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 74 of 99
2005
An MDL framework for data clustering
P Kontkanen, P Myllymäki, W Buntine, J Rissanen, H Tirri
Advances in minimum description length: Theory and applications, 323-354, 2005
Research93 citationsThe G12 project: Mapping solver independent models to efficient solutions
PJ Stuckey, MG De La Banda, M Maher, K Marriott, J Slaney, Z Somogyi, ...
International Conference on Logic Programming, 9-13, 2005
Research70 citationsSolving set constraint satisfaction problems using ROBDDs
PJ Hawkins, V Lagoon, PJ Stuckey
Journal of Artificial Intelligence Research 24, 109-156, 2005
Machine Learning70 citationsTesting for termination with monotonicity constraints
M Codish, V Lagoon, PJ Stuckey
International Conference on Logic Programming, 326-340, 2005
Machine Learning64 citationsOptimizing compilation of constraint handling rules in HAL
C Holzbaur, MG De La Banda, PJ Stuckey, GJ Duck
Theory and Practice of Logic Programming 5 (4-5), 503-531, 2005
Machine Learning59 citationsWhen do bounds and domain propagation lead to the same search space?
C Schulte, PJ Stuckey
ACM Transactions on Programming Languages and Systems (TOPLAS) 27 (3), 388-425, 2005
Machine Learning51 citationsAbstract interpretation for constraint handling rules
T Schrijvers, PJ Stuckey, GJ Duck
Proceedings of the 7th ACM SIGPLAN international conference on Principles …, 2005
Machine Learning48 citationsIncremental connector routing
M Wybrow, K Marriott, PJ Stuckey
International Symposium on Graph Drawing, 446-457, 2005
Research31 citationsDiscrete principal component analysis
W Buntine, A Jakulin
Proceedings of the Subspace, Latent Structure and Feature Selection …, 2005
Research25 citationsA temporally adaptive content-based relevance ranking algorithm
J Perkiö, W Buntine, H Tirri
Proceedings of the 28th annual international ACM SIGIR conference on …, 2005
Research18 citationsTopic-specific scoring of documents for relevant retrieval
W Buntine, J Löfström, S Perttu, K Valtonen
Workshop on Learning in Web Search: 22nd International Conference on Machine …, 2005
Research18 citationsOpportunities from open source search
W Buntine, K Aberer, I Podnar, M Rajman
IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2-8, 2005
Optimization17 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.