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 39 of 99
2018
Solution-Based Phase Saving and MaxSAT for Employee Scheduling: A Computational Study
F Winter, N Musliu, E Demirovic, PJ Stuckey
12th International Conference on the Practice and Theory of Automated …, 2018
Optimization2 citationsData Instance generator and optimization models for evacuation planning in the event of wildfire
C Artigues, E Hébrard, Y Pencolé, A Schutt, PJ Stuckey
GEOSAFE Workshop on Robust Solutions for Fire Fighting (RSFF 2018) 2146, 75-86, 2018
Optimization1 citationsComparison of characteristics and outcomes of patients admitted to the ICU with asthma in Australia, New Zealand and United States
H Abdelkarim, M Durie, K El-Khawas, R Bellomo, C Bergmeir, O Badawi
Australian Critical Care 31 (2), 114, 2018
ResearchDeep learning based image analysis of fungal pneumonia in chest computed tomography in haematology patients
MR Ananda Rajah, T Tang, H Josh, S Ellis, A Kam, DK Varma, G Haffari, ...
Deakin University, 2018
Machine LearningPrecondition Inference via Partitioning of Initial States
B Kafle, G Gange, P Schachte, H Sondergaard, PJ Stuckey
arXiv preprint arXiv:1811.06771, 2018
Bayesian MethodsPre-proceedings of the 28th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2018)
F Mesnard, PJ Stuckey
arXiv preprint arXiv:1808.03326, 2018
ResearchGeoSafe–Evacuation planning problems
C Artigues, E Hébrard, Y Pencolé, A Schutt, PJ Stuckey
OptimizationSchool of Computing and Information Systems, University of Melbourne, Melbourne, Australia {edemirovic, pstuckey}@ unimelb. edu. au
E Demirović, PJ Stuckey
Integration of Constraint Programming, Artificial Intelligence, and …, 2018
Research- Bayesian Methods
A Knowledge Mining and Ontology Constructing Technology Oriented on Massive Social Security Policy Documents
G Liu, L Sun, W Fu
International Conference on Green and Human Information Technology, 79-85, 2018
ResearchSupplementary material for" Inter and Intra topic structure learning with word embeddings"
H Zhao, L Du, W Buntine, M Zhou
Research
2017
MetaLDA: A topic model that efficiently incorporates meta information
H Zhao, L Du, W Buntine, G Liu
2017 IEEE international conference on data mining (ICDM), 635-644, 2017
Research64 citations
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