Justin Boutilier
- Pièce
- DMS 6149
- Téléphone
- 613-562-5800 poste 1640
- Courriel
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- a4hd.github.io
Biographie
Professeur adjoint à l’École de gestion Telfer, Justin Boutilier s’intéresse à la création et à l’application d’outils analytiques exploitables pour répondre à des enjeux dans la sphère de la santé ou de nature humanitaire. Ses travaux se situent au carrefour des analyses prédictives et prescriptives, qu’il applique à différents contextes. Comme le potentiel de retombées concrètes est y particulièrement élevé, ses projets portent en grande partie sur les domaines de la santé globale et planétaire; ce sont aussi des champs qui appellent à l’élaboration de théories nouvelles alliant optimisation et apprentissage machine dans une optique de résolution des problèmes.
La recherche du professeur Boutilier a été saluée par l’Institute for Operations Research and the Management Sciences (INFORMS); il a obtenu le deuxième prix Pierskalla pour le meilleur article en 2020 (pour lequel il a aussi été finaliste en 2021 et 2022) et reçu une mention honorable en 2021 pour sa participation au concours d’articles « Doing Good with Good OR ». En 2017, pendant ses études doctorales, il s’est vu décerner la bourse Seth-Bonder pour la recherche opérationnelle appliquée en services de santé (2017).
Le professeur Boutilier détient un B.Sc. en mathématiques et statistique de l’Université Acadia et un doctorat en recherche opérationnelle de l’Université de Toronto; il a également mené des recherches postdoctorales au Humanitarian Supply Chain Lab et au Center for Transportation and Logistics du MIT. Avant de se joindre à l’École Telfer, il était professeur adjoint au Département de génie industriel et des systèmes à l’Université du Wisconsin-Madison.
Publications au cours des 7 dernières années
Articles publiés dans des revues avec comité de lecture
- 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).
- Boutilier, J.J., Michini, C. and Zhou, Z. 2024. Optimal Multivariate Decision Trees. Constraints, 28: 549–577.
- 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).
- 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).
- 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).
- 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.
- 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.
- 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.
- 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.
- 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).
- 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.
- 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.
- 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).
- 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., 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).
- 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.
- 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).
- 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.
- 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.
- 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.
- 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.
Chapitres de livres
- 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.
Contributions sur invitation et/ou rapports techniques
- Russell, T., Boutilier, J.J., Kleinmann, S. and Goentzel, J. 2020. "Actionable Analysis: Simulating and Visualizing Fuel Distribution During Disasters", June.
Recherche subventionnée au cours des 7 dernières années
De-À | Source | Titre | * | ** | Rôle | Montant |
---|---|---|---|---|---|---|
2024-2026 | École de gestion Telfer | 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 |
LÉGENDE :
* But
C: Contrat de recherche | E: Subvention d'équipement | R : Subvention de recherche | S : Fonds de soutien | P : Subvention pédagogique | O : Autre | U : Inconnu
**Genre
C : Conseils subventionnaires | G : Gouvernements | F : Fondations | I : Financement interne UO | O : Autre | U : Inconnu
Rôle
PI = Chercheur(e) principal(e) | Co-I = Co-chercheur(e) | Co-PI = Co-Chercheur(e) principal(e)