Consulting
Causal Inference & RWE
Whether you’re evaluating treatment effects in routine care, assessing safety signals post-approval, generalizing trial results to broader populations, or supporting health technology assessments, I apply state-of-the-art techniques — including target trial emulation, g-methods, doubly robust estimation, sensitivity analysis, and directed acyclic graphs (DAGs) — to deliver transparent, reproducible, and regulator-ready evidence.
My work integrates target trial emulation, advanced g-methods, doubly robust estimation, and causal diagrams to ensure rigor in real-world settings.
Consulting Services
Causal inference is central to modern real-world evidence generation. Below are focused consulting areas where I apply advanced statistical and epidemiologic methods to answer high-stakes clinical, regulatory, and public health questions.
Real-World Evidence (RWE) & Data Analytics
Post-Marketing Surveillance & Pharmacovigilance Analytics
Environmental & Population Health Statistics
Causal Inference Consulting
Professional Background & Expertise
"Academic Excellence and Statistical Leadership"
Academic & Professional Background
- 10 Years as University Lecturer: Established educator of complex statistical concepts
- Academic Leadership: Former Chairman and President of Mathematics and Statistics Student Association at Université de Montréal
- Bilingual Expertise: Skilled at explaining complex concepts in both French and English
- Educational Philosophy: "He has a deep understanding of statistics, yet is able to skillfully explain complex concepts to people with little-to-no background in statistics both in French and English." - Close collaborator
Research & Publication Impact
- Academic Citations:Contributing to high-impact research across multiple disciplines
- Published Collaborations: Co-author on prestigious journal publications including COVID-19 immunity research
- Cross-Disciplinary Research: Working with academics in immunology, virology, nephrology, neurology, epidemiology, psychiatry, social cognition science, agronomy, ecology, and more
- Industry Experience: Collaboration with biotech and biopharma R&D teams, randomized trials and real-world evidence studies
Statistical Specializations
- Core Statistics: Comprehensive expertise in advanced statistical methodology and modelling
- Biostatistics Focus: Specialized applications in biological and health sciences
- Causal Inference: Modern methods for understanding cause-and-effect relationships
- Study Design:Experimental design, methodology, and data analysis
- Machine learning and AI: Industry experience in leveraging big data, algorithms and causal AI
- Consulting Excellence: Helping scientists bring research to life through best statistical practices