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 81 of 99
2002
A hybrid algorithm for the examination timetabling problem
LTG Merlot, N Boland, BD Hughes, PJ Stuckey
International Conference on the Practice and Theory of Automated Timetabling …, 2002
Research300 citationsVariational extensions to EM and multinomial PCA
W Buntine
European Conference on Machine Learning, 23-34, 2002
Research248 citationsTo the gates of HAL: a HAL tutorial
M García de la Banda, B Demoen, K Marriott, PJ Stuckey
International Symposium on Functional and Logic Programming, 47-66, 2002
Research36 citationsConstraint-based mode analysis of Mercury
D Overton, Z Somogyi, PJ Stuckey
Proceedings of the 4th ACM SIGPLAN international conference on Principles …, 2002
Machine Learning34 citationsEfficient intelligent backtracking using linear programming
B Davey, N Boland, PJ Stuckey
INFORMS Journal on Computing 14 (4), 373-386, 2002
Research31 citationsImproving sat using 2sat
L Zheng, PJ Stuckey
Proceedings of the twenty-fifth Australasian conference on Computer science …, 2002
Research21 citationsCompacting discriminator information for spatial trees
I Sitzmann, PJ Stuckey
Proceedings of the 13th Australasian database conference-Volume 5, 167-176, 2002
Research18 citationsException analysis for non-strict languages
K Glynn, PJ Stuckey, M Sulzmann, H Søndergaard
Proceedings of the seventh ACM SIGPLAN international conference on …, 2002
Research16 citationsPrecise pair-sharing analysis of logic programs
V Lagoon, PJ Stuckey
Proceedings of the 4th ACM SIGPLAN international conference on Principles …, 2002
Machine Learning15 citationsExtending GENET with lazy arc consistency
PJ Stuckey, V Tam
IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2002
Research15 citationsReducing search space in local search for constraint satisfaction
H Fang, Y Kilani, JHM Lee, PJ Stuckey
AAAI/IAAI, 28-33, 2002
Machine Learning14 citationsBuilding and maintaining web taxonomies
SP Wray Buntine, H Tirri
46 h Fg E 9 i VlE 7@ GPQ qhrhrRq@ rh, 2002
Machine Learning7 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.