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 27 of 99
2020
Abstract interpretation, symbolic execution and constraints
R Amadini, G Gange, P Schachte, H Søndergaard, PJ Stuckey
Recent Developments in the Design and Implementation of Programming …, 2020
Machine Learning16 citationsDashed strings for string constraint solving
R Amadini, G Gange, PJ Stuckey
Artificial Intelligence 289, 103368, 2020
Machine Learning15 citationsRobust resource planning for aircraft ground operations
YS Gök, D Guimarans, PJ Stuckey, M Tomasella, C Ozturk
International Conference on Integration of Constraint Programming …, 2020
Machine Learning15 citationsTheoretical and experimental results for planning with learned binarized neural network transition models
B Say, J Devriendt, J Nordström, PJ Stuckey
International Conference on Principles and Practice of Constraint …, 2020
Machine Learning14 citationsReinforcement learning for strategic recommendations
G Theocharous, Y Chandak, PS Thomas, F de Nijs
arXiv preprint arXiv:2009.07346, 2020
Machine Learning13 citationsA comparison of characteristics and outcomes of patients admitted to the ICU with asthma in Australia and New Zealand and United states
H Abdelkarim, M Durie, R Bellomo, C Bergmeir, O Badawi, K El-Khawas, ...
Journal of Asthma 57 (4), 398-404, 2020
Research12 citations- Research12 citations
Collective wisdom: Improving low-resource neural machine translation using adaptive knowledge distillation
F Saleh, W Buntine, G Haffari
arXiv preprint arXiv:2010.05445, 2020
Machine Learning12 citationsDid that lost ballot box cost me a seat? Computing manipulations of STV elections
M Blom, A Conway, PJ Stuckey, VJ Teague
Proceedings of the AAAI Conference on Artificial Intelligence 34 (08), 13235 …, 2020
Research11 citationsYou can do RLAs for IRV
M Blom, A Conway, D King, L Sandrolini, PB Stark, PJ Stuckey, V Teague
arXiv preprint arXiv:2004.00235, 2020
Research11 citationsRobust attribute and structure preserving graph embedding
B Hettige, W Wang, YF Li, W Buntine
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 593-606, 2020
Research11 citationsA strong baseline for weekly time series forecasting
R Godahewa, C Bergmeir, GI Webb, P Montero-Manso
arXiv preprint arXiv:2010.08158, 2020
Forecasting10 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.