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RabbitHawk

The team

A team built for hard decision problems

RabbitHawk brings together highly cited researchers in probabilistic forecasting, constraint optimization and machine learning with the engineers and enterprise specialists who turn those methods into governed software.

Explore the researchWork with us

Scientific leadership

The researchers building the product

1,181 indexed research outputs, 53,485 citations and highly cited papers.

Dr Christoph Bergmeir
Dr Christoph BergmeirForecasting & AI systemsRabbitHawk focus: Adaptive forecasting and context-conditioned prediction13,200+ citations across forecasting & ML research
Dr Peter Stuckey
Dr Peter StuckeyConstraint programming & optimizationRabbitHawk focus: Integrated optimization under operational constraints23,000+ citations, h-index 71
Dr Wray Buntine
Dr Wray BuntineMachine learning & generative AIRabbitHawk focus: Probabilistic machine learning and Context IntelligenceTop 0.75% most-cited AI researchers globally

Team capability map

How each discipline shapes RabbitHawk

  • Forecasting science

    Probabilistic, hierarchical, reconciled forecasts

  • Optimization & operations research

    Constraint-aware recommendations

  • Applied & agentic AI

    Adaptive elicitation, semantic routing and governed context workflows

  • Product engineering

    The planner workspace and integrations

  • Enterprise delivery

    Governed deployment and implementation

  • Alignment science

    Goals & Guardrails within Forecasting & Optimization

Team members

Scientific leadership

The researchers actively shaping the forecasting, optimization and AI behind RabbitHawk products.

Dr Christoph Bergmeir

Dr Christoph Bergmeir

Forecasting & AI systems

RabbitHawk focus: Adaptive forecasting and context-conditioned prediction

Highly cited forecasting researcher and co-author of widely used open-source forecasting tools.

A Senior Research Fellow at Monash University and Senior Fellow at the University of Granada, Christoph works across adaptive forecasting, explainable AI and coherent hierarchical prediction. He co-authored the Forecast package, NeuralProphet, Kats and Forecastingdata.org, and has collaborated with Meta, Walmart, Tokopedia, Honeywell, Worley and Yarra Valley Water.

  • 13,200+ citations across forecasting & ML research
  • Clarivate Highly Cited Papers (top 1% in forecasting)
  • Maria Zambrano Senior Fellow, University of Granada
  • Australian Research Council DECRA recipient
  • Co-author of NeuralProphet, Kats & the Forecast package
WebsiteScholar
Dr Peter Stuckey

Dr Peter Stuckey

Constraint programming & optimization

RabbitHawk focus: Integrated optimization under operational constraints

Pioneer in constraint programming and solver-independent optimization modeling.

Peter is a Professor at Monash University and a project leader in the Data61 CSIRO laboratory. His work on solver-independent modeling and high-performance optimization supports scheduling, routing and resource-allocation systems, including work with Oracle and Rio Tinto.

  • 23,000+ citations, h-index 71
  • Fellow of the AAAI (2019)
  • ACM Distinguished Scientist
  • Google Australia Eureka Prize for Innovation in Computer Science
Scholar
Dr Wray Buntine

Dr Wray Buntine

Machine learning & generative AI

RabbitHawk focus: Probabilistic machine learning and Context Intelligence

Highly cited researcher in probabilistic machine learning, text analysis and predictive modeling.

Wray is known for foundational work in statistical text analysis, predictive modeling and probabilistic machine learning. He directs the Computer Science Program at VinUniversity, co-edits ACM Transactions on Probabilistic Machine Learning and has worked with NASA Ames, UC Berkeley and Google.

  • Top 0.75% most-cited AI researchers globally
  • 13,000+ citations and 200+ publications
  • AI Best Paper Award, ECAI
  • General Chair, Asian Conference on Machine Learning 2024
  • Co-editor, ACM Transactions on Probabilistic ML
Scholar

Applied delivery

Translating the science into alignment, product and customer outcomes.

Dr Abishek Sriramulu

Dr Abishek Sriramulu

Graph AI & adaptive modeling

RabbitHawk focus: Context Intelligence, graph AI and adaptive forecasting

A machine-learning scientist who turns chaos into pattern through multimodal and graph AI.

Abishek connects structured and unstructured context through multimodal and graph AI. He holds a PhD in machine learning and forecasting from Monash University, co-founded the graph-AI pricing engine Tymestack and has collaborated with retailers including Woolworths Group, Tokopedia and Catch of the Day.

  • Pioneer of Adaptive Dependency Learning GNNs
  • PhD in Machine Learning, Monash University
  • Former co-founder & CTO, Tymestack (graph-AI pricing engine)
  • ARC and Meta research-grant recipient
ScholarLinkedIn
Dr Frits de Nijs

Dr Frits de Nijs

Optimization & agentic learning

RabbitHawk focus: Sequential decision systems and adaptive optimization

An optimization researcher working where reinforcement learning meets real-world constraints.

Frits works where optimization, reinforcement learning and operational constraints meet. A Research Fellow at Monash University and formerly with CSIRO, he develops sequential decision systems that plan, adapt and improve under uncertainty.

  • Research Fellow, Monash University
  • Australian Research Council DECRA grant recipient
  • PhD, TU Delft (multi-agent decision making)
  • 3rd globally, NeurIPS 2021 ML4CO challenge
Scholar
Paul Shale

Paul Shale

Alignment strategy & product design

RabbitHawk focus: Goals, guardrails and usable decision workflows

Turns advanced analytics into tools that are genuinely easy to use.

Paul turns advanced science into usable systems and aligned decisions. He has led large multidisciplinary teams across the USA, Australia and New Zealand in retail, construction, infrastructure, consulting, government and tourism, and shapes RabbitHawk goals, guardrails and customer workflows.

  • B.Com / LLB (Hons), University of Auckland
  • Disruptive Innovation Program, Harvard Business School
  • Former CEO, FCB NZ & Roadtrippers AU; former CCO, Nextspace
  • Led teams of 250+ across the USA, Australia & New Zealand
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Research-backed

Decades of published science, applied to your decisions

Our team’s work spans probabilistic forecasting, hierarchical reconciliation and large-scale optimization, recognized at the field’s leading venues. Explore the research foundations behind the products.

Browse the research database
indexed research outputs
1,181indexed research outputs
citations
53,485citations
highly cited papers
Top 1%highly cited papers

Bring us the decision problem others have struggled to model

Connect with the researchers and builders who turn forecasting, optimization and contextual evidence into governed software.

Talk to the team