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 84 of 99
2000
Optimization of queries using relational algebraic theta-semijoin operator
D Srivastava, PJ Stuckey, S Sudarshan
US Patent 6,032,144, 2000
Machine Learning159 citationsIncremental analysis of constraint logic programs
M Hermenegildo, G Puebla, K Marriott, PJ Stuckey
ACM Transactions on Programming Languages and Systems (TOPLAS) 22 (2), 187-223, 2000
Machine Learning124 citationsEffecting constraint magic rewriting on a query with the multiset version of the relational algebric theta-semijoin operator
D Srivastava, PJ Stuckey, S Sudarshan
US Patent 6,061,676, 2000
Machine Learning81 citationsStatistical machine learning for large-scale optimization
J Boyan, W Buntine, A Jagota
Neural Computing Surveys 3 (1), 1-58, 2000
Machine Learning30 citationsA Lagrangian reconstruction of GENET
KMF Choi, JHM Lee, PJ Stuckey
Artificial Intelligence 123 (1-2), 1-39, 2000
Research27 citationsImproving temporal joins using histograms
I Sitzmann, PJ Stuckey
International Conference on Database and Expert Systems Applications, 488-498, 2000
Research25 citationsType classes and constraint handling rules
K Glynn, M Sulzmann, PJ Stuckey
arXiv preprint cs/0006034, 2000
Machine Learning22 citationsO-trees: a constraint-based index structure
I Sitzmann, P Stuckey
Proceedings 11th Australasian Database Conference. ADC 2000 (Cat. No …, 2000
Machine Learning21 citationsMode checking in HAL
MG de la Banda, PJ Stuckey, W Harvey, K Marriott
International Conference on Computational Logic, 1270-1284, 2000
Research11 citationsComputational Logic—CL 2000: First International Conference London, UK, July 24–28, 2000 Proceedings
J Lloyd, V Dahl, U Furbach, M Kerber, KK Lau, C Palamidessi, LM Pereira, ...
Research8 citationsHistogram-based Temporal Joins
I Sitzmann, P Stuckey
Technical Report TR2000/7, Department of Computer Science and Software …, 2000
Research1 citationsProceedings of the First International Conference on Computational Logic
JW Lloyd, V Dahl, U Furbach, M Kerber, KK Lau, C Palamidessi, ...
Springer-Verlag, 2000
Research1 citations
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“Forecasting for Data Scientists”, a free 30-chapter video course by co-founder Dr Christoph Bergmeir, from fundamentals to advanced deep learning.