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 86 of 99
1999
Autonomous science decision making for Mars sample return
TL Roush, V Gulick, R Morris, P Gazis, G Benedix, C Glymour, J Ramsey, ...
Research3 citationsTemporal joins that make use of histogram information
I Sitzmann, P Stuckey
Technical Report TR1999/28, Department of Computer Science and Software …, 1999
Research1 citations
1998
- Machine Learning1,487 citations
The semantics of constraint logic programs
J Jaffar, M Maher, K Marriott, P Stuckey
The Journal of Logic Programming 37 (1-3), 1-46, 1998
Machine Learning295 citations- Machine Learning100 citations
Foundations of aggregation constraints
KA Ross, D Srivastava, PJ Stuckey, S Sudarshan
International Workshop on Principles and Practice of Constraint Programming …, 1994
Machine Learning67 citations- Machine Learning43 citations
Constraint representation for propagation
W Harvey, PJ Stuckey
International Conference on Principles and Practice of Constraint …, 1998
Machine Learning38 citationsAutomated pair-wise comparisons of microbial genomes
AK Bansal, P Bork, PJ Stuckey
Math. Model. Sci. Comput 9, 1-23, 1998
Machine Learning32 citationsA Lagrangian reconstruction of a class of local search methods
KMF Choi, JHM Lee, PJ Stuckey
Tenth IEEE International Conference on Tools with Artificial Intelligence …, 1998
Optimization17 citationsDifferential methods in logic program analysis
MG de la Banda, K Marriott, P Stuckey, H Søndergaard
The Journal of Logic Programming 35 (1), 1-37, 1998
Research16 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.