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 6 of 99
2025
ACM TOPML: Inaugural Issue Editorial
T Papamarkou, F Liu, W Buntine
ACM Transactions on Probabilistic Machine Learning 1 (1), 1-2, 2025
Research
2024
Pive: Prompting with iterative verification improving graph-based generative capability of llms
J Han, N Collier, W Buntine, E Shareghi
Findings of the Association for Computational Linguistics: ACL 2024, 6702-6718, 2024
Research67 citationsTraffic flow optimisation for lifelong multi-agent path finding
Z Chen, D Harabor, J Li, PJ Stuckey
Proceedings of the AAAI Conference on Artificial Intelligence 38 (18), 20674 …, 2024
Multi-Agent Systems38 citationsMachine learning applications in hierarchical time series forecasting: Investigating the impact of promotions
M Abolghasemi, G Tarr, C Bergmeir
International Journal of Forecasting 40 (2), 597-615, 2024
Machine Learning34 citationsTowards uncertainty-aware language agent
J Han, W Buntine, E Shareghi
arXiv preprint arXiv:2401.14016, 2024
Machine Learning28 citationsDelivering inflated explanations
Y Izza, A Ignatiev, PJ Stuckey, J Marques-Silva
Proceedings of the AAAI Conference on Artificial Intelligence 38 (11), 12744 …, 2024
Research24 citationsPlanning and execution in multi-agent path finding: Models and algorithms
Y Zhang, Z Chen, D Harabor, P Le Bodic, PJ Stuckey
Proceedings of the International Conference on Automated Planning and …, 2024
Optimization16 citationsSuperstack: Superoptimization of stack-bytecode via greedy, constraint-based, and sat techniques
E Albert, M Garcia de la Banda, A Hernández-Cerezo, A Ignatiev, A Rubio, ...
Proceedings of the ACM on Programming Languages 8 (PLDI), 1437-1462, 2024
Machine Learning15 citationsScalable Transformer for High Dimensional Multivariate Time Series Forecasting
X Zhou, W Wang, W Buntine, S Qu, A Sriramulu, W Tan, C Bergmeir
Proceedings of the 33rd ACM International Conference on Information and …, 2024
Forecasting14 citationsDiscrete diffusion language model for long text summarization
DH Dat, DD Anh, AT Luu, W Buntine
arXiv e-prints, arXiv: 2407.10998, 2024
Research9 citationsHarnessing the power of beta scoring in deep active learning for multi-label text classification
W Tan, ND Nguyen, L Du, W Buntine
Proceedings of the AAAI Conference on Artificial Intelligence 38 (14), 15240 …, 2024
Research8 citationsLLMs and Foundational Models: Not (Yet) as Good as Hoped
C Bergmeir
Foresight: The International Journal of Applied Forecasting 73, 33-38, 2024
Research7 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.