
Optimization
Forecasts do not tell teams what to do
Constraint-aware recommendations
Agentic AI
Context is trapped in emails and notes
Context ingestion and decision agents
Human-in-the-loop AI
Automation without trust creates resistance
Approval, override and audit trails
Alignment science
Teams optimize against conflicting goals
90North alignment and goal clarity
Selected publications
The full peer-reviewed database: search by title, author, venue, category or year.
1,181 results · page 59 of 99
2012
Worldwide AI
N Barnes, P Baumgartner, H Tiberio Caetano, GK Durrant-Whyte, ...
AI Magazine 33 (3), 115-128, 2012
Machine LearningAI@ NICTA
N Barnes, P Baumgartner, T Caetano, H Durrant-Whyte, G Klein, ...
Ai Magazine 33 (3), 115-115, 2012
Machine LearningA General Implementation Framework
PC de Guzmán, M Carro, MV Hermenegildo, P Stuckey
Functional and Logic Programming: 11th International Symposium, FLOPS 2012 …, 2012
ResearchAn improved Lagrangian relaxation method for maximising the net present value of large resource-constrained projects
H Gu, MG Wallace, PJ Stuckey
International Symposium on the Mathematical Theory of Networks and Systems, 2012
Machine LearningPreface: Demo session
M Van Leeuwen, F Bonchi, M Berlingerio, WL Buntine, R Trasarti, ...
IEEE International Conference on Data Mining Workshops 2012, 2012
Research
2011
Improving topic coherence with regularized topic models
D Newman, EV Bonilla, W Buntine
Advances in neural information processing systems 24, 2011
Research284 citationsAutomatic generation of protein structure cartoons with Pro-origami
A Stivala, M Wybrow, A Wirth, JC Whisstock, PJ Stuckey
Bioinformatics 27 (23), 3315-3316, 2011
Research215 citationsExplaining the cumulative propagator
A Schutt, T Feydy, PJ Stuckey, MG Wallace
Constraints 16 (3), 250-282, 2011
Machine Learning148 citationsLeave-one-out cross-validation
GI Webb, C Sammut, C Perlich, T Horváth, S Wrobel, KB Korb, WS Noble, ...
Encyclopedia of machine learning, 600-601, 2011
Research105 citationsSampling table configurations for the hierarchical Poisson-Dirichlet process
C Chen, L Du, W Buntine
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
Research58 citationsSolving talent scheduling with dynamic programming
M Garcia de la Banda, PJ Stuckey, G Chu
INFORMS Journal on Computing 23 (1), 120-137, 2011
Optimization55 citationsHalf reification and flattening
T Feydy, Z Somogyi, PJ Stuckey
International Conference on Principles and Practice of Constraint …, 2011
Research46 citations
Learn the science behind the engine
“Forecasting for Data Scientists”, a free 30-chapter video course by co-founder Dr Christoph Bergmeir, from fundamentals to advanced deep learning.