Jenny Alderden, PhD, APRN, FAAN

Associate Professor, Boise State University

Critical carePredictionImplementation

Nurse scientist and Fellow of the American Academy of Nursing, nationally recognized for applying machine learning to pressure injury prevention in critical care. We are collaborating with Dr. Alderden to develop predictive models for pressure injury risk stratification using real-world clinical data.

Igor Shuryak, MD, PhD

Associate Professor of Radiation Oncology, Columbia University Irving Medical Center

Radiation oncologyMechanistic modelsCausal ML

Radiation oncology researcher at Columbia Center for Radiological Research whose work connects radiation biology, oncology, mathematical modeling, machine learning, and causal inference, with more than 140 peer-reviewed publications. His collaboration helps ground the time-to-event and run-at-home analytics workflow in a real scientific use case.

Justin Belair

Causal Inference Expert, HEC Montreal & ETS Montreal

Causal inferenceTeachingStatistics

International expert in causal inference and data science based in Montreal, Canada. Justin focuses on moving beyond correlation to identify true cause-and-effect relationships and supports the teaching backbone behind the Navigator.

Kathryn Morrison, PhD, PStat

President, Precision Analytics

BiostatisticsClinical researchR community

Accredited statistician and founder of Precision Analytics, a Montreal-based health and life-science analytics firm. Kathryn has more than twenty peer-reviewed publications, consults across areas from genomics to clinical research, leads statistical technology development, and co-organizes Montreal R-Ladies.

MaryLena Bleile, PhD

Causal RLDynamic regimesIdentification

Researcher specializing in causal inference and reinforcement learning. Her work on bridging these fields inspired our reformulation of the Causal Navigator around identification, decisions, and dynamic strategies.

Yunzhe (Jeffrey) Zhou, PhD

Reinforcement learningDTRsCausal methods

Researcher in reinforcement learning and causal inference, with a focus on novel methods for identifying optimal treatment strategies in dynamic treatment regimes.

Carlos Garcia Meixide, PhD

Targeted learningImplied interventionsTools

Causal inference researcher and creator of Variacle, an interactive tool for exploring causal methods. His work focuses on causal inference with implied interventions and targeted learning approaches.

Brian Knaeble, PhD

Coordinator, Computational Data Science, Utah Valley University

Sensitivity analysisData scienceMathematics

Mathematician, statistical consultant, and professor of computer science. Brian coordinates the computational data science program at Utah Valley University and contributes perspective on sensitivity analysis for causal inference.

Alexandra (Lexi) Pasi, PhD

CEO & Co-Founder, Lucidity Sciences

ML systemsHEORPlatform R&D

Data scientist and entrepreneur whose work bridges novel mathematics with practical machine learning. Through Lucidity Sciences and the Lumawarp engine, we are exploring next-generation ML approaches for real-world evidence problems in health economics and outcomes research.