Julian Wolfson, PhD
Associate Professor, Division of Biostatistics
Associate Professor, Division of Biostatistics
PhD, Biostatistics, University of Washington, 2009
BS, Mathematics and Computer Science, McGill University, 2004
Summary
My research lies at the intersection of causal inference and machine learning, particularly as applied to large, messy datasets. I have applied my methods to problems such as finding surrogate endpoints in clinical trials, identifying relevant explanatory variables in the presence of correlation and measurement error, predicting the risk of heart attacks using electronic health record data, and understanding human behavior patterns using smartphone sensor data. My collaborative work spans multiple disciplines, including infectious disease (HIV/Ebola), cardiovascular health, nutrition and obesity, and pediatrics. I serve as lead statistician on a number of clinical trials, consult on small projects with a wide variety of investigators, and participate in interdisciplinary research teams pursuing longer-term research projects.
Expertise
Chronic diseases, food & nutrition, infectious disease, methods, causal inference, machine learning, variable selection, risk prediction, HIV/AIDS
Awards & Recognition
Professional Associations
Research
Research Methods/Techniques
Research Funding Grants
- NIH/NHLBI, "Targeting Anticoagulant to Reduce Inflammation in Treated HIV Disease," C- Investigator
- NIH/NIA, "Treatment to Reduce Inflammation and Improve Immune Recovery Among Older HIV Patients," Co-Investigator
- NIH/NIDDK, "Weight Tracking and Weight Loss Outcomes: Establishing the Standard of Care," Co-investigator
- Minnesota Metropolitan Council, "Smartphone-Based Interventions for Sustainable Travel Behavior," Co-Investigator
- National Science Foundation, "SRN: Integrated Urban Infrastructure Solutions for Environmentally Sustainable, Healthy and Livable Cities."
Patents
SmarTrAC: A smartphone solution for travel and activity capturing.
- Inventors: Fan Y, Wolfson J and Adomavicius G
- Provisional patent filed August 2014
- Full patent application filed August 2015
Publications
See a full list of my publications on Google Scholar
Selected Publications
- Wolfson J, Vock DM, Bandyopadhyay S, Kottke T, Vazquez Benitez G, Johnson P, Adomavicius G, and O'Connor PJ. "Use and Customization of Risk Scores for Predicting Cardiovascular Events Using Electronic Health Record Data," To appear, Journal of the American Heart Association, 2017.
- Brown, B., Miller, C.J., and Wolfson, J. "ThrEEBoost: Thresholded Boosting for Variable Selection and Prediction Via Estimating Equations," Journal of Computational and Graphical Statistics, March 2017.
- Wolfson J, Bandyopadhyay S, Elidrisi M, Vazquez-Benitez G, Vock DM, Musgrove D, Adomavicius G, Johnson PE, O'Connor PJ. "A Naive Bayes Machine Learning Approach to Risk Prediction Using Censored, Time-to-Event Data," Statistics in Medicine, September 2015
Teaching
Teaching Areas
I teach biostatistics courses and serve as an adviser for Master's and PhD students.
Courses
- PubH 6450, Biostatistics I
- PubH 7430, Statistical Methods for Correlated Data
- PubH 7461, Exploring and Visualizing Data in R
- PubH 8412, Advanced Statistical Inference
Community Engagement
- Associate Editor for Reproducibility, Journal of the American Statistical Association. Read more
- Associate Editor, International Journal of Biostatistics
Media
In The News
SPH News
- Study Tests Cardiovascular Risk Models with Patient Health Data
- Tracking Daily Activity to Understand Movement
- Wolfson Named Reproducibility Editor for Leading Statistics Journal
In The Media
- App promotes sustainable transportation options to UMN contract parkers (Minnesota Daily)