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 5 of 99
2025
Efficient Lower Bounding of Single Transferable Vote Election Margins
M Blom, A Ek, PJ Stuckey, V Teague, D Vukcevic
arXiv preprint arXiv:2501.14847, 2025
ResearchThree-or-More Seat Risk-Limiting Audits for Single Transferable Vote Elections
M Blom, A Ek, PJ Stuckey, VJ Teague, D Vukcevic
Monash Econometrics and Business Statistics Working Papers, 2025
ResearchA Consecutive Flight Leg Model for the Aircraft Maintenance Routing Problem
I Gjergji, L Kletzander, H Bierlee, N Musliu, PJ Stuckey
Machine LearningParallelising Lazy Clause Generation with Trail Sharing
TO Davies, F Didier, L Perron, PJ Stuckey
International Conference on the Integration of Constraint Programming …, 2025
Machine LearningRevisiting Pseudo-Boolean Encodings from an Integer Perspective
H Bierlee, JJ Dekker, PJ Stuckey
International Conference on the Integration of Constraint Programming …, 2025
ResearchUnit Types for MiniZinc
JJ Dekker, J Nguyen, PJ Stuckey, G Tack
31st International Conference on Principles and Practice of Constraint …, 2025
ResearchAssessing the Sensitivity and Alignment of FOL Closeness Metrics
RK Thatikonda, W Buntine, E Shareghi
Findings of the Association for Computational Linguistics: EMNLP 2025, 16775 …, 2025
ResearchLogical Reasoning with Outcome Reward Models for Test-Time Scaling
RK Thatikonda, W Buntine, E Shareghi
Proceedings of the 2025 Conference on Empirical Methods in Natural Language …, 2025
ResearchLeveraging Deep AUC Maximisation for Enhanced Active Learning in Named Entity Recognition
W Tan, D Nguyen, C Li, W Buntine, H Zhao, L Du
International Conference on Advanced Data Mining and Applications, 287-302, 2025
ResearchMultilingual LLM Prompting Strategies for Medical English-Vietnamese Machine Translation
N Vo, NUP Le, DD Le, M Piccardi, W Buntine
arXiv preprint arXiv:2509.15640, 2025
ResearchALScope: A Unified Toolkit for Deep Active Learning
C Wu, Y Qi, X Yang, J Lu, G Liu, W Buntine, L Du
arXiv preprint arXiv:2508.04937, 2025
ResearchUncertainty-Based Methods for Automated Process Reward Data Construction and Output Aggregation in Mathematical Reasoning
J Han, W Buntine, E Shareghi
arXiv preprint arXiv:2508.01773, 2025
Machine Learning
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.