Velibor V. Mišić

Associate Professor
Decisions, Operations and Technology Management Anderson School of Management
University of California, Los Angeles

CV: PDF
Email: velibor.misic@anderson.ucla.edu

Welcome to my website! I am an associate professor of Decisions, Operations and Technology Management at the Anderson School of Management at the University of California, Los Angeles. I received my PhD in June 2016 from the Operations Research Center at the Massachusetts Institute of Technology, where I was advised by Professor Dimitris Bertsimas.


My research is broadly on analytics: how to transform data into models that lead to effective decisions. Within this larger area, I have focused on three main substreams: problems involving dynamic decision making under uncertainty; problems involving customer choice; and problems at the interface of machine learning and optimization. My CV can be viewed here. A list of my publications can be found below.


I currently serve as an associate editor for Operations Research (Optimization and Decision Analysis areas), Manufacturing & Service Operations Management (Analytics in Operations department), and Production & Operations Management (Revenue Management and Marketplace Analytics department). I previously served as an associate editor for Service Science (2019 - 2023).


How to typeset my last name in LaTeX:   Mi\v{s}i\'{c}

Submitted papers/working papers:

  1. Randomized Robust Price Optimization.
    Guan, X., and Mišić, V. V. (2023)
    Major revision in Management Science.
    [Abstract] [SSRN]
  2. Randomized Policy Optimization for Optimal Stopping.
    Guan, X., and Mišić, V. V. (2022)
    Revise and resubmit in Management Science.
    [Abstract] [SSRN]
    • Finalist, INFORMS Finance Section Best Student Paper Competition (2023) (to student co-author X. Guan)
  3. Exact Logit-Based Product Design.
    Akçakuş, İ., and Mišić, V. V. (2021)
    Major revision in Management Science.
    [Abstract] [SSRN]
  4. Assortment Optimization under the Decision Forest Model.
    Akchen, Y.-C., and Mišić, V. V. (2021)
    Major revision in Manufacturing & Service Operations Management.
    [Abstract] [SSRN]

Refereed journal papers:

  1. Automated Scheduling of Doppler Exoplanet Observations at Keck Observatory.
    Handley, L. B., Petigura, E. A., Mišić, V. V., Lubin, J., and Isaacson, H. (2024)
    The Astronomical Journal, 167 (3): 122.
    [Abstract] [DOI] [PDF]
  2. Solving the Traveling Telescope Problem with Mixed Integer Linear Programming.
    Handley, L. B., Petigura, E. A., and Mišić, V. V. (2024)
    The Astronomical Journal, 167 (1): 133.
    [Abstract] [DOI] [PDF]
  3. Column-Randomized Linear Programs: Performance Guarantees and Applications.
    Akchen, Y.-C., and Mišić, V. V. (2023)
    Forthcoming in Operations Research.
    [Abstract] [SSRN] [DOI]
  4. Decision Forest: A Nonparametric Approach to Modeling Irrational Choice.
    Chen, Y.-C., and Mišić, V. V. (2022)
    Management Science, 68 (10): 7090-7111.
    [Abstract] [SSRN] [DOI] [Code]
    • Honorable Mention, INFORMS George E. Nicholson Student Paper Competition (2020) (awarded to student co-author Y.-C. Chen)
    • First Place, INFORMS Decision Analysis Society Best Student Paper Award (2019) (awarded to student co-author Y.-C. Chen)
    • Second Place, INFORMS Revenue Management and Pricing (RMP) Section Best Student Paper Award (2019) (awarded to student co-author Y.-C. Chen)
    • Finalist, INFORMS Service Science Section Best Paper Award (2019)
    • Spotlight presentation (16 out of 80+ submissions) at INFORMS Revenue Management & Pricing (RMP) Conference 2019, Stanford, CA.
    • Management Science Review Blog Post: Modeling Irrational Decisions
  5. A Simulation-Based Evaluation of Machine Learning Models for Clinical Decision Support: Application and Analysis Using Hospital Readmission.
    Mišić, V. V., Rajaram, K. and Gabel, E. (2021)
    npj (Nature) Digital Medicine, 4 (98): 1-11.
    [Abstract] [DOI] [PDF]
  6. Interpretable Optimal Stopping.
    Ciocan, D. F., and Mišić, V. V. (2022)
    Management Science, 68 (3): 1616-1638.
    [Abstract] [DOI] [SSRN]
  7. Machine Learning Prediction of Post-Operative Emergency Department Hospital Readmission.
    Mišić, V. V., Gabel, E., Hofer, I., Rajaram, R., and Mahajan, A. (2020)
    Anesthesiology, 132 (5): 968-980.
    [Abstract] [DOI] [PDF]
  8. Optimization of Tree Ensembles.
    Mišić, V. V. (2020)
    Operations Research, 68 (5): 1605-1624.
    [Abstract] [DOI] [Arxiv]
    • Second Place, INFORMS Junior Faculty Interest Group (JFIG) Paper Competition (2017)
  9. Data Analytics in Operations Management: A Review.
    Mišić, V. V. and Perakis, G. (2020)
    Manufacturing & Services Operations Management, 22 (1): 158-169.
    [Abstract] [DOI] [SSRN]
  10. Exact First-Choice Product Line Optimization.
    Bertsimas, D., and Mišić, V. V. (2019)
    Operations Research, 67 (3): 651-670.
    [Abstract] [DOI] [SSRN] [Code]
    • An earlier version of this work was titled "Data-driven assortment optimization".
  11. The Airlift Planning Problem.
    Bertsimas, D., Chang, A. A., Mišić, V. V., and Mundru, N. (2019)
    Transportation Science, 53 (3): 773-795.
    [Abstract] [DOI] [PDF]
  12. A Comparison of Monte Carlo Tree Search and Rolling Horizon Optimization for Large Scale Dynamic Resource Allocation Problems.
    Bertsimas, D., Griffith, J. D., Gupta, V., Kochenderfer, M. and Mišić, V. V. (2017)
    European Journal of Operational Research, 263 (2): 664-678.
    [Abstract] [DOI] [PDF] [Supplement]
  13. Robust Product Line Design.
    Bertsimas, D., and Mišić, V. V. (2017)
    Operations Research, 65 (1): 19 - 37
    [Abstract] [DOI] [PDF]
  14. Decomposable Markov Decision Processes: A Fluid Optimization Approach.
    Bertsimas, D., and Mišić, V. V. (2016)
    Operations Research, 64 (6): 1537 - 1555
    [Abstract] [DOI] [PDF] [e-companion]
  15. The Perils of Adapting to Dose Errors in Radiation Therapy.
    Mišić, V. V., and Chan, T. C. Y. (2015)
    PLoS ONE, 10 (5), e0125335.
    [Abstract] [DOI] [PDF]
    • An earlier version of this work was titled "Dose-reactive methods in adaptive robust radiation therapy for lung cancer".
  16. Adaptive and Robust Radiation Therapy Optimization for Lung Cancer.
    Chan, T. C. Y., and Mišić, V. V. (2013)
    European Journal of Operational Research, 231 (3) 745-756.
    [Abstract] [PDF] [Supplement]
    • Honorable mention, Canadian Operational Research Society (CORS) 2012 Student Paper Competition, Open Category
  17. Computational Enhancements to Fluence Map Optimization for Total Marrow Irradiation Using IMRT.
    Aleman, D. M., Mišić, V. V., and Sharpe, M. B. (2013)
    Computers & Operations Research, 40 (9) 2167-2177.
    [Abstract] [PDF]
  18. Neighborhood Search Approaches to Non-Coplanar Beam Orientation Optimization for Total Marrow Irradiation using IMRT.
    Mišić, V. V., Aleman, D. M., and Sharpe, M. B. (2010)
    European Journal of Operational Research, 205 (3) 522-527.
    [Abstract] [PDF]

Refereed conference proceedings:

  1. Optimization of Tree Ensembles.
    Mišić, V. V. (2017)
    Extended abstract for 2017 MSOM Conference, Chapel Hill, NC.
  2. Data-driven Assortment Optimization.
    Bertsimas, D. and Mišić, V. V. (2015)
    Extended abstract for 2015 MSOM Conference, Toronto, Canada.
  3. Total Marrow Irradiation Using Intensity Modulated Radiation Therapy Optimization.
    Mišić, V. V., Aleman, D. M., and Sharpe, M. B. (2009)
    Proceedings of the IIE Annual Conference, IERC 2009, Miami, Florida.

Book chapters:

  1. Optimization methods in large-scale radiotherapy
    Aleman, D. M., Ghaffari, H. R., Mišić, V. V., Sharpe, M. B., Ruschin, M., and Jaffray, D. A. (2012)
    Chapter in Systems Analysis Tools for Better Health Care Delivery.
    Editors: P. M. Pardalos, P. G. Georgiev, P. Papajorgji and B. Neugaard.

Invited talks:

  1. Assortment Optimization Under the Decision Forest Model.
    • Singapore University of Technology and Design, Engineering Systems and Design Research Seminar, January 26, 2022.
    • Columbia University, Graduate School of Business, Decision, Risk and Operations Seminar, November 23, 2021.
  2. Column-Randomized Linear Programs: Performance Guarantees and Applications.
    • Stanford University, Graduate School of Business, Operations, Information and Technology Seminar, October 5, 2023.
    • University of British Columbia, Sauder School of Business, Operations and Logistics Seminar, February 12, 2021.
  3. Decision Forest: A Nonparametric Approach to Modeling Irrational Choice.
    • Massachusetts Institute of Technology, Sloan School of Management, Operations Management Seminar, May 17, 2021.
    • 2019 INFORMS Annual Conference, Seattle, WA, October 20-23, 2019 (presented by student co-author Y.-C. Chen).
    • 2019 ICCOPT Conference, Berlin, Germany, August 5-8, 2019.
    • 2019 INFORMS Revenue Management and Pricing (RMP) Conference, Stanford, CA, June 6-7, 2019 (spotlight presentation; presented by student co-author Y.-C. Chen).
    • 2019 POMS Conference, Washington, DC, May 3-6, 2019 (presented by student co-author Y.-C. Chen).
    • 2018 INFORMS Annual Conference, Phoenix, AZ, November 4-7, 2018 (presented by student co-author Y.-C. Chen).
  4. A Machine Learning Model to Predict Unplanned Hospital Readmissions in Post-Operative Patients Using Electronic Medical Record Data.
    • 2021 CORS Annual Conference (Virtual), June 7-10, 2021.
    • 2019 POMS Conference, Washington, DC, May 3-6, 2019.
  5. Interpretable Optimal Stopping.
    • 2021 CORS Annual Conference (Virtual), June 7-10, 2021.
    • University of Illinois Chicago, School of Business, Information and Decision Sciences Seminar, February 5, 2021.
    • University of Southern California, Marshall School of Business, Data Sciences and Operations Seminar, January 29, 2021.
    • 2019 INFORMS Annual Conference, Seattle, WA, October 20-23, 2019.
    • 2019 POMS Conference, Washington, DC, May 3-6, 2019.
    • University of Maryland, Smith School of Business, Decisions, Operations and Information Technology Seminar, April 19, 2019.
    • 2018 INFORMS Annual Conference, Phoenix, AZ, November 4-7, 2018.
    • 2018 IMA Workshop on "Forging a New Discipline: Data-driven Supply Chain Management", University of Minnesota, Minneapolis, MN, October 3-5, 2018.
    • 2018 ISMP Conference, Bordeaux, France, July 1-7, 2018.
  6. Exact First-Choice Product Line Optimization.
    • 2018 INFORMS Annual Conference, Phoenix, AZ, November 4-7, 2018.
    • 2017 INFORMS Annual Conference, Houston, TX, October 22-25, 2017.
  7. Optimization of Tree Ensembles.
    • 2019 INFORMS Annual Conference, Seattle, WA, October 20-23, 2019.
    • 2019 Machine Learning in Science and Engineering Conference, Georgia Institute of Technology, Atlanta, GA, June 10-11, 2019.
    • 2018 INFORMS Annual Conference, Phoenix, AZ, November 4-7, 2018.
    • Duke University, Fuqua School of Business, Decision Sciences Seminar, March 14, 2018.
    • 2017 INFORMS Annual Conference, Houston, TX, October 22-25, 2017.
    • 2017 MSOM Conference, Chapel Hill, NC, June 19-21, 2017.
    • INSEAD, Decision Sciences and Technology and Operations Management Seminar, June 7, 2017.
    • 2017 Computational Management Science Conference, Bergamo, Italy, May 30 - June 2, 2017.
    • 2017 SoCal OR/OM Day, University of Southern California, May 19, 2017.
  8. The Airlift Planning Problem.
    • 2016 INFORMS Annual Conference, Nashville, TN.
  9. Data, Models and Decisions in Large-Scale Stochastic Optimization.
    • University of California Los Angeles, Anderson School of Management, Decisions, Operations and Technology Management Seminar, February 2016.
    • University of Chicago, Booth School of Business, Operations Management Seminar, February 2016.
    • Carnegie Mellon University, Tepper School of Business, Operations Management Seminar, January 2016.
  10. Data-driven Assortment Optimization.
    • 2017 POMS Conference, Seattle, WA.
    • University of Southern California, Marshall School of Business, Data Sciences and Operations Seminar, February 2016.
    • University of Waterloo, Department of Management Sciences, January 2016.
    • University of Toronto, Department of Mechanical and Industrial Engineering, January 2016.
    • 2015 INFORMS Annual Conference, Philadelphia, PA.
    • 2015 MSOM Conference, Toronto, Canada.
  11. Decomposable Markov Decision Processes: a Fluid Optimization Approach.
    • 2015 ISMP Conference, Pittsburgh, PA.
    • 2014 INFORMS Annual Conference, San Francisco, CA.
  12. Robust Product Line Design.
    • 2017 POMS Conference, Seattle, WA.
    • 2014 Data-driven Optimization Workshop, Cornell University, Ithaca, NY.
  13. A Comparison of Robust Optimization and Monte Carlo Tree Search for Dynamic Resource Allocation.
    • 2013 INFORMS Annual Conference, Minneapolis, MN.
  14. Adaptive and Robust Radiation Therapy Optimization for Lung Cancer.
    • 2011 INFORMS Annual Conference, Charlotte, NC [PDF];
    • 2011 INFORMS Healthcare Conference, Montreal, Canada [PDF].
  15. Non-coplanar Beam Orientation Optimization for Total Marrow Irradiation using IMRT.
    • 2009 CORS-INFORMS International Meeting, Toronto, Canada. [PDF]

Theses:

  1. Data, models and decisions for large-scale stochastic optimization.
    Massachusetts Institute of Technology, PhD thesis. (2016)
    [Abstract] [PDF]
  2. Adaptive and robust radiation therapy optimization for lung cancer.
    University of Toronto, Master of Applied Science thesis. (2012)
    [Abstract] [PDF]
  3. Computational enhancements to fluence map optimization for total marrow irradiation using IMRT.
    University of Toronto, Bachelor of Applied Science thesis. (2010)
    [Abstract] [PDF]
    • Centennial Thesis Award, University of Toronto, 2010

Current students:

  1. Xinyi Guan
    UCLA Anderson DOTM PhD Student
    Research topic: Randomization approaches in stochastic control and revenue management
    Expected graduation: June 2024
    [Website]
    • On the academic job market (2023-2024 academic year)

Graduated students:

  1. Yi-Chun Chen (2022)
    UCLA Anderson DOTM PhD Student
    Research topic: Data-driven models for irrational customer choice behavior
    Placement: University College London (UCL) School of Management, Assistant Professor [Website]
  2. İrem Akçakuş (2023)
    UCLA Anderson DOTM PhD Student
    Research topic: Modern optimization approaches in machine learning and product development
    Placement: Gopuff, Data Science

Instructor:

  1. MGMTMSA408 -- Operations Analytics (UCLA Anderson MSBA Core Class), Spring 2023 (2 sections)
  2. MGMTEX 402 -- Data Analysis and Management Decisions under Uncertainty (UCLA Anderson EMBA Core Class), Fall 2022 (1 section)
  3. MGMTGEX 402 -- Data Analysis and Management Decisions under Uncertainty (UCLA Anderson / NUS GEMBA Core Class), Summer 2022 (1 section)
  4. MGMTMSA408 -- Operations Analytics (UCLA Anderson MSBA Core Class), Spring 2022 (1 section)
  5. MGMTMSA408 -- Operations Analytics (UCLA Anderson MSBA Core Class), Spring 2021 (1 section)
  6. MGMT 402 -- Data and Decisions (UCLA Anderson FEMBA Core Class), Fall 2020 (3 sections)
  7. MGMTMSA408 -- Operations Analytics (UCLA Anderson MSBA Core Class), Spring 2020 (1 section)
  8. MGMT 402 -- Data and Decisions (UCLA Anderson FEMBA Core Class), Fall 2019 (2 sections)
  9. MGMTMSA408 -- Operations Analytics (UCLA Anderson MSBA Core Class), Spring 2019 (1 section)
  10. MGMT 402 -- Data and Decisions (UCLA Anderson FEMBA Core Class), Fall 2018 (2 sections)
  11. MGMTMSA 408 -- Operations Analytics (UCLA Anderson MSBA Core Class), Spring 2018 (1 section)
  12. MGMT 402 -- Data and Decisions (UCLA Anderson MBA Core Class), Fall 2017 (3 sections)
  13. MGMT 402 -- Data and Decisions (UCLA Anderson FEMBA Core Class), Fall 2016 (2 sections)

An up-to-date version of my CV can be downloaded here.

  • MOST: During my PhD I was first treasurer and later president of the MIT Organization of Serbian Students (MOST). MOST organizes various events at MIT (dinners, dessert nights, etc.) with good food and even better company. You can learn more about MOST at this link.

Anderson School of Management
University of California, Los Angeles
110 Westwood Plaza
Los Angeles CA, USA
90095

Email: velibor.misic@anderson.ucla.edu