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 97 of 99
1991
Two papers on feed-forward networks
WL Buntine, AS Weigend
Research
1990
- Research384 citations
A constraint logic programming shell
P Lim, PJ Stuckey
International Workshop on Programming Language Implementation and Logic …, 1990
Machine Learning19 citationsMeta programming as constraint programming
P Lim, PJ Stuckey
Proceedings of the 1990 North American conference on Logic programming, 416-430, 1990
Machine Learning18 citationsEliminating negation from normal logic programs
K Kanchanasut, P Stuckey
International Conference on Algebraic and Logic Programming, 217-231, 1990
Research12 citations- Bayesian Methods5 citations
Interface logic programming
JN Crossley, P Lim, P Stuckey
Australian Computer Journal 21 (2), 49-55, 1990
Research3 citationsThe CLP (Si) Language and System
J JA FFAR, S Michaylov, PJ ST UCKEY, R Yap
Research report, IBM, 1990
Research3 citations
1989
Learning classification rules using Bayes
W Buntine
Proceedings of the sixth international workshop on Machine learning, 94-98, 1989
Research74 citationsExpanding query power in constraint logic programming languages
MJ Maher, PJ Stuckey
IBM Thomas J. Watson Research Division, 1989
Machine Learning45 citations- Research41 citations
On meta-programming in CLP (R)
N Heintze, S Michaylov, P Stuckey, R Yap
the 1989 North American Conference on Logic Programming (NACLP’89), 52-66, 1989
Research29 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.