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 68 of 99
2008
- Research7 citations
- Machine Learning6 citations
Smooth linear approximation of non-overlap constraints
G Gange, K Marriott, PJ Stuckey
International Conference on Theory and Application of Diagrams, 45-59, 2008
Machine Learning5 citationsDynamic analysis of bounds versus domain propagation
C Schulte, PJ Stuckey
International Conference on Logic Programming, 332-346, 2008
Machine Learning3 citationsDynamic variable elimination during propagation solving
C Schulte, PJ Stuckey
Proceedings of the 10th international ACM SIGPLAN conference on Principles …, 2008
Research3 citations- Research3 citations
Principles and Practice of Constraint Programming-14th International Conference, CP 2008. Sydney, Australia, September 2008. Proceedings
PJ Stuckey
Lecture Notes in Computer Science 5202, 2008
Machine Learning2 citationsEntwicklung und Evaluation einer Kalibrierungsmethode für 3D-Ultraschall
C Bergmeir, M Seitel, C Frank, R De Simone, HP Meinzer, I Wolf
ResearchBayesian Analysis of the Poisson-Dirichlet Process
W Buntine, M Hutter
Bayesian MethodsNatural Language Retrieval of Grocery Products Proceedings
P Nurmi, E Lagerspetz, W Buntine, P Floreen, J Kukkonen, P Peltonen
Research
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.