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 11 of 99
2023
Model-Free Approach to Fair Solar PV Curtailment Using Reinforcement Learning
Z Wei, F De Nijs, J Li, H Wang
Proceedings of the 14th ACM International Conference on Future Energy …, 2023
Machine Learning16 citationsSETAR-Tree: a novel and accurate tree algorithm for global time series forecasting
R Godahewa, GI Webb, D Schmidt, C Bergmeir
Machine Learning 112 (7), 2555-2591, 2023
Forecasting15 citationsEnhancing educational dialogue act classification with discourse context and sample informativeness
J Lin, W Tan, L Du, W Buntine, D Lang, D Gašević, G Chen
IEEE Transactions on Learning Technologies 17, 258-269, 2023
Research15 citationsTree-based survival analysis improves mortality prediction in cardiac surgery
JC Penny-Dimri, C Bergmeir, CM Reid, J Williams-Spence, LA Perry, ...
Frontiers in Cardiovascular Medicine 10, 1211600, 2023
Forecasting13 citationsAn accurate and fully-automated ensemble model for weekly time series forecasting
R Godahewa, C Bergmeir, GI Webb, P Montero-Manso
International Journal of Forecasting 39 (2), 641-658, 2023
Forecasting13 citationsBayesian estimate of mean proper scores for diversity-enhanced active learning
W Tan, L Du, W Buntine
IEEE transactions on pattern analysis and machine intelligence 46 (5), 3463-3479, 2023
Bayesian Methods13 citationsBeyond pairwise reasoning in multi-agent path finding
B Shen, Z Chen, J Li, MA Cheema, DD Harabor, PJ Stuckey
Proceedings of the International Conference on Automated Planning and …, 2023
Machine Learning12 citationsEfficient multi agent path finding with turn actions
Y Zhang, D Harabor, P Le Bodic, PJ Stuckey
Proceedings of the International Symposium on Combinatorial Search 16 (1 …, 2023
Multi-Agent Systems11 citationsExact anytime multi-agent path finding using branch-and-cut-and-price and large neighborhood search
E Lam, DD Harabor, PJ Stuckey, J Li
Proceedings of the International Conference on Automated Planning and …, 2023
Optimization11 citationsOpen-set graph anomaly detection via normal structure regularisation
Q Wang, G Pang, M Salehi, X Xia, C Leckie
arXiv preprint arXiv:2311.06835, 2023
Research9 citationsOptimal dynamic partial order reduction with context-sensitive independence and observers
E Albert, MG de la Banda, M Gómez-Zamalloa, M Isabel, P Stuckey
Journal of Systems and Software 202, 111730, 2023
Research8 citationsOptimal pathfinding on weighted grid maps
M Carlson, SK Moghadam, DD Harabor, PJ Stuckey, M Ebrahimi
Proceedings of the AAAI conference on artificial intelligence 37 (10), 12373 …, 2023
Research8 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.