Methodologist, Ministry of Treasury Board and Finance, Government of Alberta, Canada
Former Assistant Professor at Parkinson's School of Health Science and Public Health, Loyola University Chicago. Specializing in Statistics, Computational Analysis, Data Science, and Dynamic Simulation Modeling.
Academic Background & Expertise
Educational Journey
MS in Applied Statistics
University of Dhaka, Bangladesh
BS in Applied Statistics
University of Dhaka, Bangladesh
Areas of Expertise
Advanced statistical methods for health research
Innovative approaches to complex data analysis
Complex systems analysis for health applications
Dr. Zahan brings extensive expertise in biostatistics, computational analysis, systems science, data science, machine learning, simulation modeling, complex systems, business statistics, data analytics, and dynamic modeling. Her interdisciplinary background enables innovative approaches to health research and data analysis.
Professional Experience
Methodologist
Government of Alberta (2025-Present)
Assistant Professor in Biostatistics
Loyola University Chicago (2024-2025)
Lecturer in Data Analytics
University of Saskatchewan (2023)
Dynamic Modeller
Sax Institute, Australia (2019-2023)
Mathematical Modeller
Public Health Agency of Canada (2017-2022)
Data Scientist (Contract)
University of California, Los Angeles and International Centre for Diarrheal Disease Research, Bangladesh (ICDDR,B)
Research & Publications
Published research in prestigious journals including JMIR Public Health and Surveillance, International Journal of Environmental Research and Public Health, and BMC Public Health, focusing on dynamic simulation models, opioid overdose deaths, and spatial analysis.
Presented at IEEE International Conference on Healthcare Informatics, International Conference on Social Computing, and other notable venues, showcasing work on machine learning approaches to health data and dynamic modeling.
Research featured in Canadian government reports including the Chief Public Health Officer's Report and Federal Framework for Suicide Prevention, demonstrating real-world impact of academic work.
Project Portfolio
A selection of research projects showcasing statistical expertise, methodological innovation, and interdisciplinary collaboration across various healthcare domains.
Suicide Prevention Research
Systems Science for Suicidal Behaviors
System Dynamics Model, Particle filtering, and Particle MCMC algorithms using C++, R, and GNU-based multithread processors
Developed complex mathematical models to simulate suicide and suicide-related behaviors across Canadian populations. This work provided policymakers with baseline tool to assess for resource allocation and program design.
Dynamic Simulation Models of Suicide: Systematic Review
Comprehensive systematic review of simulation models for suicide-related behaviors using Covidence
Evaluated studies published in English and French to identify key modeling approaches and their applications. Findings published in a high-impact journal highlighted critical gaps in current modeling approaches and established methodological standards for future research.
#chatsafe Suicide Postvention Response
Acceptability study using logistic regression modeling and intervention analysis with Stata
Evaluated a social media-based suicide prevention program targeting adolescents and young adults.
Social Media Activity After Cluster Suicides
Pilot case-control study using scan statistics, concept mapping, and sentiment analysis with SaTScan and ArcGIS
Pioneered innovative geospatial analysis techniques to identify patterns in social media responses following suicide clusters. Results informed the development of targeted digital intervention protocols now used by crisis response teams in multiple jurisdictions.
DNA Methylation Data for Suicide Prediction
Machine learning approach using PCA, t-SNE, Logistic regression, and SVM in R
Applied advanced machine learning algorithms to epigenetic markers to identify biological signatures associated with suicidal behavior. The resulting predictive model achieved over 90% accuracy in validation testing, offering potential for clinical screening applications.
Copycat Suicide Agent-Based Modeling
Investigation using agent-based simulation modeling in AnyLogic (Java-based)
Created detailed simulations of social contagion effects in suicide clusters, accounting for media exposure, peer networks, and individual vulnerability factors. This project informs media guidelines for suicide reporting adopted by journalist.
Educational Attainment and Suicide: Demographic and Occupational Disparities
Investigating relationships between advanced educational attainment and suicide risk factors across different demographic groups and professions in the United States. We are using SAS to conduct the analysis based on the data from Center for Disease Control (CDC) and Prevention mortality data.
Unraveling Temporal Dynamics of Psychiatric Symptoms
Applying continuous time structoral equation modeling (CTSEM) to smartphone-collected longitudinal data to track fluctuations in suicidality, depression, irritability, and social connectedness among psychiatric inpatients using R.
Opioid Crisis Research
Innovative statistical approaches to understand and address the complex dynamics of opioid use disorders and overdose prevention.
Opioid Overdose Deaths in Canada
Dynamic modeling of opioid crisis during COVID-19 pandemic using System Dynamics Simulation in AnyLogic
Developed comprehensive models with interventions include, but are not limited to, increasing the availability of take-home naloxone, elevated access to opioid agonist therapy, growing awareness of safety measures while using opioids, and the Good Samaritan Drug Overdose Act. Findings presented to federal health authorities informed emergency response strategies and resource allocation during the pandemic in Canada.
Hidden Elements of Opioid Abuse
Dynamic modeling with Big Data and Particle Markov Chain Monte Carlo using C++ and R
Utilized advanced Bayesian computational methods to integrate diverse data sources including emergency department visits, prescription monitoring programs, and community survey data. This novel approach revealed previously unidentified high-risk populations and leading to targeted intervention deployment.
Women and Children's Health Research
Statistical applications to address critical health disparities and improve outcomes for vulnerable populations.
Pregnancy Termination Factors in Bangladesh
Bayesian spatial analysis using logistic regression with Integrated Nested Laplace Approximation (INLA) in R
Conducted sophisticated spatial statistical analysis of demographic and health survey data covering 64 districts. Results identified significant geographic variations in access to reproductive healthcare and informed targeted interventions by NGOs working in underserved regions.
Lung Function in Cree First Nations Children
Reference equations using Generalized Additive Model for Location, Shape, and Scale (GAMLSS) in R
Developed the first population-specific pulmonary function reference equations for Indigenous children in Canada. This culturally tailored approach corrected systematic biases in standard reference values, improving diagnostic accuracy and treatment planning for respiratory conditions in this population.
Child Mortality Risk Factors in Bangladesh
Analysis using Cox's proportional hazards model implemented in R
Analyzed longitudinal data from over 8000 children to identify critical risk factors for childhood mortality. Findings highlighted the importance of parents' education, wealth index, birth interval, mother's age that provides influence to national public health initiatives and international aid progr
Grants & Awards
Research Grant
Start-up Research Grant from Loyola University Chicago (2024)
Department Grant
Internal department grant from Loyola University Chicago (2025)
Applied Science Award
Health Promotion and Chronic Disease Prevention Branch, Government of Canada
University of Saskatchewan
Dr. Zahan has received numerous awards throughout her career, including multiple Student Travel Awards, PhD Citizenship Award, Award of Excellence in Opioid Modeling, and various scholarships from institutions in Canada and Bangladesh, recognizing her excellence in research and academic contributions.
Teaching & Mentorship
Course Instruction
Teaching courses including Biostatistics-I, Public Health Capstone (co-teaching), Foundations of Business Statistics, and Statistics for Business Decisions, providing students with essential quantitative skills.
Student Supervision
Mentoring postdoctoral fellow, MPH students, and teaching assistants, guiding research projects and supporting academic development of future health science professionals.
Research Guidance
Supporting students and researchers in developing research skills, applying for grants, and presenting findings at conferences, fostering the next generation of biostatisticians and health researchers.
Professional Memberships
American Statistical Association (ASA)
American Public Health Association (APHA)
Statistical Society of Canada (SSC)
Bangladesh Statistical Association (BSA)
Leadership & Service
Academic Leadership
Served as President of Graduate Students' Association and Computer Science Graduate Council at University of Saskatchewan
Editorial Service
Reviewer for International Journal of Public Health, Model Assisted Statistics and Applications
Community Service
Volunteer at Saskatoon Bangla School, CFCR 90.5 FM community radio host, blood donor
Initiated Women in Computer Science Awards to recognize women's contributions in STEM research
Contact & Connect
Email: rizu.85@gmail.com
Dr. Rifat Zahan - Statistician & Data Scientist