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 25 of 99
2020
Smart predict-and-optimize for hard combinatorial optimization problems
J Mandi, PJ Stuckey, T Guns
Proceedings of the AAAI conference on artificial intelligence 34 (02), 1603-1610, 2020
Optimization240 citationsPackage ‘forecast’
RJ Hyndman, G Athanasopoulos, C Bergmeir, G Caceres, L Chhay, ...
Forecasting218 citationsPublic perceptions and attitudes toward COVID-19 nonpharmaceutical interventions across six countries: a topic modeling analysis of twitter data
C Doogan, W Buntine, H Linger, S Brunt
Journal of medical Internet research 22 (9), e21419, 2020
Research131 citationsNew techniques for pairwise symmetry breaking in multi-agent path finding
J Li, G Gange, D Harabor, PJ Stuckey, H Ma, S Koenig
Proceedings of the International Conference on Automated Planning and …, 2020
Machine Learning102 citationsNeural topic model via optimal transport
H Zhao, D Phung, V Huynh, T Le, W Buntine
arXiv preprint arXiv:2008.13537, 2020
Machine Learning102 citationsMonash university, uea, ucr time series extrinsic regression archive
CW Tan, C Bergmeir, F Petitjean, GI Webb
arXiv preprint arXiv:2006.10996, 2020
Forecasting61 citationsPackage forecast: Forecasting functions for time series and linear models
R Hyndman, G Athanasopoulos, C Bergmeir, G Caceres, L Chhay, ...
Software, R package version 8, 2020
Forecasting48 citationsLoRMIkA: Local rule-based model interpretability with k-optimal associations
D Rajapaksha, C Bergmeir, W Buntine
Information Sciences 540, 221-241, 2020
Research47 citationsModelling diversity of solutions
L Ingmar, MG de la Banda, PJ Stuckey, G Tack
Proceedings of the AAAI Conference on Artificial Intelligence 34 (02), 1528-1535, 2020
Research47 citationsLogistics optimization for a coal supply chain
G Belov, NL Boland, MWP Savelsbergh, PJ Stuckey
Journal of Heuristics 26 (2), 269-300, 2020
Machine Learning47 citationsComputing optimal decision sets with SAT
J Yu, A Ignatiev, PJ Stuckey, P Le Bodic
International Conference on Principles and Practice of Constraint …, 2020
Research42 citationsIterative-deepening conflict-based search
E Boyarski, A Felner, D Harabor, PJ Stuckey, L Cohen, J Li, S Koenig
International Joint Conference on Artificial Intelligence-Pacific Rim …, 2020
Optimization39 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.