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 52 of 99
2014
Constructing fuzzy rule-based systems with the R package “frbs”
LS Riza, C Bergmeir, F Herrera, JM Benítez
Research1 citationsGrounding bound founded answer set programs
RA Aziz, G Chu, PJ Stuckey
arXiv preprint arXiv:1405.3362, 2014
Research1 citationsExperiments with dynamic topic models
J Li, W Buntine
NewsKDD 2014: Data Science for News Publishing, 1-5, 2014
Research1 citations- Research
Introduction to the special issue on social web mining
F Bonchi, W Buntine, R Gavaldá, S Guo
ACM Transactions on Intelligent Systems and Technology (TIST) 5 (1), 1-2, 2014
Research
2013
Improving lda topic models for microblogs via tweet pooling and automatic labeling
R Mehrotra, S Sanner, W Buntine, L Xie
Proceedings of the 36th international ACM SIGIR conference on Research and …, 2013
Research689 citationsActigraph GT3X: validation and determination of physical activity intensity cut points
A Santos-Lozano, F Santin-Medeiros, G Cardon, G Torres-Luque, ...
Int J Sports Med 10, 0033-1337945, 2013
Research534 citationsTopic segmentation with a structured topic model
L Du, W Buntine, M Johnson
Proceedings of the 2013 conference of the North American chapter of the …, 2013
Research150 citationsSolving RCPSP/max by lazy clause generation
A Schutt, T Feydy, PJ Stuckey, MG Wallace
Journal of scheduling 16 (3), 273-289, 2013
Research117 citations- Machine Learning86 citations
Explaining time-table-edge-finding propagation for the cumulative resource constraint
A Schutt, T Feydy, PJ Stuckey
International Conference on Integration of Constraint Programming …, 2013
Machine Learning73 citationsSearch combinators
T Schrijvers, G Tack, P Wuille, H Samulowitz, PJ Stuckey
International Conference on Principles and Practice of Constraint …, 2011
Optimization53 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.