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 71 of 99
2006
Type processing by constraint reasoning
PJ Stuckey, M Sulzmann, J Wazny
Asian Symposium on Programming Languages and Systems, 1-25, 2006
Machine Learning27 citationsA hybrid BDD and SAT finite domain constraint solver
P Hawkins, PJ Stuckey
International Symposium on Practical Aspects of Declarative Languages, 103-117, 2006
Machine Learning27 citationsFast node overlap removal—correction
T Dwyer, K Marriott, PJ Stuckey
Research25 citationsA stochastic non-CNF SAT solver
R Muhammad, PJ Stuckey
Pacific Rim International Conference on Artificial Intelligence, 120-129, 2006
Research23 citationsPrincipal type inference for GHC-style multi-parameter type classes
M Sulzmann, T Schrijvers, PJ Stuckey
ASIAN Symposium on Programming Languages and Systems, 26-43, 2006
Bayesian Methods18 citationsRealizing the e-science desktop peer using a peer-to-peer distributed virtual machine middleware
L Ni, A Harwood, PJ Stuckey
Proceedings of the 4th international workshop on Middleware for grid …, 2006
Multi-Agent Systems13 citationsAdding constraint solving to Mercury
R Becket, MG de la Banda, K Marriott, Z Somogyi, PJ Stuckey, M Wallace
International Symposium on Practical Aspects of Declarative Languages, 118-133, 2006
Machine Learning13 citationsSIGIR06 workshop report: Open source information retrieval systems (OSIR06)
WG Yee, M Beigbeder, W Buntine
ACM SIGIR Forum 40 (2), 61-65, 2006
Research13 citationsNP-completeness of minimal width unordered tree layout
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Graph Algorithms and Applications 5 5, 295, 2006
Research12 citationsOptimal sum-of-pairs multiple sequence alignment using incremental Carrillo and Lipman bounds
AS Konagurthu, PJ Stuckey
Journal of Computational Biology 13 (3), 668-685, 2006
Machine Learning12 citationsSize-Change Termination Analysis in k-Bits
M Codish, V Lagoon, P Schachte, PJ Stuckey
European Symposium on Programming, 230-245, 2006
Research11 citationsThe dom event and its use in implementing constraint propagators
NF Zhou, M Wallace, PJ Stuckey
Technical report TR-2006013, CUNY Compute Science, 2006
Machine Learning4 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.