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 89 of 99
1997
A Generic Object-Oriented Incremental Analyser for Constraint Logic Programs
AD Kelly, K Marriott, H Søndergaard, PJ Stuckey
AUSTRALIAN COMPUTER SCIENCE COMMUNICATIONS 19, 92-101, 1997
Machine Learning11 citations- Machine Learning7 citations
Adaptive methods for netlist partitioning
L Su
1997 Proceedings of IEEE International Conference on Computer Aided Design …, 1997
Research7 citationsFinding Facets of General Integer Knapsacks
B Davey, N Boland, P Stuckey
Technical report, University of Melbourne, Mel bourne, Australia, 1997
Research1 citationsAn efficient evaluation technique for non-stratified programs by transformation to explicitly locally stratified programs
DB Kemp, K Ramamohanarao, PJ Stuckey
Journal of Systems Integration 7 (3), 191-230, 1997
Research1 citations- Bayesian Methods1 citations
Learning as applied to simulated annealing
L Su, W Buntine, R Newton
Master’s thesis, University of California, Berkeley, CA, 1997
Research1 citationsOptimization of logic programs with dynamic scheduling
AG Puebla Sánchez, M García de la Banda, K Marriott, PJ Stuckey
MIT Press, 1997
OptimizationMethodologies and Tools for Complex Software Systems in Electronic Design
W Buntine, A Mayer, L Su
Research
1996
Cost-based optimization for magic: Algebra and implementation
P Seshadri, JM Hellerstein, H Pirahesh, TYC Leung, R Ramakrishnan, ...
Proceedings of the 1996 ACM SIGMOD international conference on Management of …, 1996
Optimization147 citationsGraphical Models for Discivering Knowledge.
WL Buntine
Advances in knowledge discovery and data mining, 59-82, 1996
Bayesian Methods135 citations- Research36 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.