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 34 of 99
2019
Information-theoretic inference of an optimal dictionary of protein supersecondary structures
AS Konagurthu, R Subramanian, L Allison, D Abramson, MG de la Banda, ...
Protein Supersecondary Structures: Methods and Protocols, 123-131, 2019
Bayesian Methods3 citationsCertifying optimality in constraint programming
G Gange, P Stuckey
Presentation at KTH Royal Institute of Technology. Slides available at https …, 2019
Machine Learning3 citationsOptimal bounds for floating-point addition in constant time
M Andrlon, P Schachte, H Søndergaard, PJ Stuckey
2019 IEEE 26th Symposium on Computer Arithmetic (ARITH), 159-166, 2019
Research2 citationsTime table edge finding with energy variables
M Yang, A Schutt, PJ Stuckey
International Conference on Integration of Constraint Programming …, 2019
Research2 citationsElection manipulation 100
M Blom, PJ Stuckey, VJ Teague
International Conference on Financial Cryptography and Data Security, 211-225, 2019
Research2 citationsA universal representation framework for fuzzy rule-based systems based on PMML
LS Riza, C Bergmeir, F Herrera, JM Benitez
Working paper, 2019
Research1 citations- Research1 citations
Package ‘Rmalschains’
C Bergmeir, JM Benítez, D Molina, R Davies, D Eddelbuettel, N Hansen
Machine Learning2018 Index IEEE Transactions on Cloud Computing Vol. 6
CT Abdallah, K Ahmed, M Ali, A Almutairi, H Alshammari, ...
IEEE Transactions on Cloud Computing 7 (1), 1, 2019
ResearchElection Manipulation with Partial
M Blom, PJ Stuckey, VJ Teague¹
Electronic Voting: 4th International Joint Conference, E-Vote-ID 2019 …, 2019
ResearchPeak-Hour Rail Demand Shifting with Discrete Optimisation
JM Betts, DL Dowe, D Guimarans, DD Harabor, H Kumarage, PJ Stuckey, ...
International Conference on Principles and Practice of Constraint …, 2019
Machine LearningLoandra: Core-Boosted Linear Search for incomplete MaxSAT
J Berg, P Stuckey, EE Demirović
Optimization
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.