Information for Prospective PhD Students who want to conduct research under my supervision

Graduate students who wish to work with me can be enrolled in either the school of Engineering Science, the school of Computer Science, or Applied Mathematics. Application deadlines are February 1 for the Fall semester, and August 1 for the Spring semester.

Funding

Ph.D. students are funded from one of the available research assistantships. There is also the possibility of additional fellowships from internal awards as well as external awards and departmental teaching assistantships. NSERC, CIHR and MSFHR offer awards for outstanding Canadian students at the graduate level. Student registered full-time for graduate studies at SFU can apply for the BC-IIS awards. Students are typically expected to work 40 hours/week on their research. The academic setting offers considerable flexibility; graduate students are given increasing responsibility to self-manage their time and deadlines efficiently.

Coursework 

As an overview, PhD students in Engineering Science are required to take six graduate level courses with flexibility in the choice of these courses to cater to their research interest. Students in the doctoral program in CS are required to take 8 courses spread over three areas: Area 1: Formal topics in Computing Science, Area 2: Computer Systems, and Area 3: Knowledge and Information Systems. Check here for course requirements in Applied Mathematics.

Relevant Graduate courses in the School of Engineering Science:

  1. ENSC 801 - Linear System Theory
  2. ENSC 802 - Stochastic Processes
  3. ENSC 810 - Statistical Signal Processing
  4. ENSC 815 -  Multirate Signal Processing
  5. ENSC 883 - Optimal Control Theory
  6. ENSC 888 - Finite Element Methods in Engineering
  7. ENSC 894 - Computational Anatomy and Medical Image Analysis.

Relevant Graduate courses in Applied Mathematics:

  1. MATH 709-3 - Numerical Linear Algebra and Optimization
  2. MATH 716-3 - Numerical Analysis II
  3. MATH 718-3 - Partial Differential Equations
  4. MATH 719-3 - Linear Analysis
  5. MATH 724-3 - Applications of Complex Analysis
  6. MATH 725-3 - Real Analysis
  7. MATH 761-3 - Continuous Mathematical Models
  8. MATH 762-3 - Fluid Dynamics
  9. MATH 767-3 - Dynamical Systems
  10. MATH 770-3 - Variational Calculus

Relevant Courses in Statistics:

  1. STAT-460 Bayesian Statistics
  2. STAT-602 Generalized Linear and Nonlinear Modelling
  3. STAT-801 Statistics
  4. STAT-802 Multivariate Analysis
  5. STAT-804 Time Series Analysis
  6. STAT-805 Non-Parametric Statistics and Discrete Data Analysis
  7. STAT-806 Lifetime Data Analysis

Relevant Graduate courses in the School of Computer Science:

  1. CMPT 720-3 Artificial Intelligence
  2. CMPT 705-3 Design and Analysis of Algorithms
  3. CMPT 706-3 Parallel Algorithms
  4. CMPT 770-3 Computer Graphics
  5. CMPT 775-3 Scientific Visualization
  6. CMPT 815-3 Algorithms of Optimization
  7. CMPT 822-3 Computational Vision
  8. CMPT 880-3 Special Topics in Medical Image Analysis

 

Collaborations

Graduate students under my supervision will have the opportunity to engage in collaborative research with the Johns Hopkins University, the National Institutes of Health, Washington University, St. Louis, University of New South Wales, Australia, and University of British Columbia. Opportunities for travel to present talks at international conferences will likely be available.

Social Scene

Vancouver is considered one of the best cities in the world to live in. There are ample recreational opportunities in the city as well as outdoor adventure activities such as hiking and skiing.

Questions

For any additional information or if you have any queries, please feel free to email me at mfbeg. at. ensc. sfu. ca. I look forward to hear from you.