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 49 of 99
2015
A fusion of predicate logic and document semantic distance method orientated on data and context mapping
G Liu, W Buntine, S Sun, X Yang
2015 4th International Conference on Computer Science and Network Technology …, 2015
ResearchSpecial session on trends & controversies in data science (TCDS)
F Forbes, W Buntine
2015 IEEE International Conference on Data Science and Advanced Analytics …, 2015
ResearchIntroduction: special issue of selected papers of ACML 2013
CS Ong, W Buntine, TB Ho, M Sugiyama, GI Webb
Machine Learning 99 (2), 165-167, 2015
Research
2014
Implementing algorithms of rough set theory and fuzzy rough set theory in the R package “RoughSets”
LS Riza, A Janusz, C Bergmeir, C Cornelis, F Herrera, D Śle, JM Benítez
Research222 citationsThe minizinc challenge 2008–2013
PJ Stuckey, T Feydy, A Schutt, G Tack, J Fischer
Research172 citationsOn the usefulness of cross-validation for directional forecast evaluation
C Bergmeir, M Costantini, JM Benítez
Computational Statistics & Data Analysis 76, 132-143, 2014
Forecasting119 citationsTwitter opinion topic model: Extracting product opinions from tweets by leveraging hashtags and sentiment lexicon
KW Lim, W Buntine
Proceedings of the 23rd ACM international conference on conference on …, 2014
Research117 citationsExperiments with non-parametric topic models
WL Buntine, S Mishra
Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014
Research79 citationsEncoding linear constraints into SAT
I Abío, PJ Stuckey
International Conference on Principles and Practice of Constraint …, 2014
Machine Learning49 citationsDifferential topic models
C Chen, W Buntine, N Ding, L Xie, L Du
IEEE transactions on pattern analysis and machine intelligence 37 (2), 230-242, 2014
Research38 citations- Machine Learning37 citations
Synthesizing optimal switching lattices
G Gange, H Søndergaard, PJ Stuckey
ACM Transactions on Design Automation of Electronic Systems (TODAES) 20 (1 …, 2014
Research31 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.