Mucahit Cevik

150 

Mucahit Cevik, Ph.D.
Assistant Professor
Mechanical and Industrial Engineering
Ryerson University

Contact

350 Victoria Street,
Toronto, ON, Canada, M5B 2K3
Phone: x3756
mcevik[at]ryerson[dot]ca

Education

Ph.D., Industrial and Systems Engineering, University of Wisconsin-Madison, 2016
M.S., Industrial Engineering, Bogazici University, 2011
B.S., Industrial Engineering, Bogazici University, 2009

Research Interests

Methodologies: Markov Decision Processes, Integer Programming, Stochastic Programming, Machine Learning
Applications: Healthcare Operations, Medical Decision Making, Radiation Therapy

Journal Papers

  1. M. Cevik, D. Aleman, Y. Lee, A. Berdyshev, H. Nordstrom, S. Riad, A. Sahgal, M. Ruschin, “Simultaneous optimization of isocenter locations and sector duration in radiosurgery”, Physics in Medicine & Biology, 2019.

  2. M. Cevik, P. Shirvani Ghomi, D. Aleman, Y. Lee, A. Berdyshev, H. Nordstrom, S. Riad, A. Sahgal, M. Ruschin, “Modeling and comparison of alternative approaches for sector duration optimization in a dedicated radiosurgery system”, Physics in Medicine & Biology, 2018.

  3. M. Cevik, T. Ayer, O. Alagoz, B. Sprague, “Analysis of mammography screening policies under resource constraints”, Production and Operations Management, 2018.

  4. J. Van Den Broek, N. Van Ravesteyn, J. Mandelblatt, M. Cevik, C. Schechter, S. Lee, H. Huang, Y. Li, D. Munoz, S. Plevritis, H. De Koning, N. Stout, M. Van Ballegooijen, “Comparing CISNET breast cancer models using the maximum clinical incidence reduction methodology”, Medical Decision Making, 2018.

  5. O. Alagoz, M. Ergun, M. Cevik, B. Sprague, D. Fryback, R. Gangnon, J. Hampton, N. Stout, A. Trentham-Dietz, “The University of Wisconsin breast cancer epidemiology simulation model: An update”, Medical Decision Making, 2018.

  6. M. Cevik, M. Ergun, N. Stout, A. Trentham-Dietz, M. Craven, O. Alagoz, “Using active learning for speeding up calibration in simulation models”, Medical Decision Making, 2016.

  7. B. Sprague, N. Stout, C. Schechter, N. Van Ravestayn, M. Cevik, O. Alagoz, C. Lee, J. Van Den Broek, D. Miglioretti, J. Mandelblatt, H. De Koning, K. Kerlikowske, C. Lehman, A. Tosteson, “Benefits, harms, and cost-effectiveness of supplemental ultrasonography screening for women with dense breasts”, Annals of Internal Medicine, 2015.

  8. C. Lee, M. Cevik, O. Alagoz, B. Sprague, A. Tosteson, D. Miglioretti, K. Kerlikowske, N. Stout, J. Jarvik, S. Ramsey, C. Lehman, “Comparative effectiveness of combined digital mammography and tomosynthesis screening for women with dense breasts”, Radiology, 2014.

  9. N. Stout, S. Lee, C. Schechter, K. Kerlikowske, O. Alagoz, D. Berry, D. Buist, M. Cevik, G. Chisholm, H. De Koning, H. Huang, R. Hubbard, D. Miglioretti, M. Munsell, A. Trentham-Dietz, N. Van Ravesteyn, A. Tosteson, J. Mandelblatt, “Benefits, harms, and costs for breast cancer screening after US implementation of digital mammography,” Journal of National Cancer Institute, 2014.

  10. Z. C. Taşkın, and M. Cevik, “Combinatorial Benders Cuts for Decomposing IMRT Fluence Maps Using Rectangular Apertures”, Computers and Operations Research, 40:2178-2186, 2013.

Conference Papers

  1. H. Jahanshahi, D. Jothimani, A. Başar, M. Cevik, “Does chronology matter in JIT defect prediction?: A Partial Replication Study”, PROMISE’19, pages 90-99, 2019.

Working Papers

Teaching

Ryerson University

  • DS 8002: Machine Learning, Fall 2019.

  • DS 8004: Data Mining, Winter 2020.

  • IND 405: Introduction to Data Analytics, Fall 2019.

  • IND 300: Introduction to Management, Winter 2019.

  • IND 708: Information Systems, Fall 2018.

University of Toronto

  • MIE 1605: Stochastic Process, Fall 2017.

University of Wisconsin - Madison

  • ISyE 620: Simulation Modeling and Analysis, Summer 2014.

Links