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 21 of 99
2021
Learning optimal decision sets and lists with sat
J Yu, A Ignatiev, PJ Stuckey, P Le Bodic
Journal of Artificial Intelligence Research 72, 1251-1279, 2021
Research34 citationsSymmetry breaking for k-robust multi-agent path finding
Z Chen, DD Harabor, J Li, PJ Stuckey
Proceedings of the AAAI Conference on Artificial Intelligence 35 (14), 12267 …, 2021
Multi-Agent Systems30 citationsReasoning-based learning of interpretable ML models
A Ignatiev, J Marques-Silva, N Narodytska, PJ Stuckey
International Joint Conference on Artificial Intelligence 2021, 4458-4465, 2021
Research30 citationsA scalable two stage approach to computing optimal decision sets
A Ignatiev, E Lam, PJ Stuckey, J Marques-Silva
Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 3806-3814, 2021
Research26 citationsNeural attention-aware hierarchical topic model
Y Jin, H Zhao, M Liu, L Du, W Buntine
arXiv preprint arXiv:2110.07161, 2021
Machine Learning24 citationsMultirocket: Effective summary statistics for convolutional outputs in time series classification
CW Tan, A Dempster, C Bergmeir, GI Webb
arXiv preprint arXiv:2102.00457, 2021
Forecasting18 citationsA fresh look at zones and octagons
G Gange, Z Ma, JA Navas, P Schachte, H Søndergaard, PJ Stuckey
ACM Transactions on Programming Languages and Systems (TOPLAS) 43 (3), 1-51, 2021
Research16 citationsF-aware conflict prioritization & improved heuristics for conflict-based search
E Boyarski, A Felner, P Le Bodic, DD Harabor, PJ Stuckey, S Koenig
Proceedings of the AAAI Conference on Artificial Intelligence 35 (14), 12241 …, 2021
Optimization16 citationsAssertion-based approaches to auditing complex elections, with application to party-list proportional elections
M Blom, J Budurushi, RL Rivest, PB Stark, PJ Stuckey, V Teague, ...
International Joint Conference on Electronic Voting, 47-62, 2021
Research15 citationsECBS with flex distribution for bounded-suboptimal multi-agent path finding
SH Chan, J Li, G Gange, D Harabor, PJ Stuckey, S Koenig
Proceedings of the International Symposium on Combinatorial Search 12 (1 …, 2021
Multi-Agent Systems15 citationsUniversal architectural concepts underlying protein folding patterns
AS Konagurthu, R Subramanian, L Allison, D Abramson, PJ Stuckey, ...
Frontiers in Molecular Biosciences 7, 612920, 2021
Research13 citationsContracting and compressing shortest path databases
B Shen, MA Cheema, DD Harabor, PJ Stuckey
Proceedings of the International Conference on Automated Planning and …, 2021
Research12 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.