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 8 of 99
2024
Predict. Optimize. Revise. On Forecast and Policy Stability in Energy Management Systems
E Genov, J Ruddick, C Bergmeir, M Vafaeipour, T Coosemans, S Garcia, ...
arXiv e-prints, arXiv: 2407.03368, 2024
Forecasting2 citationsEfficient weighting schemes for auditing instant-runoff voting elections
A Ek, PB Stark, PJ Stuckey, D Vukcevic
International Conference on Financial Cryptography and Data Security, 18-32, 2024
Research2 citationsRLAs for 2-seat STV elections: Revisited
M Blom, PJ Stuckey, V Teague, D Vukcevic
International Conference on Financial Cryptography and Data Security, 3-17, 2024
Research2 citationsContext Neural Networks: A Scalable Multivariate Model for Time Series Forecasting
A Sriramulu, C Bergmeir, S Smyl
arXiv preprint arXiv:2405.07117, 2024
Machine Learning1 citationsFast Gibbs sampling for the local and global trend Bayesian exponential smoothing model
X Long, DF Schmidt, C Bergmeir, S Smyl
arXiv preprint arXiv:2407.00492, 2024
Bayesian Methods1 citationsTimetable nodes for public transport network
A Rohovyi, PJ Stuckey, T Walsh
arXiv preprint arXiv:2410.15715, 2024
Research1 citationsSolving Facility Location Problems via FastMap and Locality Sensitive Hashing
A Li, PJ Stuckey, S Koenig, TKS Kumar
Proceedings of the International Symposium on Combinatorial Search 17, 46-54, 2024
Research1 citationsAvoiding Node Re-Expansions Can Break Symmetry Breaking
M Carlson, D Harabor, PJ Stuckey
Proceedings of the International Symposium on Combinatorial Search 17, 20-27, 2024
Research1 citationsGoanna: Resolving Haskell Type Errors With Minimal Correction Subsets
S Fu, T Dwyer, PJ Stuckey, J Grundy
arXiv preprint arXiv:2405.12697, 2024
Research1 citationsOptimal multi-agent pickup and delivery using branch-and-cut-and-price
E Lam, PJ Stuckey, D Harabor
Monash University, 2024
Multi-Agent Systems1 citationsMtp: A dataset for multi-modal turning points in casual conversations
GB Ho, C Tan, Z Darban, M Salehi, R Haf, W Buntine
Proceedings of the 62nd Annual Meeting of the Association for Computational …, 2024
Research1 citationsGraph Neural Network based forecasting framework for large scale multivariate time series
A SRIRAMULU
Monash University, 0
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.