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 75 of 99
2005
The ALVIS document model for a semantic search engine
W Buntine, K Valtonen, M Taylor
2nd Annual European Semantic Web Conference, 1-2, 2005
Optimization17 citationsType inference for guarded recursive data types
PJ Stuckey, M Sulzmann
arXiv preprint cs/0507037, 2005
Bayesian Methods15 citationsMulti-faceted information retrieval system for large scale email archives
J Perkio, V Tuulos, W Buntine, H Tirri
The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05 …, 2005
Machine Learning14 citationsTopic-specific link analysis using independent components for information retrieval
W Buntine, J Löfström, S Perttu, K Valtonen
Grobelnik et al.[63], 2005
Research6 citations- Optimization6 citations
Constraint abduction and constraint handling rules
M Sulzmann, J Wazny, PJ Stuckey
Schrijvers and Frühwirth (2005b), 63-78, 2005
Machine Learning5 citationsChecking modes of HAL programs
MG De La Banda, W Harvey, K Marriott, PJ Stuckey, B Demoen
Theory and Practice of Logic Programming 5 (6), 623-667, 2005
Research3 citationsSolutions of implication constraints yield type inference for more general algebraic data types
PJ Stuckey, M Sulzmann
Manuscript, April, 2005
Machine Learning3 citationsStatic ranking of web pages, and related ideas
W Buntine
Open Source Web Information Retrieval, 23-26, 2005
Research3 citationsEduskuntaryhmien äänestyskäyttäytyminen ja-koheesio vuoden 2003 valtiopäivillä
A Pajala, A Jakulin, W Buntine
Research3 citationsImproved inference for checking type annotations
PJ Stuckey, M Sulzmann, J Wazny
Technical Report TRA2/05, The National University of Singapore, 2005
Bayesian Methods2 citationsCo-induction and type improvement in type class proofs
M Sulzmann, J Wazny, PJ Stuckey
Research1 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.