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 46 of 99
2015
Personalized electronic-mail delivery
J Oliver, R Baxter, W Buntine, S Waterhouse
US Patent App. 13/460,774, 2012
Machine Learning74 citationsBibliographic analysis with the citation network topic model
KW Lim, W Buntine
Asian conference on machine learning, 142-158, 2015
Research69 citationsLazy model expansion: Interleaving grounding with search
B De Cat, M Denecker, M Bruynooghe, P Stuckey
Journal of Artificial Intelligence Research 52, 235-286, 2015
Optimization59 citationsAn Abstract Domain of Uninterpreted Functions
PJ Stuckey
International Conference on Verification, Model Checking, and Abstract …, 2015
Machine Learning48 citationsMiniSearch: a solver-independent meta-search language for MiniZinc
A Rendl, T Guns, PJ Stuckey, G Tack
International Conference on Principles and Practice of Constraint …, 2015
Optimization46 citations- Machine Learning38 citations
Interval analysis and machine arithmetic: Why signedness ignorance is bliss
G Gange, JA Navas, P Schachte, H Søndergaard, PJ Stuckey
ACM Transactions on Programming Languages and Systems (TOPLAS) 37 (1), 1-35, 2015
Research37 citationsHorn clauses as an intermediate representation for program analysis and transformation
G Gange, JA Navas, P Schachte, H Søndergaard, PJ Stuckey
Theory and Practice of Logic Programming 15 (4-5), 526-542, 2015
Research36 citationsEfficient computation of exact IRV margins
M Blom, PJ Stuckey, VJ Teague, R Tidhar
arXiv preprint arXiv:1508.04885, 2015
Research34 citationsLearning value heuristics for constraint programming
G Chu, PJ Stuckey
International Conference on Integration of Constraint Programming …, 2015
Machine Learning32 citationsStable model counting and its application in probabilistic logic programming
R Aziz, G Chu, C Muise, P Stuckey
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
Bayesian Methods32 citationsBest-response planning of thermostatically controlled loads under power constraints
F de Nijs, MTJ Spaan, MM de Weerdt
Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
Machine Learning24 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.