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Justin Boutilier

Boutilier, Justin
Assistant Professor
Bachelor of Science (with Honors) (Acadia University), Doctor of Philosophy (University of Toronto)
Location
DMS 6149
Telephone
613-562-5800 x 1640
Email
This email address is being protected from spambots. You need JavaScript enabled to view it.
Website
a4hd.github.io

Biography

Professor Justin Boutilier is an Assistant Professor at the Telfer School of Management. His research focuses on developing and applying actionable analytics to solve health and humanitarian problems. He is interested in pursuing a diverse set of applications at the interface between predictive and prescriptive analytics. Much of Justin’s research focuses on global and planetary health because these areas have potential for significant practical impact, while motivating novel problem-driven theory at the intersection of optimization and machine learning.

Professor Boutilier’s work has been recognized by the Institute for Operations Research and the Management Sciences (INFORMS): once runner-up (2020) and twice finalist (2021, 2022) for the Pierskalla Best Paper Award, honorable mention for the Doing Good with Good OR Paper competition (2021), and as a PhD student, he won the Seth Bonder Scholarship for Applied Operations Research in Health Services (2017).

Justin received a B.Sc. in Mathematics and Statistics from Acadia University, a Ph.D. in Operations Research from the University of Toronto, and he was a postdoctoral associate with the Humanitarian Supply Chain Lab and the Center for Transportation and Logistics at MIT. Prior to joining Telfer, he was an Assistant Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin Madison.

Publications during the last 7 years

Papers in Refereed Journals

  • Boutilier, J.J., Michini, C. and Zhou, Z. 2024. Optimal Multivariate Decision Trees. Constraints, 28: 549–577.
  • Rana, S., Russell, T., Boutilier, J.J. and Goentzel, J. 2024. Discrete Event Simulation for Evaluating Fuel Distribution Interventions to Mitigate Disruptions. Production and Operations Management, (In Press).
  • Jolliff, A., Fields, B., Boutilier, J.J., Dudek, A., Elliott, C., Zuraw, M. and Werner, N.E. 2023. Care Partner Confidence and Experiences in Legal Planning for People Living with Dementia: A Mixed Methods Study. The Gerontologist, (In Press).
  • Liu, Y., Yu, M., LaMantia, J.N., Lobo, J.M., Boutilier, J.J. and Brennan, M.B. 2023. Associations between specialty care and improved outcomes among patients with diabetic foot ulcers. PLOS ONE, (In Press).
  • Boutilier, J.J., Yoeli, E., Rathauser, J., Owiti, P., Subbaraman, R. and Jónasson, J.O. 2022. Can digital adherence technologies reduce inequity in tuberculosis treatment success? Evidence from a randomized controlled trial in Nairobi, Kenya. BMJ Global Health, 7.
  • Smith, A.J., Patterson, B.W., Pulia, M.S., Mayer, J., Schwei, .R.J., Nagarajan, R., Liao, F. and Boutilier, J.J. 2022. Multisite Evaluation of Prediction Models for Emergency Department Crowding Before and During the COVID-19 Pandemic. Journal of the American Medical Informatics Association, 30(2): 292–300.
  • Boutilier, J.J., Loganathar, P., Linden, A., Scheer, E., Noejovich, S., Elliott, C., Zuraw, M. and Werner, N.E. 2022. A Web-Based Platform (CareVirtue) to Support Caregivers of People Living With Alzheimer Disease and Related Dementias: Mixed Methods Feasibility Study. JMIR Aging, 5(30).
  • Brice, S.N., Boutilier, J.J., Gartner, D., Harper, P., Knight, V., Lloyd, J., Pusponegoro, A.D., Rini, A.P., Turnbull-Ross, J. and Tuson, M. 2022. Emergency services utilization in Jakarta, Indonesia: A cross-sectional study of patients attending hospital emergency departments. BMC Health Services Research, 22.
  • Boutilier, J.J. and Chan, T.C.Y. 2022. Drone network design for cardiac arrest response. Manufacturing & Service Operations Management (M&SOM), 24(5): 2387-2796.
  • Sun, Y., Kaur, R., Gupta, S., Paul, R., Das, R., Cho, S.J., Anand, S., Boutilier, J.J., Saria, S., Palma, J., Saluja, S., McAdams, R.M., Kaur, A., Yadav, G. and Singh, H. 2021. Development and Validation of High Definition Phenotype (HDP) based mortality prediction in critical care units. Journal of the American Medical Informatics Association, 4(1).
  • Singh, H., Kusuda, S., McAdams, R.M., Gupta, S., Kalra, J., Kaur, R., Das, R., Anand, S., Pandey, A.K., Cho, S.J., Saluja, S., Boutilier, J.J., Saria, S., Palma, J., Kaur, A., Yadav, G. and Sun, Y. 2021. Machine Learning-Based Automatic Classification of Video Recorded Neonatal Manipulations and Associated Physiological Parameters: A Feasibility Study. Children, 8(1).
  • Boutilier, J.J., Chan, T.C.Y., Ranjan, M. and Deo, S. 2021. Risk Stratification for Early Detection of Diabetes and Hypertension in Resource-Limited Settings: Machine Learning Analysis. Journal of Medical Internet Research, 23(1).
  • Stoesser, C.E., Boutilier, J.J., Sun, C.L.F., Brooks, S.C., Cheskes, S., Dainty, K.N., Feldman, M., Ko, D., Lin, S., Morrison, L., Scales, D.C. and Chan, T.C.Y. 2021. Moderating effects of out-of-hospital cardiac arrest characteristics on the association between EMS response time and survival. Resuscitation, 169: 31-38.
  • Lee, Y., Mansur, R.B., Brietzke, E., Kapogiannis, D., Delgado-Peraza, F., Boutilier, J.J., Chan, T.C.Y., Carmona, N.E., Rosenblat, J.D., Lee, J.G., Maletic, V., Vinberg, M., Suppes, T., Goldstein, B.I., Ravindran, A.V., Taylor, V.H., Chawla, S., Nogueras-Ortiz, C., Cosgrove, V.E., Kramer, N.E., Ho. R,, Raison, C.A. and McIntyre, R.S. 2021. Peripheral inflammatory biomarkers define biotypes of bipolar depression. Molecular Psychiatry, 26: 3395–3406.
  • Boutilier, J.J. and Chan, T.C.Y. 2021. Introducing and Integrating Machine Learning in an Operations Research Curriculum: An Application-Driven Course. INFORMS Transactions on Education, 23(2): 57-135.
  • Boutilier, J.J., Jónasson, J.O. and Yoeli, E. 2021. Improving TB Treatment Adherence Support: The Case for Targeted Behavioral Interventions. Manufacturing & Service Operations Management (M&SOM), 24(6): 2797-3306.
  • Alcock, R., Boutilier, J.J. and Siddiq, A. 2021. Shield-Net: Matching Supply with Demand for Face Shields During the COVID-19 Pandemic. INFORMS Journal of Applied Analytics, 52(6): 471-582.
  • Boutilier, J.J. and Chan, T.C.Y. 2020. Ambulance Emergency Response Optimization in Developing Countries. Operations Research, 68(5): 1285-1624.
  • Lee, Y., Ragguett, R-M., Mansur, R.B., Boutilier, J.J., Rosenblat, J.D., Trevizol, A., Brietzke, E., Lin, K., Pan, Z., Subramaniapillai, M., Chan, T.C.Y., Fus, D., Park, C., Musial, N., Zuckerman, H., Chen, V.C-H., Ho, R., Rong, C. and McIntyre, R.S. 2018. Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review. Journal of Affective Disorders, 241(1): 519-532.
  • Goli, A., Boutilier, J.J., Craig, T., Sharpe, M.B. and Chan, T.C.Y. 2018. A small number of objective function weight vectors is sufficient for automated treatment planning in prostate cancer. Physics in Medicine & Biology, 63(19).
  • Babier, A., Boutilier, J.J., McNiven, A. and Chan, T.C.Y. 2018. Knowledge-based automated planning for oropharyngeal cancer. Medical Physics, 45(7): 2875-2883.
  • Babier, A., Boutilier, J.J., Sharpe, M.B., McNiven, A. and Chan, T.C.Y. 2018. Inverse optimization of objective function weights for treatment planning using clinical dose-volume histograms. Physics in Medicine & Biology, 63(10): 105004.
  • Boutilier, J.J., Brooks, S.C., Janmohamed, A., Byers, A., Buick, J.E., Zhan, C., Schoellig, A.P., Cheskes, S., Morrison, L.J. and Chan, T.C.Y. 2017. Optimizing a Drone Network to Deliver Automated External Defibrillators. Circulation, 135(25): 2454 - 2465.

Chapters in Books

  • Stratman, E.G., Boutilier, J.J. and Albert, L.A. Uncertainty in Facility Location Models for Emergency Medical Services. In Eiselt, H.A. and Marianov, V.. Uncertainty in Facility Location Problems. Springer, 2023.

Invited Contributions and/or Technical Reports

  • Russell, T., Boutilier, J.J., Kleinmann, S. and Goentzel, J. 2020. "Actionable Analysis: Simulating and Visualizing Fuel Distribution During Disasters", June.

Funded Research during the last 7 years

Funded Research during the last 7 years
From-To Source Title * ** Role Amount
2024-2026 Telfer School of Management Start-up grant O I PI $ 40,000
2022-2024 National Institutes of Health R44 SBIR: Design, development, and validation of an AI- enabled legal planning and financial management training tool for ADRD caregivers R O Co-I $ 221,922
2021-2022 National Institutes of Health R43 SBIR: Design, development, and validation of an AI- enabled legal planning and financial management training tool for ADRD caregivers R O Co-I $ 26,971
2020-2022 National Institutes of Health R41 STTR: Development of a Caregiver Application and AI- Enabled Intelligent Assistant to Support Families and Formal Care Providers in Caring for Persons with Alzheimer's Disease and Related Dementias R O Co-I $ 23,962
2020-2021 National Science Foundation RAPID: An Online Matching Platform for Coordinating Supply and Demand for Medical Equipment During the COVID-19 Pandemic R F PI $ 100,000

LEGEND:

*Purpose
C: Contract (R and D) | E: Equipment Grant | R: Research Grant | S: Support Award | P: Pedagogical Grant | O: Other, U: Unknown

**Type
C: Granting Councils | G: Government | F: Foundations | I: UO Internal Funding | O: Other | U: Unknown

Role
PI = Principal Investigator | Co-I = Co-Investigator | Co-PI = Co-Principal Investigator

Pillars
Greener Healthier

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