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 1 of 99
2026
Ensembled Bayesian tabular data generator: Y. Zhang et al.
Y Zhang, N Zaidi, J Zhou, G Li, W Buntine
Knowledge and Information Systems 68 (1), 36, 2026
Bayesian MethodsImproving Symbolic Translation of Language Models for Logical Reasoning
RK Thatikonda, J Han, W Buntine, E Shareghi
arXiv e-prints, arXiv: 2601.09446, 2026
Research
2025
MSTL: A seasonal-trend decomposition algorithm for time series with multiple seasonal patterns
K Bandara, RJ Hyndman, C Bergmeir
International Journal of Operational Research 52 (1), 79-98, 2025
Forecasting203 citationsTime series adversarial attacks: an investigation of smooth perturbations and defense approaches
G Pialla, H Ismail Fawaz, M Devanne, J Weber, L Idoumghar, PA Muller, ...
International Journal of Data Science and Analytics 19 (1), 129-139, 2025
Forecasting19 citationsNeusis: A compositional neuro-symbolic framework for autonomous perception, reasoning, and planning in complex uav search missions
Z Cai, CR Cardenas, K Leo, C Zhang, K Backman, H Li, B Li, ...
IEEE Robotics and Automation Letters, 2025
Optimization13 citationsLocal and global trend Bayesian exponential smoothing models
S Smyl, C Bergmeir, A Dokumentov, X Long, E Wibowo, D Schmidt
International Journal of Forecasting 41 (1), 111-127, 2025
Bayesian Methods12 citationsOnline guidance graph optimization for lifelong multi-agent path finding
H Zang, Y Zhang, H Jiang, Z Chen, D Harabor, PJ Stuckey, J Li
Proceedings of the AAAI Conference on Artificial Intelligence 39 (14), 14726 …, 2025
Optimization12 citationsNaver: A neuro-symbolic compositional automaton for visual grounding with explicit logic reasoning
Z Cai, F Ke, S Jahangard, MG de la Banda, R Haffari, PJ Stuckey, ...
arXiv preprint arXiv:2502.00372, 2025
Research10 citationsLlm reading tea leaves: Automatically evaluating topic models with large language models
X Yang, H Zhao, D Phung, W Buntine, L Du
Transactions of the Association for Computational Linguistics 13, 357-375, 2025
Research9 citationsPredict+ Optimize Problem in Renewable Energy Scheduling.
C Bergmeir, F De Nijs, E Genov, A Sriramulu, M Abolghasemi, R Bean, ...
IEEE Access, 2025
Optimization8 citationsHier-slam++: Neuro-symbolic semantic slam with a hierarchically categorical gaussian splatting
B Li, VC Hao, PJ Stuckey, I Reid, H Rezatofighi
arXiv preprint arXiv:2502.14931, 2025
Research8 citationsMoTime: A Dataset Suite for Multimodal Time Series Forecasting
X Zhou, W Wang, FJ Baldán, W Buntine, C Bergmeir
arXiv preprint arXiv:2505.15072, 2025
Forecasting6 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.