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 40 of 99
2017
Context-sensitive dynamic partial order reduction
E Albert, P Arenas, MG De La Banda, M Gómez-Zamalloa, PJ Stuckey
International Conference on Computer Aided Verification, 526-543, 2017
Research54 citationsShort-term scheduling of an open-pit mine with multiple objectives
M Blom, AR Pearce, PJ Stuckey
Engineering Optimization 49 (5), 777-795, 2017
Optimization51 citationsLeveraging node attributes for incomplete relational data
H Zhao, L Du, W Buntine
International conference on machine learning, 4072-4081, 2017
Research47 citationsCombining string abstract domains for JavaScript analysis: An evaluation
R Amadini, A Jordan, G Gange, F Gauthier, P Schachte, H Søndergaard, ...
International Conference on Tools and Algorithms for the Construction and …, 2017
Machine Learning46 citationsEfficient parameter learning of Bayesian network classifiers
NA Zaidi, GI Webb, MJ Carman, F Petitjean, W Buntine, M Hynes, ...
Machine Learning 106 (9), 1289-1329, 2017
Bayesian Methods45 citationsUsing constraint programming for solving RCPSP/max-cal
S Kreter, A Schutt, PJ Stuckey
Constraints 22 (3), 432-462, 2017
Machine Learning44 citationsA word embeddings informed focused topic model
H Zhao, L Du, W Buntine
Asian conference on machine learning, 423-438, 2017
Research44 citationsForecasting across time series databases using long short-term memory networks on groups of similar series
K Bandara, C Bergmeir, S Smyl
arXiv preprint arXiv:1710.03222 8, 805-815, 2017
Forecasting42 citationsforecast: Forecasting functions for time series and linear models, 2018, r package version 8.4
RJ Hyndman, G Athanasopoulos, C Bergmeir, G Caceres, L Chhay, ...
URL http://github. com/robjhyndman/forecast, 2017
Forecasting42 citationsBounding the Probability of Resource Constraint Violations in Multi-Agent MDPs
F de Nijs, E Walraven, MM de Weerdt, MTJ Spaan
Proceedings of the 31st AAAI Conference on Artificial Intelligence, 3562-3568, 2017
Machine Learning30 citationsStatistical inference of protein structural alignments using information and compression
JH Collier, L Allison, AM Lesk, PJ Stuckey, M Garcia de la Banda, ...
Bioinformatics 33 (7), 1005-1013, 2017
Bayesian Methods30 citationsA novel approach to string constraint solving
R Amadini, G Gange, PJ Stuckey, G Tack
International Conference on Principles and Practice of Constraint …, 2017
Machine Learning29 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.