CV
A concise web-based version of my CV is below.
Profile summary
Ph.D. Candidate in Computing at Queen’s University and Lead Data Scientist at Venford Technologies. My work spans causal inference, Bayesian modelling, simulation, and explainable AI, with a particular focus on causal discovery, forecasting, and decision-making under changing conditions.
Education
Ph.D., Computing
Queen’s University, Kingston, Ontario, Canada
2022–2026
M.Sc., Computer Science, AI Specialization
Lakehead University, Thunder Bay, Ontario, Canada
2020–2022
Honours B.Sc., Computer Science
Lakehead University, Thunder Bay, Ontario, Canada
2017–2020
B.Eng., Civil Engineering
Lakehead University, Thunder Bay, Ontario, Canada
2010–2014
Professional Experience
Venford Technologies
Lead Data Scientist, 2026-Present
- Develop modelling, simulation, and machine-learning methods for decision intelligence and digital-twin applications.
- Contribute to the core technical architecture underlying the modelling and simulation platform.
- Implement computational approaches for scenario analysis, uncertainty quantification, policy evaluation, and complex-system decision-making.
- Translate research ideas in probabilistic modelling, simulation, and AI into applied software solutions.
Selected recent publications
Brandon Mossop and Salimur Choudhury. Causal Story-Guided Agentic Causal Discovery with Small Language Models. Accepted to the 4th International Conference on Foundation and Large Language Models, 2026.
Brandon Mossop and Salimur Choudhury. Regime-aware causal Bayesian forecasting for non-stationary time series. PLOS ONE, 2026.
Brandon Mossop and Salimur Choudhury. Improving machine learning forecasting explainability and performance with causal feature selection for infectious disease spread. INFOR: Information Systems and Operational Research, 2026.
Brandon Mossop and Salimur Choudhury. Agent-guided Causal Discovery with a Small Language Model. International Conference on Foundation and Large Language Models (FLLM 2025), 2025.
See the complete publications page.
Teaching
Queen’s University
Teaching Assistant, 2023-Present
- CISC 223: Software Specifications
- CISC 452: Neural and Genetic Computing
- CISC 352: Artificial Intelligence
- CISC 203: Discrete Structures II
- CISC 151: Elements of Computing with Data Analytics
Trent University
Guest Lecturer, 2024
Delivered an undergraduate guest lecture on time series forecasting.
Lakehead University
Graduate Assistant, 2020-2022
- COMP 5421: Deep Learning
- COMP 5012: Big Data
- COMP 5013: Pattern Recognition
- COMP 4111: Clinical Decision Support
- COMP 2412: Data Structures
Service & Community Engagement
Technical Program Committee (TPC), 4th International Conference on Foundation and Large Language Models (FLLM 2026) (2026)
- Reviewed and evaluated submitted research papers
- Contributed to the technical program and peer-review process
Reviewer, Information Processing & Management (2026)
Reviewer, INFOR: Information Systems and Operational Research (2026)
Ph.D.-Community Initiative, Queen’s University (2023–2024)
- Collaborated with an interdisciplinary team and KFL&A Public Health to develop organizational guidance for the responsible use of generative AI
- Contributed to recommendations for the practical, ethical, and responsible adoption of generative AI within the organization