Core Team

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Paul Arora


Founding Partner / Managing Director

MSc. Epidemiology
(University of Toronto)
PhD. Epidemiology
(University of Toronto)

Paul Arora completed his PhD in Epidemiology from the University of Toronto and serves as Founding Partner and Managing Director at Lighthouse Outcomes Inc. He has co-authored over 30 peer-reviewed scientific publications in influential journals including The Lancet, The American Journal of Epidemiology, British Medical Journal, and the Canadian Medical Association Journal. He has worked extensively with evidence synthesis methods including systematic literature reviews and meta-analyses.

Paul was a member of The Lancet Diarrhoea and Pneumonia Interventions Study Group and has served as a Biologist at the Public Health Agency of Canada in the National Public Health Laboratory. He holds an Assistant Professor status appointment at the Dalla Lana School of Public Health, University of Toronto in the Division of Epidemiology where he teaches epidemiology at the graduate level.

He recently served as Epidemiologist and Visiting Scholar at the Centre for Global Child Health at the Hospital for Sick Children. Paul’s primary research interests are in the application and development of knowledge synthesis, decision analysis and quantitative methods to address the evidence for medical interventions to reduce the burden of chronic and infectious diseases.

Darren R. Brenner


Senior Consultant

MSc. Epidemiology
(Brock University)
PhD. Epidemiology
(University of Toronto)
Postdoctoral Fellowship
International Agency for Research on Cancer (WHO)

Dr. Darren Brenner is an epidemiologist with over a decade of experience conducting observational and intervention research on chronic disease risk and survival. To date he has published over 75 peer-reviewed articles in leading journals in the area medicine, public health and epidemiology.

He is sought out for his epidemiologic expertise in the area of cancer etiology and methods of disease estimation. Darren has led several large multi-centered analyses of observational (real world) datasets as well as systematic literature reviews and meta-analyses in the oncology space. He completed his PhD at the University of Toronto followed by a post-doctoral fellowship at the International Agency for Research on Cancer of the World Health Organization in Lyon France.

Darren leads a program of research focused on the intersection of genetics, lifestyle and molecular pathways in the development of several cancers, including colon, lung and breast. Several studies examining the utility of biomarkers in the prediction of cancer risk are underway. Darren is also leading several international analyses of disease burden modelling in the oncology space.

Audrey Béliveau

audrey beliveau

Director of Analytics / Consulting Principal Statistician

MSc. Statistics
(Université de Montréal)
PhD. Statistics
(Simon Fraser University)
Postdoctoral Research Fellow
(University of British Columbia)

Audrey Béliveau is an Assistant Professor of statistics at the University of Waterloo. She has developed quantitative solutions in network meta-analysis (NMA) and other statistical areas for companies, government agencies and the academic environment.

Audrey has developed projects in simulation studies, power calculation, Before-After-Control-Impact designs, capture-recapture studies, Bayesian modelling, survey sampling and statistical methodology. Her current area of research is on the threats to validity of NMA. She has presented on the influence of baseline treatment effects and the role of fixed- versus random-effects in NMA.

Her work in applied statistics in the field of ecology led to her development of a new Bayesian modelling framework to integrate capture-recapture data with other sources of data in a fully explicit manner. This new approach relies on the use of an appropriate set of latent variables that allows for the formulation of the full joint likelihood of a dataset.

Marek J Druzdzel


Senior Consulting Scientist, Machine Learning

PhD. Engineering and Public Policy
(Carnegie Mellon University)
MS. Computer Engineering
(Delft University of Technology)
MS. Technical Mathematics and Informatics
(Delft University of Technology)

Marek Druzdzel is a Founding Partner at BayesFusion, LLC. He is a graduate of the Delft University of Technology, The Netherlands (M.Sc. degrees in Computer Science and in Electrical Engineering) and holds a Ph.D. degree from Carnegie Mellon University, Pittsburgh, PA, USA.

Marek has worked in the area of decision-theoretic systems for almost 30 years and has been the principal conceptual designer of GeNIe and SMILE, a software engine widely used to power Bayesian network (BN) models. Prof. Druzdzel has published widely on BN applications in health and other field including methodological advances in the use of BNs.

Jean Hai Ein Yong


Senior Consulting Scientist, Health Economics

MASc. Industrial Engineering
(University of Toronto)
BASc. Engineering
(University of Toronto)

Jean completed her training in operational research and health economics at the University of Toronto. She has more than 10 years of experience in developing evidence to inform resource allocation decisions in health care settings. Her expertise is in health technology assessments. She has extensive experience in assessing health care delivery models, complex interventions, screening strategies, drug therapies and medical devices, particularly in the oncology space.

Justin J Slater

justin j slater

Analytics Lead and Statistics & Methodology

MSc. Statistics
(Queen’s University)
Hon. BSc. Math and Statistics
(Dalhousie University)

Justin Slater completed his MSc in Statistics from Queen’s University and serves as an Analytics Lead at Lighthouse outcomes. To date he has acted as the primary statistician on 10 observational studies in a variety of areas, including acute kidney injury and the opioid crisis.

Before coming to Lighthouse, Justin served as a biostatistician at the Institute for Clinical Evaluative Sciences. His focus was applying modern statistical methods to real-world kidney health datasets. His contributions to this field will be highly impactful to Ontario’s renal healthcare policy over the next 5 years.

Justin has extensive experience in survival analysis, applied time series, and Bayesian modelling. His current professional interests lie in predictive modelling using Bayesian Networks, and software development for Network Meta-Analysis.

Alind Gupta


Senior Research Associate, Machine Learning

PhD(c) Molecular Genetics
(University of Toronto)
Hon. B.Sc. Microbiology &

(University of Toronto)

Alind is completing his PhD at the University of Toronto studying ways for better prognosis of rare multi-organ diseases called ciliopathies. He currently serves as Research Consultant at Lighthouse Outcomes.

For his PhD, he used probabilistic modelling and traditional machine learning techniques for mining heterogeneous real-world datasets, such as gene expression profiles and biological images, in an effort to combine cell biology with interpretable, generative Bayesian statistical models.

At Lighthouse Outcomes, Alind is using methods for Bayesian network structure learning to develop reasoning and clinical decision support systems.

Devon J Boyne


Research Consultant, Real-world evidence

PhD(c) Epidemiology
(University of Calgary)
MSc. Epidemiology
(Queen’s University)

Devon Boyne is completing his PhD. in Epidemiology in the Department of Community Health Sciences at the University of Calgary. He holds an MSc. degree in Epidemiology from Queen’s University and a Certificate in Data Analysis from the SAS Institute. His doctoral research involves the exploration of methods for synthesizing evidence from randomized clinical trials and observational studies within network meta-analyses.

His other research interests include the development and validation of clinical prediction models and the identification of optimal dynamic treatment regimes using real-world evidence. In addition to having several peer-reviewed publications in oncology, Devon has helped to teach numerous graduate-level courses in quantitative epidemiology and biostatistics including courses on survival analysis and multilevel modeling.

Outside of his graduate studies, Devon has experience in applying advanced statistical methods to real-world evidence. Such methods include G methods, propensity scores, instrumental variables, and directed acyclic graphs. Devon is also a classically trained pianist and he enjoys running and playing the piano in his spare time.

Eric Mackay



MA. Economics
(Queen’s University)
MSc. Statistics
(University of Toronto)

Eric completed his MSc in Statistics at the University of Toronto. He serves as a statistician at Lighthouse Outcomes.

Eric also holds an MA in Economics from Queen’s University and has previously worked as a consulting associate in the Antitrust and Competition Economics practice at Charles River Associates. He has extensive experience with methods of causal inference for observational data, including differences-in-differences, instrumental variables, and structure learning for directed acyclic graphs.

His primary interests are in Bayesian methods, causal inference, and probabilistic graphical models. He also has interests and experience in machine learning.

Contact us

1 University Avenue. 3rd Floor.
Toronto, Ontario.
M5J 2P1. Canada