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Justin Boutilier

Boutilier, Justin
Professeur adjoint
Bachelor of Science (with Honors) (Acadia University), Doctor of Philosophy (University of Toronto)
Pièce
DMS 6149
Téléphone
613-562-5800 poste 1640
Courriel
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Site web
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

  • 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.

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

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)

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