EDUCATION
RESEARCH INTERESTS
- Methodologies: Applied Machine Learning, Reinforcement Learning, Stochastic Modeling and Simulation, Integer Programming
- Applications: Healthcare, Transportation, Software Engineering
JOURNAL PAPERS
- A unified framework for financial commentary prediction
O. Ozyegen, G. Malik, M. Cevik, K. Ioi, K. El Mokhtari
Information Technology and Management (2024)
- Approximate dynamic programming for pickup and delivery problem with crowd-shipping
K. Mousavi, M. Bodur, M. Cevik, M. Roorda
Transportation Research Part B: Methodological (2024)
- Optimizing electricity peak shaving through stochastic programming and probabilistic time series forecasting
S. Rafayal, A. Alnaggar, M. Cevik
Journal of Building Engineering (2024)
- Game‐theoretic approaches to product introduction strategies for durable products
D. Pirayesh Neghab, J. Restrepo Diaz, M. Cevik, M.I.M. Wahab
Managerial and Decision Economics (2024)
- Explaining Exchange Rate Forecasts with Macroeconomic Fundamentals Using Interpretive Machine Learning
D. Pirayesh Neghab, M. Cevik, M.I.M. Wahab, A. Basar
Computational Economics (2024)
- Multistage stochastic fractionated intensity modulated radiation therapy planning
M. Bodur , M. Cevik, A. Cire, M. Ruschin, J. Wang
Computers and Operations Research (2023)
- Sequence labeling for disambiguating medical abbreviations
M. Cevik, S. Mohammadjafari, M. Myers, S. Yildirim
Journal of Healthcare Informatics Research (2023)
- ADPTriage: Approximate dynamic programming for bug triage
H. Jahanshahi, M. Cevik, K. Mousavi, A. Basar
IEEE Transactions on Software Engineering (2023)
- Improved alpha-GAN architecture for generating 3D connected volumes with an application to radiosurgery treatment planning
S. Mohammadjafari, M. Cevik, A. Basar
Applied Intelligence (2023)
- A multiobjective constrained POMDP model for breast cancer screening
R. Helmeczi, C. Kavaklioglu, M. Cevik, D. Pirayesh Neghab
Operational Research (2023)
- Linear programming-based solution methods for constrained POMDPs
R. Helmeczi, C. Kavaklioglu, M. Cevik
Applied Intelligence (2023)
- SDABT: A schedule and dependency-aware bug triaging method
H. Jahanshahi, M. Cevik
Information and Software Technology (2022)
- Multiobjective optimization approaches for sector duration optimization problem in radiosurgery [link]
O. Seker, M. Cevik, M. Bodur, Y. Lee, M. Ruschin
INFORMS Journal on Computing (2022)
- Auto response generation in online medical chat services
H. Jahanshahi, S. Kazmi, M. Cevik
Journal of Healthcare Informatics Research (2022)
- Active learning for multi-way sensitivity analysis with application to disease screening modeling
M. Cevik, S. Angco, E. Heydari, H. Jahanshahi, N. Prayogo
Journal of Healthcare Informatics Research (2022)
- Word-level text highlighting of medical texts for telehealth services
O. Ozyegen, D. Kabe, M. Cevik
Artificial Intelligence in Medicine (2022)
- Wayback machine: Capturing the evolutionary behaviour of the bug dependency graph in open-source software systems
H. Jahanshahi, M. Cevik, J. Navas-Su, A. Basar, A. Gonzales-Torres
Journal of Systems and Software (2022)
- A deep reinforcement learning approach for the meal delivery problem
H. Jahanshahi, A. Bozanta, M. Cevik, E. Kavuk, A. Tosun, S. Sonuc, A. Basar
Knowledge-Based Systems (2022)
- VARGAN: Variance enforcing network enhanced GAN
S. Mohammadjafari, M. Cevik, A. Basar
Applied Intelligence (2022)
- Classifying multi-level product categories using dynamic masking and transformer models
O. Ozyegen, H. Jahanshahi, M. Cevik, B. Bulut, D. Yigit, F. Gonen, A. Basar
Journal of Data, Information and Management (2022)
- An empirical study on using CNNs for fast radio signal prediction
O. Ozyegen, S. Mohammadjafari, M. Cevik, Karim El mokhtari, J. Ethier, A. Basar
SN Computer Science (2022)
- Scalable grid-based approximation algorithms for POMDPs
C. Kavaklioglu, M. Cevik
Concurrency and Computation: Practice and Experience (2021)
- Courier routing optimization for food delivery service using reinforcement learning
A. Bozanta, M. Cevik, C. Kavaklioglu, E. Kavuk, A. Tosun, S. Sonuc, A. Duranel, A. Basar
Computers and Industrial Engineering (2021)
- On the impact of deep learning-based time-series forecasts on multistage stochastic programming policies
J. Wang, M. Cevik, M. Bodur
INFOR: Information Systems and Operational Research (2021)
- Evaluation of local explanation methods for multivariate time series forecasting
O. Ozyegen, I. Ilic, M. Cevik
Applied Intelligence (2021)
- A replication study on implicit feedback recommender systems with application to the data visualization recommendation
P. Lak, A. Bozanta, C. Kavaklioglu, M. Cevik, A. Basar, M. Petitclerc, G. Wills
Expert Systems (2021)
- Order dispatching for an ultra-fast delivery service via deep reinforcement learning
E. Kavuk, A. Tosun, M. Cevik, A. Bozanta, S. Sonuc, A. Duranel, M. Tutuncu, A. Basar
Applied Intelligence (2021)
- Explainable boosted linear regression for time series forecasting
I. Ilic, B. Gorgulu, M. Cevik, M. Baydogan
Pattern Recognition (2021)
- Mixed-integer linear programming models for the paint waste management problem
J. Wang, M. Cevik, S. Amin, A Parsaee
Transportation Research Part E (2021)
- Designing mm-wave electromagnetic engineered surfaces using generative adversarial networks
S. Mohammadjafari, O. Ozyegen, M. Cevik, E. Kavurmacioglu, J. Ethier, A. Basar
Neural Computing and Applications (2020)
- Machine learning-based radio coverage prediction in urban environments [link]
S. Mohammadjafari, S. Roginsky, E. Kavurmacioglu, M. Cevik, J. Ethier, A. Basar
IEEE Transactions on Network and Service Management (2020)
- Analyzing intracranial EEG in pharmacoresistant epilepsy patients using hidden Markov models and time series forecasting methods [link]
A. Bhowmick, M. Cevik, A. Basar
SN Computer Science (2020)
- Knowledge-based isocenter selection in radiosurgery planning [link]
A. Berdyshev, M. Cevik, D. Aleman, H. Nordstrom, S. Riad, Y. Lee, A. Saghal, M. Ruschin
Medical Physics (2020)
- Simultaneous optimization of isocenter locations and sector duration in radiosurgery [link]
M. Cevik, D. Aleman, Y. Lee, A. Berdyshev, H. Nordstrom, S. Riad, A. Sahgal, M. Ruschin
Physics in Medicine & Biology (2019)
- Modeling and comparison of alternative approaches for sector duration optimization in a dedicated radiosurgery system [link]
M. Cevik, P. Shirvani Ghomi, D. Aleman, Y. Lee, A. Berdyshev, H. Nordstrom, S. Riad, A. Sahgal, M. Ruschin
Physics in Medicine & Biology (2018)
- Analysis of mammography screening policies under resource constraints [link]
M. Cevik, T. Ayer, O. Alagoz, B. Sprague
Production and Operations Management (2018)
- Comparing CISNET breast cancer models using the maximum clinical incidence reduction methodology [link]
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
Medical Decision Making (2018)
- The University of Wisconsin breast cancer epidemiology simulation model: An update [link]
O. Alagoz, M. Ergun, M. Cevik, B. Sprague, D. Fryback, R. Gangnon, J. Hampton, N. Stout, A. Trentham-Dietz
Medical Decision Making (2018)
- Using active learning for speeding up calibration in simulation models [link]
M. Cevik, M. Ergun, N. Stout, A. Trentham-Dietz, M. Craven, O. Alagoz
Medical Decision Making (2016)
- Benefits, harms, and cost-effectiveness of supplemental ultrasonography screening for women with dense breasts [link]
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
Annals of Internal Medicine (2015)
- Comparative effectiveness of combined digital mammography and tomosynthesis screening for women with dense breasts [link]
C. Lee, M. Cevik, O. Alagoz, B. Sprague, A. Tosteson, D. Miglioretti, K. Kerlikowske, N. Stout, J. Jarvik, S. Ramsey, C. Lehman
Radiology (2014)
- Benefits, harms, and costs for breast cancer screening after US implementation of digital mammography [link]
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
Journal of National Cancer Institute (2014)
- Combinatorial Benders cuts for decomposing IMRT fluence maps using rectangular apertures [link]
Z. C. Taşkın, M. Cevik
Computers and Operations Research (2013)
PEER REVIEWED CONFERENCE PAPERS
- Transformer-based Text Highlighting for Medical Terms
L. Ozyegen, M. Cevik, A. Basar
Proceedings of the 34th Annual International Conference on Computer Science and Software Engineering (2024)
- Exploring Large Language Models for Automated Essay Grading in Finance Domain
G. Malik, M. Cevik, S. Lee
Proceedings of the 34th Annual International Conference on Computer Science and Software Engineering (2024)
- Machine Learning-based Control of Dual-Sourcing Inventory Systems
D. Pirayesh Neghab, S. Li, M. Cevik, M.I.M. Wahab
Proceedings of the 34th Annual International Conference on Computer Science and Software Engineering (2024)
- Anaphora Resolution in Software Requirements Engineering: A Comparison of Generative NLP Pipelines and Encoder-Based Models
G. Malik, S. Yildirim, M. Cevik, A. Basar
Proceedings of the 34th Annual International Conference on Computer Science and Software Engineering (2024)
- Interpreting time series forecasting models using model class reliance
S. Berry, M. Cevik, O. Ozyegen
Proceedings of the 37th Canadian Conference on AI (2024)
- Anaphoric Ambiguity Resolution in Software Requirement Texts
S. Mohammadjafari, S. Yildirim, M. Cevik, A. Basar
Proceedings of the IEEE International Conference on Big Data (2023)
- Few-shot learning approaches to software requirement quality prediction
S. Yildirim, M. Cevik, A. Basar
Proceedings of the 33rd Annual International Conference on Computer Science and Software Engineering (2023)
- Data augmentation for conflict and duplicate detection in software engineering sentence pairs
G. Malik, M. Cevik, A. Basar
Proceedings of the 33rd Annual International Conference on Computer Science and Software Engineering (2023)
- Few-shot learning approaches to essay scoring
R. Helmeczi, S. Yildirim, M. Cevik, S. Lee
Proceedings of the 36th Canadian Conference on AI (2023)
- An empirical study on vagueness detection in privacy policy texts
G. Malik, S. Yildirim, M. Cevik, A. Basar
Proceedings of the 36th Canadian Conference on AI (2023)
- Identifying the factors influencing IPO underpricing using explainable machine learning techniques
D. Pirayesh Neghab, M. Cevik, A. Basar
Proceedings of the 36th Canadian Conference on AI (2023)
- A prompt-based few-shot learning approach to software conflict detection
R. Helmeczi, M. Cevik, S. Yildirim
Proceedings of the 32nd Annual International Conference on Computer Science and Software Engineering (2022)
- Time series forecasting-based peak shaving for building energy management
S. Rafayal, M. Cevik
Proceedings of the 32nd Annual International Conference on Computer Science and Software Engineering (2022)
- Partially observable Markov chain models for evaluating lung cancer screening policies
N. Prayogo, S. Rafayal, D. Pirayesh Neghab, M. Cevik
Proceedings of the 32nd Annual International Conference on Computer Science and Software Engineering (2022)
- An empirical study on probabilistic forecasting for predicting city-wide electricity consumption
S. Rafayal, M. Cevik, D. Kici
Proceedings of the 35th Canadian Conference on AI (2022)
- Software requirement specific entity extraction using transformer models
G. Malik, M. Cevik, S. Bera, S. Yildirim, D. Parikh, A. Basar
Proceedings of the 35th Canadian Conference on AI (2022)
- Text classification for predicting multi-level product categories
H. Jahanshahi, O. Ozyegen, M. Cevik, B. Bulut, D. Yigit, F. Gonen, A. Basar
Proceedings of the 31st Annual International Conference on Computer Science and Software Engineering (2021)
- Time series forecasting for patient arrivals in online health services
S. Kazmi, A. Bozanta, M. Cevik
Proceedings of the 31st Annual International Conference on Computer Science and Software Engineering (2021)
- Text classification on software requirements specifications using transformer models
D. Kici, A. Bozanta, M. Cevik, D. Parikh, A. Basar
Proceedings of the 31st Annual International Conference on Computer Science and Software Engineering (2021)
- Sentiment analysis of stockTwits using transformer models
A. Bozanta, S. Angco, M. Cevik, A. Basar
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications (2021)
- Using ProtoPNet for interpretable Alzheimer’s disease classification
S. Mohammadjafari, M. Thanabalasingam, M. Cevik, A. Basar
Proceedings of the 34th Canadian Conference on AI (2021)
- Named entity recognition on software requirements specification documents
G. Malik, Y. Khedr, M. Cevik, D. Parikh, A. Basar
Proceedings of the 34th Canadian Conference on AI (2021)
- A BERT-based transfer learning approach to text classification on software requirements specifications
D. Kici, G. Malik, M. Cevik, D. Parikh, A. Basar
Proceedings of the 34th Canadian Conference on AI (2021)
- DABT: A dependency-aware bug triaging method [link]
H. Jahanshahi, K. Chhabra, M. Cevik, A. Basar
Proceedings of the EASE 2021 (2021)
- Moving from cross-project just-in-time defect prediction to heterogeneous just-in-time defect prediction: An extended replication study [link]
H. Jahanshahi, M. Cevik, A. Basar
Proceedings of the 30th Annual International Conference on Computer Science and Software Engineering (2020)
- Deep learning approaches to classify the relevance and sentiment of news articles to the economy
J. Wang, A. Bhowmick, M. Cevik, A. Basar
Proceedings of the 30th Annual International Conference on Computer Science and Software Engineering (2020).
- Time series sampling for probabilistic forecasting [link]
N. Prayogo, M. Cevik, M. Bodur
Proceedings of the 30th Annual International Conference on Computer Science and Software Engineering (2020)
- Value of MRI and ultrasound screening for breast cancer in non-high-risk population [link]
B. Sandikci, M. Cevik
Proceedings of the Global Joint Conference on Industrial Engineering and Its Application Areas (GJCIE) (2020).
- Predicting the number of reported bugs in a software repository
H. Jahanshahi, M. Cevik, A. Basar
Proceedings of the 33rd Canadian Conference on AI (2020)
- Using topic modelling to improve prediction of financial report commentary classes
K. El mokhtari, M. Cevik, A. Basar
Proceedings of the 33rd Canadian Conference on AI, pages 201-207 (2020)
- Augmented out-of-sample comparison method for time series forecasting techniques [link]
I. Ilic, B. Gorgulu, M. Cevik
Proceedings of the 33rd Canadian Conference on AI, pages 302-308 (2020)
- Does chronology matter in JIT defect prediction?: A Partial Replication Study [link]
H. Jahanshahi, D. Jothimani, A. Başar, M. Cevik
Proceedings of the PROMISE’19, pages 90-99 (2019)
PREPRINTS
- Screening for breast cancer: The role of supplemental tests and breast density information [link]
B. Sandikci, M. Cevik, D. Schacht
Working paper (2018)
TEACHING
Toronto Metropolitan University
- DS 8001: Design of Algorithms (Fall 2020, Fall 2021, Fall 2022, Fall 2023, Fall 2024)
- DS 8007: Advanced Data Visualization (Fall 2024)
- DS 8013: Deep Learning (Winter 2024)
- DS 8004: Data Mining (Winter 2020, Winter 2021, Winter 2022, Winter 2023)
- DS 8010: Interactive Learning in Decision Process (Winter 2021, Winter 2022, Winter 2023)
- DS 8002: Machine Learning (Fall 2019)
- IND 405: Introduction to Data Analytics (Fall 2019)
- IND 300: Introduction to Management (Winter 2019)
- IND 708: Information Systems (Fall 2018, Fall 2024)
University of Toronto
- MIE 1605: Stochastic Process (Fall 2017)
University of Wisconsin - Madison
- ISyE 620: Simulation Modeling and Analysis (Summer 2014)