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 37 of 99
2018
Lagrangian constrained community detection
M Ganji, J Bailey, P Stuckey
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
Machine Learning15 citationsReference abstract domains and applications to string analysis
R Amadini, G Gange, F Gauthier, A Jordan, P Schachte, H Søndergaard, ...
Fundamenta Informaticae 158 (4), 297-326, 2018
Machine Learning15 citationsForward search in contraction hierarchies
D Harabor, P Stuckey
Proceedings of the International Symposium on Combinatorial Search 9 (1), 55-62, 2018
Optimization15 citationsSolution dominance over constraint satisfaction problems
T Guns, PJ Stuckey, G Tack
arXiv preprint arXiv:1812.09207, 2018
Machine Learning14 citationsBayesian multi-label learning with sparse features and labels, and label co-occurrences
H Zhao, P Rai, L Du, W Buntine
International Conference on Artificial Intelligence and Statistics, 1943-1951, 2018
Bayesian Methods14 citationsCapacity-aware Sequential Recommendations
F de Nijs, G Theocharous, N Vlassis, MM de Weerdt, MTJ Spaan
Proceedings of the 17th International Conference on Autonomous Agents and …, 2018
Research12 citationsDeclarative local-search neighbourhoods in MiniZinc
G Björdal, P Flener, J Pearson, PJ Stuckey, G Tack
2018 IEEE 30th International Conference on Tools with Artificial …, 2018
Optimization12 citationsBallot-polling risk limiting audits for IRV elections
M Blom, PJ Stuckey, VJ Teague
International Joint Conference on Electronic Voting, 17-34, 2018
Research12 citationsPropagating lex, find and replace with Dashed Strings
R Amadini, G Gange, PJ Stuckey
International Conference on the Integration of Constraint Programming …, 2018
Research12 citationsPropagating regular membership with dashed strings
R Amadini, G Gange, PJ Stuckey
International Conference on Principles and Practice of Constraint …, 2018
Research10 citationsPreallocation and planning under stochastic resource constraints
F de Nijs, MTJ Spaan, MM de Weerdt
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Machine Learning9 citationsForecast: Forecasting functions for time series and linear models. R package
R Hyndman, G Athanasopoulos, C Bergmeir, G Caceres, L Chhay, ...
Forecasting7 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.