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 79 of 99
2003
Interactive type debugging in Haskell
PJ Stuckey, M Sulzmann, J Wazny
Proceedings of the 2003 ACM SIGPLAN workshop on Haskell, 72-83, 2003
Research108 citationsRemoving node overlapping in graph layout using constrained optimization
K Marriott, P Stuckey, V Tam, W He
Constraints 8 (2), 143-171, 2003
Machine Learning80 citations- Research79 citations
Improving linear constraint propagation by changing constraint representation
W Harvey, PJ Stuckey
Constraints 8 (2), 173-207, 2003
Machine Learning55 citationsEfficient computation of stochastic complexity
P Kontkanen, W Buntine, P Myllymäki, J Rissanen, H Tirri
Proceedings of the Ninth International Conference on Artificial Intelligence …, 2003
Research49 citationsResource usage verification
K Marriott, PJ Stuckey, M Sulzmann
Programming Languages and Systems: First Asian Symposium, APLAS 2003 …, 2003
Research48 citationsExtending arbitrary solvers with constraint handling rules
GJ Duck, PJ Stuckey, M Garcia de la Banda, C Holzbaur
Proceedings of the 5th ACM SIGPLAN international conference on Principles …, 2003
Machine Learning43 citationsTermination analysis with types is more accurate
V Lagoon, F Mesnard, PJ Stuckey
International Conference on Logic Programming, 254-268, 2003
Research29 citationsIs multinomial PCA multi-faceted clustering or dimensionality reduction?
WL Buntine, S Perttu
International Workshop on Artificial Intelligence and Statistics, 57-64, 2003
Research29 citationsPropagation redundancy in redundant modelling
CW Choi, JHM Lee, PJ Stuckey
International Conference on Principles and Practice of Constraint …, 2003
Research25 citationsBox constraint collections for adhoc constraints
CK Cheng, JHM Lee, PJ Stuckey
International Conference on Principles and Practice of Constraint …, 2003
Machine Learning24 citationsAutomatic derivation of statistical algorithms: The EM family and beyond
AG Gray, B Fischer, J Schumann, W Buntine
Advances in Neural Information Processing Systems 15, 2002
Research17 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.