Ehsan Karim

Assistant Professor

Research Classification

Epidemiology
Pharmacoepidemiology
Statistics and Probabilities
Data mining
Parametric and Non-Parametric Inference
Community Health / Public Health
Model Building
Computer Science and Statistics

Research Interests

Causal inference
Biostatistics
Statistics
Machine Learning
data science
Survey sampling

Relevant Degree Programs

 

Biography

Dr. M. Ehsan. Karim is an Assistant Professor at the UBC School of Population and Public Health, and a Scientist & a Biostatistician at the Centre for Health Evaluation and Outcome Sciences (CHÉOS). He obtained his PhD in Statistics from the University of British Columbia. He completed his postgraduate training in the Department of Epidemiology, Biostatistics, and Occupational Health at McGill University, and was also a trainee at the Canadian Network for Observational Drug Effect Studies (CNODES). His current research focuses on causal inference and real-world observational data analyses, in both cross-sectional and longitudinal settings; patient-oriented research; survival analysis & survey sampling methodologies; applications of machine learning approaches, big-data analytics and Bayesian methodologies in epidemiologic studies.

Research Methodology

Mediation Analysis
Time-dependent confounding
Statistical learning
Longitudinal Data Analysis
Survival Analysis
Observational data analysis
Patient-Oriented Research
High-dimensional propensity score
Marginal structural models
Immortal-time bias
Multiple sclerosis
Super learner
Monte Carlo Simulation
Non-differential Exposure Misclassification
R
Directed Acyclic Graphs
Frailty Model
Bayesian methodologies
Big-Data Analysis
Predictive Modelling
Statistical Computing

Recruitment

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Master's students
Doctoral students
Any time / year round
2017
2018
2019
2020

I am currently looking for multiple graduate students for the following two projects (with methodologic focuses within epidemiologic contexts):
(1) Improving Causal Inference Methods in Statistics for Analyzing High-dimensional / Big Data.
(2) Developing and Evaluating Causal Inference Methods for Pragmatic Trials to address nonadherence.
Graduate students in statistics, biostatistics, epidemiology, economics or computer science with some methodological expertise in statistics and statistical software are encouraged to contact me directly (particularly those with some of the following skills: making data requests, extracting analytic data from administrative / survey databases, running statistical analyses, coding statistical estimators, conducting simulation studies, excellent scientific writing, ability to work on a multidisciplinary team). Interested candidates should email me (at my UBC email address) their complete CV and a cover letter. Only candidates shortlisted will be contacted.

I support public scholarship, e.g. through the Public Scholars Initiative, and am available to supervise students and Postdocs interested in collaborating with external partners as part of their research.
I support experiential learning experiences, such as internships and work placements, for my graduate students and Postdocs.

Publications

 
 

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