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 93 of 99
1994
Proceedings of the Post-ILPS'94 Workshop on Constraints and Databases: Nov. 17, 1994, Ithaca, NY, USA
P Revesz, D Srivastava, P Stuckey
University of Nebraska, 1994
Machine Learning- Research
- Bayesian Methods
Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry
W Buntine, DH Fisher
Knowledge-Based Artificial Intelligence Systems in Aerospace and Industry 2244, 1994
Machine LearningKnowledge-based artificial intelligence systems in aerospace and industry: 5-6 April 1994, Orlando, Florida
W Buntine, DH Fisher
(No Title), 1994
Machine LearningProposal: Interactive Media for Research in Uncertainty
WL Buntine
Uncertainty in Artificial Intelligence, 118, 1994
Machine LearningOperations on Graphical Models with Plates
WL Buntine, H Lum Jr
Bayesian Methods
1993
The 3 R's of optimizing constraint logic programs: Refinement, removal and reordering
KG Marriott, PJ Stuckey
Proceedings of the 20th ACM SIGPLAN-SIGACT symposium on Principles of …, 1993
Machine Learning92 citationsSemantics of constraint logic programs with optimization
K Marriott, PJ Stuckey
ACM Letters on Programming Languages and Systems (LOPLAS) 2 (1-4), 197-212, 1993
Machine Learning37 citationsTree classification software
W Buntine
NASA, Washington, Technology 2002: The Third National Technology Transfer …, 1993
Research35 citationsProjecting CLPR constraints
J Jaffar, MJ Maher, PJ Stuckey, RHC Yap
New Generation Computing 11 (3), 449-469, 1993
Machine Learning29 citations- Machine Learning29 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.