Velibor V. Mišić

Assistant 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 assistant 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 broad research interest is to develop data-driven optimization methods for important practical problems. My research has focused on choice and assortment problems, dynamic decision making under uncertainty, robust optimization and healthcare applications. My CV can be viewed here. A list of my publications can be found below.


I currently serve as an associate editor for the INFORMS journal Service Science.


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

Submitted papers/working papers:

  1. Column-Randomized Linear Programs: Performance Guarantees and Applications.
    Chen, Y.-C., and Mišić, V. V. (2020)
    Submitted.
    [Abstract] [SSRN]
  2. A Framework for Evaluating Healthcare Machine Learning Models: Application and Analysis Using Hospital Readmission.
    Mišić, V. V., Rajaram, K. and Gabel, E. (2020)
    Submitted.
    [Abstract]
  3. Decision forest: a nonparametric approach to modeling irrational choice.
    Chen, Y.-C., and Mišić, V. V. (2019)
    Submitted.
    [Abstract] [SSRN]
    • Finalist, INFORMS George E. Nicholson Student Paper Competition (2020) (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.

Refereed journal papers:

  1. Interpretable optimal stopping.
    Ciocan, D. F., and Mišić, V. V. (2019)
    Forthcoming in Management Science.
    [Abstract] [DOI] [SSRN]
    • Finalist, INFORMS Data Mining Section Best Paper Competition, Applied Track (2018)
  2. Machine Learning Prediction of Post-Operative Emergency Department Hospital Readmission.
    Mišić, V. V., Gabel, E., Hofer, I., Rajaram, R., and Mahajan, A. (2019)
    Anesthesiology, 132 (5): 968-980.
    [Abstract] [DOI] [PDF]
  3. 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)
  4. 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]
  5. 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".
  6. 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]
  7. 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]
  8. Robust product line design.
    Bertsimas, D., and Mišić, V. V. (2017)
    Operations Research, 65 (1): 19 - 37
    [Abstract] [DOI] [PDF]
  9. 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]
  10. 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".
  11. 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
  12. 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]
  13. 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. Decision Forest: A Nonparametric Approach to Modeling Irrational Choice.
    • 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).
  2. A Machine Learning Model to Predict Unplanned Hospital Readmissions in Post-Operative Patients Using Electronic Medical Record Data.
    • 2019 POMS Conference, Washington, DC, May 3-6, 2019.
  3. Interpretable Optimal Stopping
    • 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.
  4. 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.
  5. 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.
  6. The Airlift Planning Problem.
    • 2016 INFORMS Annual Conference, Nashville, TN.
  7. Data-driven Assortment Optimization.
    • 2017 POMS Conference, Seattle, WA.
    • 2015 INFORMS Annual Conference, Philadelphia, PA.
    • 2015 MSOM Conference, Toronto, Canada.
  8. Decomposable Markov Decision Processes: a Fluid Optimization Approach.
    • 2015 ISMP Conference, Pittsburgh, PA.
    • 2014 INFORMS Annual Conference, San Francisco, CA.
  9. Robust Product Line Design.
    • 2017 POMS Conference, Seattle, WA.
    • 2014 Data-driven Optimization Workshop, Cornell University, Ithaca, NY.
  10. A Comparison of Robust Optimization and Monte Carlo Tree Search for Dynamic Resource Allocation.
    • 2013 INFORMS Annual Conference, Minneapolis, MN.
  11. Adaptive and Robust Radiation Therapy Optimization for Lung Cancer.
    • 2011 INFORMS Annual Conference, Charlotte, NC [PDF];
    • 2011 INFORMS Healthcare Conference, Montreal, Canada [PDF].
  12. Non-coplanar Beam Orientation Optimization for Total Marrow Irradiation using IMRT.
    • 2009 CORS-INFORMS International Meeting, Toronto, Canada. [PDF]

Selected course project work:

  1. Growth and inequality in the presence of taxation and inequality aversion.
    Mišić, V. V., and Thraves, C. (2014)
    Project for 15.795 (Behavioral Decision Theories and Applications) at MIT.
    [Abstract]
  2. Predicting hits on the Billboard Hot 100 Chart.
    Mišić, V. V., and Papush, A. M. (2013)
    Course project for 15.071 (The Analytics Edge) at MIT.
    [Abstract]

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

Instructor:

  1. MGMTMSA408 -- Operations Analytics (UCLA Anderson MSBA Core Class), Spring 2020 (1 section)
  2. MGMT 402 -- Data and Decisions (UCLA Anderson FEMBA Core Class), Fall 2019 (2 sections)
  3. MGMTMSA408 -- Operations Analytics (UCLA Anderson MSBA Core Class), Spring 2019 (1 section)
  4. MGMT 402 -- Data and Decisions (UCLA Anderson FEMBA Core Class), Fall 2018 (2 sections)
  5. MGMTMSA 408 -- Operations Analytics (UCLA Anderson MSBA Core Class), Spring 2018 (1 section)
  6. MGMT 402 -- Data and Decisions (UCLA Anderson MBA Core Class), Fall 2017 (3 sections)
  7. MGMT 402 -- Data and Decisions (UCLA Anderson FEMBA Core Class), Fall 2016 (2 sections)

Teaching assistantships:

(Teaching evaluations available upon request.)

  1. 15.727 -- The Analytics Edge (MIT Sloan Executive MBA Elective), Spring 2015
    • Instructors: Professor Dimitris Bertsimas and Dr. Allison K. O'Hair
    • Assisted in designing and grading homework, leading recitations over WebEx and advising student teams on course project.
    • Overall evaluation: 6.75/7.0.
  2. 15.071 -- The Analytics Edge (MIT Sloan MBA Elective), Spring 2014
    • Instructors: Professor Dimitris Bertsimas and Dr. Allison K. O'Hair
    • Assisted in designing and grading homework, leading recitations and advising student teams on course project.
    • Overall evaluation: 6.5/7.0.
  3. 15.071x -- The Analytics Edge (Massive Open Online Course (MOOC) offered through edX), Spring 2014
    • Instructors: Professor Dimitris Bertsimas and Dr. Allison K. O'Hair
    • As part of a team of four other PhD students and the two co-instructors, assisted in creating course content (lecture slides, recitations, homework and exam problems) and recording video recitations.

Other teaching experience:

  1. Guest lecturer for 15.073 -- Optimization Methods in Management Science (MIT Sloan Undergraduate Elective), Spring 2014
    • Instructor: Professor James B. Orlin
    • Delivered part of a lecture on optimization applications, on the topic of "Optimization in eHarmony" (originally developed for 15.071 and 15.071x).
  2. Session instructor for 15.S60 -- Special Seminar in Management: Software Tools for Operations Research (MIT IAP Course), January 2014

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

  • My brother Bratislav is a professor of neuroscience at McGill -- check out his research website 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