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Dr. Ayşe Başar

Ayşe Başar
Graduate Program Director, Data Science and Analytics
BSc, MASc, PhD
416-979-5000 ext. 553155

Areas of Academic Interest

Machine learning

Bayesian inference

Recommender systems


Year University Degree
2000 London School of Economics PhD
1988 University of Alabama in Huntsville MASc
1986 Boğaziçi University BSc

Selected Courses

Course Code Course
DS8002 Machine Learning
IND 405 Introduction to Data Science and Analytics


What does it take to train a machine to think? If you are Ayşe Başar, it isn’t just a relentless drive, years of research into AI and machine learning, and more than a decade of experience working in industry. Building predictive models also relies on an ability to step into someone’s shoes. “To translate what an expert does into mathematics and code, we basically role-play their experiences to understand how they think,” she says.

One such instance came while Başar and her team were building an AI system intended to improve the capacity for emergency room teams at St. Michael’s Hospital. The team’s goal was to assess whether a patient should be discharged or stay in hospital. Once a preliminary model was in place, Başar’s team spent a morning in the ER being trained alongside a group of medical students, ordering tests, looking at patient histories and talking with a patient recovering from surgery. “Being immersed in their world was fascinating and incredibly helpful in modifying our models to think more effectively,” she says.

Ayse Bener

“With every project, I learn something new that enables me to look at things from a different angle.”

  • Paper among top 3 most cited articles in Empirical Software Engineering Journal in five-year period after publication (2009-14): B. Turhan, T. Menzies, A. Bener and J. Distefano. “On the Relative Value of Cross-Company and Within-Company Data for Defect Prediction.” Empirical Software Engineering Journal, Vol. 14, no. 5, 2009, pp. 540-578.
  • Best Paper Award: A. Tosun, A. Bener, and R. Kale. “AI Based Defect Predictors: Applications and Benefits in a Case Study.” (AAAI), 2010.
  • Best Paper Award: Mohammadjafari, S., Kavurmacioglu, E., Maidens, J., and Bener, A. “Neural Network Based Spectrum Prediction in Land Mobile Radio Bands for IoT deployments.” IFIP/IEEE Symposium on Integrated Network and Service Management (IM), 2019, pp. 31-36.
  • Best Paper Award: G. Calikli, A. Bener, T. Aytac, and O. Bozcan. “Towards a Metric Suite Proposal to Quantify Confirmation Biases of Developers.” (ESEM), 2013.
  • S. Young, T. Abdou, A. Bener. “Deep Super Learner: A Deep Ensemble for Classification Problems.” Canadian AI Conference, Toronto, May 9, 2018.
  • M. Habayeb, S.S. Murtaza, A. Miranskyy, and A.B. Bener. “On the Use of Hidden Markov Model to Predict the Time to Fix Bugs.” IEEE Transactions on Software Engineering, 10.1109/TSE.2017.2757480, 2017.
  • A.B. Fecso, S.S. Kuzulugil, C. Babaoglu, A.B. Bener, and T.P. Grantcharov. “Studying the Interactions Between Teams and Individuals in the Operating Room: A Pilot Study.” Journal of the American College of Surgeons, vol. 225, no. 4, 2017, S181.
  • A.B. Bener, B. Caglayan, A.D. Henry, and P. Praat. “Empirical Models of Social Learning in a Huge, Evolving Network.” PLOS One, vol. 11, no. 10, 2016, e0160307.
  • A.T. Misirli, and A.B. Bener. “Bayesian Networks for Evidence-Based Decision-making in Software Engineering.” IEEE Transactions on Software Engineering, vol. 40, no. 6, 2014, 533-554.
  • Data Science Lab
  • Program director, Certificate in Data Analytics, Big Data, and Predictive Analytics
  • Affiliated scientist, St. Michael’s Hospital
  • Research fellow, IBM CAS
  • Director, Big Data, Office of the Provost and Vice President Academic
  • Senior member, IEEE
  • Associate editor, IEEE Transactions on Big Data
  • Editorial board member, Software Quality Journal
  • General chair, ESEIW 2017
  • Board member, IEEE Software
  • Board member, IEEE Publications