Barry Po
Job Title
Senior Director, Product & Business Development
Employer
NGRAIN
Canadian Immigration Updates
Review details about the recently announced changes to study and work permits that apply to master’s and doctoral degree students. Read more
Overview
PhD students in the Department of Computer Science may focus their research in the following areas:
- Artificial Intelligence: computer vision, decision theory/game theory, knowledge representation and reasoning, intelligent user interfaces, machine learning, natural language understanding and generation, robotics and haptics.
- Computer Graphics: animation, imaging, modeling, rendering, visualization.
- Data Management and Mining: business intelligence, data integration, genomic analysis, text mining, web databases.
- Formal Verification and Analysis of Systems: analog, digital and hybrid systems, VLSI, protocols, software.
- Human Centered Technologies: human computer interaction (HCI), visual, haptic and multimodal interfaces, computer-supported cooperative work (CSCW), visual analytics.
- Networks, Systems, and Security: high performance computing/parallel processing, networking, operating systems and virtualization, security.
- Scientific Computing: numerical methods and software, differential equations, linear algebra, optimization.
- Software Engineering and Programming Languages: development tools, foundations of computation, middleware, programming languages, software engineering.
- Theory: algorithm design and analysis (including empirical), algorithmic game theory, discrete optimization, graph theory, computational geometry
What makes the program unique?
The UBC Department of Computer Science has many contacts in the computing industry. A strong rapport between the industry and research communities is beneficial to both, especially in cases where the department focuses its research to developing real-world applications.
Quick Facts
Program Enquiries
Still have questions after reviewing this page thoroughly?
Contact the program
Contact the program
Admission Information & Requirements
1) Check Eligibility
Minimum Academic Requirements
The Faculty of Graduate and Postdoctoral Studies establishes the minimum admission requirements common to all applicants, usually a minimum overall average in the B+ range (76% at UBC). The graduate program that you are applying to may have additional requirements. Please review the specific requirements for applicants with credentials from institutions in:
Each program may set higher academic minimum requirements. Please review the program website carefully to understand the program requirements. Meeting the minimum requirements does not guarantee admission as it is a competitive process.
English Language Test
Applicants from a university outside Canada in which English is not the primary language of instruction must provide results of an English language proficiency examination as part of their application. Tests must have been taken within the last 24 months at the time of submission of your application.
Minimum requirements for the two most common English language proficiency tests to apply to this program are listed below:
TOEFL: Test of English as a Foreign Language - internet-based
Overall score requirement: 100
Reading
22
Writing
21
Speaking
21
Listening
22
IELTS: International English Language Testing System
Overall score requirement: 7.0
Reading
6.5
Writing
6.5
Speaking
6.5
Listening
6.5
Other Test Scores
Some programs require additional test scores such as the Graduate Record Examination (GRE) or the Graduate Management Test (GMAT). The requirements for this program are:
The GRE is not required.
2) Meet Deadlines
Application open dates and deadlines for an upcoming intake have not yet been configured in the admissions system. Please check back later.
3) Prepare Application
Transcripts
All applicants have to submit transcripts from all past post-secondary study. Document submission requirements depend on whether your institution of study is within Canada or outside of Canada.
Letters of Reference
A minimum of three references are required for application to graduate programs at UBC. References should be requested from individuals who are prepared to provide a report on your academic ability and qualifications.
Statement of Interest
Many programs require a statement of interest, sometimes called a "statement of intent", "description of research interests" or something similar.
Supervision
Students in research-based programs usually require a faculty member to function as their thesis supervisor. Please follow the instructions provided by each program whether applicants should contact faculty members.
Instructions regarding thesis supervisor contact for Doctor of Philosophy in Computer Science (PhD)
Applicants should browse faculty profiles and indicate in their application who they are interested in working with. No commitment from a supervisor prior to applying is necessary, but contacting faculty members is encouraged.
Citizenship Verification
Permanent Residents of Canada must provide a clear photocopy of both sides of the Permanent Resident card.
4) Apply Online
All applicants must complete an online application form and pay the application fee to be considered for admission to UBC.
Tuition & Financial Support
Tuition
| Fees | Canadian Citizen / Permanent Resident / Refugee / Diplomat | International |
|---|---|---|
| Application Fee | $116.25 | $168.25 |
| Tuition * | ||
| Installments per year | 3 | 3 |
| Tuition per installment | $1,875.34 | $3,294.66 |
| Tuition per year (plus annual increase, usually 2%-5%) | $5,626.02 | $9,883.98 |
| Int. Tuition Award (ITA) per year (if eligible) | $3,200.00 (-) | |
| Other Fees and Costs | ||
| Student Fees (yearly) | $1,144.10 (approx.) | |
| Costs of living | Estimate your costs of living with our interactive tool in order to start developing a financial plan for your graduate studies. | |
* Regular, full-time tuition. For on-leave, extension, continuing or part time (if applicable) fees see UBC Calendar.
All fees for the year are subject to adjustment and UBC reserves the right to change any fees without notice at any time, including tuition and student fees. Tuition fees are reviewed annually by the UBC Board of Governors. In recent years, tuition increases have been 2% for continuing domestic students and between 2% and 5% for continuing international students. New students may see higher increases in tuition. Admitted students who defer their admission are subject to the potentially higher tuition fees for incoming students effective at the later program start date. In case of a discrepancy between this webpage and the UBC Calendar, the UBC Calendar entry will be held to be correct.
All fees for the year are subject to adjustment and UBC reserves the right to change any fees without notice at any time, including tuition and student fees. Tuition fees are reviewed annually by the UBC Board of Governors. In recent years, tuition increases have been 2% for continuing domestic students and between 2% and 5% for continuing international students. New students may see higher increases in tuition. Admitted students who defer their admission are subject to the potentially higher tuition fees for incoming students effective at the later program start date. In case of a discrepancy between this webpage and the UBC Calendar, the UBC Calendar entry will be held to be correct.
Financial Support
Applicants to UBC have access to a variety of funding options, including merit-based (i.e. based on your academic performance) and need-based (i.e. based on your financial situation) opportunities.
Program Funding Packages
All full-time PhD students will be provided with a funding package of at least $33,612 for each of the first four years of their PhD program. The funding package consists of any combination of internal or external awards, teaching-related work, research assistantships, and graduate academic assistantships. This support is contingent on full-time registration as a UBC Graduate student, satisfactory performance in assigned teaching and research assistantship duties, and good standing with satisfactory progress in your academic performance. CS students are expected to apply for fellowships or scholarship to which they are eligible.
Average Funding
Based on the criteria outlined below, 82 students within this program were included in this study because they received funding through UBC in the form of teaching, research, academic assistantships or internal or external awards averaging $37,326.
- 40 students received Teaching Assistantships. Average TA funding based on 40 students was $6,950.
- 77 students received Research Assistantships. Average RA funding based on 77 students was $20,513.
- 18 students received Academic Assistantships. Average AA funding based on 18 students was $6,167.
- 81 students received internal awards. Average internal award funding based on 81 students was $11,015.
- 8 students received external awards. Average external award funding based on 8 students was $19,625.
Study Period: Sep 2022 to Aug 2023 - average funding for full-time PhD students enrolled in three terms per academic year in this program across years 1-4, the period covered by UBC's Minimum Funding Guarantee. Averages might mask variability in sources and amounts of funding received by individual students. Beyond year 4, funding packages become even more individualized.
Review methodology
Review methodology
Scholarships & awards (merit-based funding)
All applicants are encouraged to review the awards listing to identify potential opportunities to fund their graduate education. The database lists merit-based scholarships and awards and allows for filtering by various criteria, such as domestic vs. international or degree level.
Graduate Research Assistantships (GRA)
Many professors are able to provide Research Assistantships (GRA) from their research grants to support full-time graduate students studying under their supervision. The duties constitute part of the student's graduate degree requirements. A Graduate Research Assistantship is considered a form of fellowship for a period of graduate study and is therefore not covered by a collective agreement. Stipends vary widely, and are dependent on the field of study and the type of research grant from which the assistantship is being funded.
Graduate Teaching Assistantships (GTA)
Graduate programs may have Teaching Assistantships available for registered full-time graduate students. Full teaching assistantships involve 12 hours work per week in preparation, lecturing, or laboratory instruction although many graduate programs offer partial TA appointments at less than 12 hours per week. Teaching assistantship rates are set by collective bargaining between the University and the Teaching Assistants' Union.
Graduate Academic Assistantships (GAA)
Academic Assistantships are employment opportunities to perform work that is relevant to the university or to an individual faculty member, but not to support the student’s graduate research and thesis. Wages are considered regular earnings and when paid monthly, include vacation pay.
Financial aid (need-based funding)
Canadian and US applicants may qualify for governmental loans to finance their studies. Please review eligibility and types of loans.
All students may be able to access private sector or bank loans.
Foreign government scholarships
Many foreign governments provide support to their citizens in pursuing education abroad. International applicants should check the various governmental resources in their home country, such as the Department of Education, for available scholarships.
Working while studying
The possibility to pursue work to supplement income may depend on the demands the program has on students. It should be carefully weighed if work leads to prolonged program durations or whether work placements can be meaningfully embedded into a program.
International students enrolled as full-time students with a valid study permit can work on campus for unlimited hours and work off-campus for no more than 24 hours a week during academic sessions.
A good starting point to explore student jobs is the UBC Work Learn program or a Co-Op placement.
Tax credits and RRSP withdrawals
Students with taxable income in Canada may be able to claim federal or provincial tax credits.
Canadian residents with RRSP accounts may be able to use the Lifelong Learning Plan (LLP) which allows students to withdraw amounts from their registered retirement savings plan (RRSPs) to finance full-time training or education for themselves or their partner.
Please review Filing taxes in Canada on the student services website for more information.
Cost Estimator
Applicants have access to the cost estimator to develop a financial plan that takes into account various income sources and expenses.
Career Outcomes
111 students graduated between 2005 and 2013. Of these, career information was obtained for 106 alumni (based on research conducted between Feb-May 2016):
RI (Research-Intensive) Faculty: typically tenure-track faculty positions (equivalent of the North American Assistant Professor, Associate Professor, and Professor positions) in PhD-granting institutions
TI (Teaching-Intensive) Faculty: typically full-time faculty positions in colleges or in institutions not granting PhDs, and teaching faculty at PhD-granting institutions
Term Faculty: faculty in term appointments (e.g. sessional lecturers, visiting assistant professors, etc.)
Sample Employers in Higher Education
University of British Columbia (5)McGill University (3)
University of Waterloo (3)
University of Manitoba (2)
Swansea University
Stanford University
University of Utah
Ecole Polytechnique Federale de Lausanne (EPFL)
Swiss Federal Institute of Technology
University of Saskatchewan
Sample Employers Outside Higher Education
Google (12)Microsoft (4)
Amazon (3)
Intel Corporation (3)
Disney (2)
Oracle Labs (2)
IBM (2)
Tasktop Technologies (2)
Tableau (2)
OriGene Technologies Inc.
Sample Job Titles Outside Higher Education
Research Scientist (5)Software Engineer (5)
Senior Software Engineer (4)
Chief Technology Officer (3)
Product Manager (3)
Software Development Engineer (2)
Senior Data Scientist (2)
Senior Research Engineer (2)
Advisory Engineer
Senior Research Scientist
PhD Career Outcome Survey
You may view the full report on career outcomes of UBC PhD graduates on outcomes.grad.ubc.ca.Disclaimer
These data represent historical employment information and do not guarantee future employment prospects for graduates of this program. They are for informational purposes only. Data were collected through either alumni surveys or internet research.Enrolment, Duration & Other Stats
These statistics show data for the Doctor of Philosophy in Computer Science (PhD). Data are separated for each degree program combination. You may view data for other degree options in the respective program profile.
ENROLMENT DATA
| 2023 | 2022 | 2021 | 2020 | 2019 | |
|---|---|---|---|---|---|
| Applications | 281 | 265 | 375 | 299 | 278 |
| Offers | 31 | 40 | 41 | 45 | 26 |
| New Registrations | 14 | 15 | 20 | 20 | 16 |
| Total Enrolment | 129 | 124 | 116 | 98 | 81 |
Completion Rates & Times
This program has a graduation rate of 63% based on 60 students admitted between 2011 - 2014. Based on 28 graduations between 2020 - 2023 the minimum time to completion is 2.73 years and the maximum time is 11.15 years with an average of 5.74 years of study. All calculations exclude leave times.
Disclaimer
Admissions data refer to all UBC Vancouver applications, offers, new registrants for each registration year, May to April, e.g. data for 2022 refers to programs starting in 2022 Summer and 2022 Winter session, i.e. May 1, 2022 to April 30, 2023. Data on total enrolment reflects enrolment in Winter Session Term 1 and are based on snapshots taken on November 1 of each registration year. Program completion data are only provided for datasets comprised of more than 4 individuals. Graduation rates exclude students who transfer out of their programs. Rates and times of completion depend on a number of variables (e.g. curriculum requirements, student funding), some of which may have changed in recent years for some programs.
Upcoming Doctoral Exams
Thursday, 10 April 2025 - 9:00am - X836, ICICS, 2366 Main Mall
Vasileios Lioutas
Towards Realistic Controllable Driving Simulators
Thursday, 29 May 2025 - 12:30pm - X836, ICICS, 2366 Main Mall
Dujian Ding
Towards Efficient Machine Learning Management Systems
Research Supervisors
Supervision
Students in research-based programs usually require a faculty member to function as their thesis supervisor. Please follow the instructions provided by each program whether applicants should contact faculty members.
Instructions regarding thesis supervisor contact for Doctor of Philosophy in Computer Science (PhD)
Applicants should browse faculty profiles and indicate in their application who they are interested in working with. No commitment from a supervisor prior to applying is necessary, but contacting faculty members is encouraged.
Advice and insights from UBC Faculty on reaching out to supervisors
These videos contain some general advice from faculty across UBC on finding and reaching out to a supervisor. They are not program specific.
This list shows faculty members with full supervisory privileges who are affiliated with this program. It is not a comprehensive list of all potential supervisors as faculty from other programs or faculty members without full supervisory privileges can request approvals to supervise graduate students in this program.
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Lemieux, Caroline (Programming languages and software engineering; help developers improve the correctness, security, and performance of software systems; test-input generation; specification mining; program synthesis)
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Leyton-Brown, Kevin (Computer and information sciences; Artificial Intelligence; Algorithms; theoretical computer science; Resource Allocation; Computer Science and Statistics; Auction theory; game theory; Machine Learning)
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MacLean, Karon (Computer and information sciences; Information Systems; design of user interfaces; haptic interfaces; human-computer interaction; human-robot interaction)
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McGrenere, Joanna (Computer and information sciences; computer science; computer supported cooperative work (CSCW); human-computer interaction; interactive technologies for older users and people with cognitive disorders; personalized user interfaces; universal usability)
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Mehta, Aastha (Software domains (including operating systems and software infrastructure); Information privacy; security & privacy; Systems security; networking; Operating systems; Data privacy; distributed systems)
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Mitchell, Ian (safety critical systems, assistive technology (mobility), robotics, scientific computing, cyber-physical systems, Mathematical software, computational science and engineering, hybrid and cyber-physical systems, verification and validation, reproducible research, level set methods, robotic path, planning)
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Munzner, Tamara (Human-centered computing; visualization; information visualization; visual analytics; data science)
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Murphy, Gail (Programming languages and software engineering; Software Development; knowledge worker productivity; software design; software engineering; software evolution)
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Ng, Raymond Tak-Yan (Data mining and analysis, health informatics, text summarization, text mining)
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Pai, Dinesh (Robotics, computer graphics, medical imaging, neuroscience, sensorimotor computation )
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Park, Mi Jung (Privacy-preserving machine learning algorithms, Compressing neural network models using Bayesian methods, Relationships between differential privacy and other emerging notions in machine learning)
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Pasquier, Thomas (Development of more transparent computer systems, Whole-system provenance, Computational experiments reproducibility, Intrusion detection, privacy and compliance)
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Pottinger, Rachel (Computer and information sciences; Computer Science and Statistics; data integration; data management; databases; metadata management)
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Roth, Andrew (Bioinformatics; Cancer Evolution; Cancer omics data; computational statistics; Computational Biology; computational methods for studying clonal population structures and tumour evolution; Evolutionary cancer biology; genomics; Machine Learning; Methodological work in computational statistics; Molecular Oncology)
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Schmidt, Mark (Machine learning; Numerical Optimizaiton; Probabilistic Graphical Models; Causality)
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Seltzer, Margo (Computer Systems; Data Quality; Storage; Machine Learning & Systems; Systems for capturing and accessing data provenance; File Systems; databases; Transaction processing systems; Storage and analysis of graph-structured data; New architectures for parallelizing execution; Systems that apply technology to problems in healthcare.; Artificial Intelligence; Decision-making & Action; Software Practices; Networks, Systems and Security)
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Sheffer, Alla (Computer graphics, shape modeling and geometry processing)
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Shelhamer, Evan (Machine learning; Computer vision in artificial intelligence; Artificial intelligence (AI); Machine Learning; Computer Vision / Visual Recognition; Robustness and Adaptation; Self-Supervised / Unsupervised Learning; Applications to Remote Sensing and Sustainability)
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Shepherd, Bruce (Natural sciences; Algorithms, Combinatorics, Polyhedra)
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Shwartz, Vered (Artificial Intelligence; Machine Learning; Natural Language Processing)
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Sigal, Leonid (Computer and information sciences; Artificial Intelligence; Computer Science and Statistics; Parametric and Non-Parametric Inference; Computer Vision; Machine Learning; Semantic Recognition; Vision + Natural Language Processing; Visual Recognition and Understanding)
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Summers, Alexander (Programming languages and software engineering; programming languages; software engineering)
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Tang, Xin (Bioinformatics; Artificial intelligence (AI); Cell biology; Neurosciences, biological and chemical aspects; Mathematical biology; Genetics; Medical and biomedical engineering; Cancer; Neurosciences, medical and physiological and health aspects; Explainable and Interpretable Learning, Representation Learning, Knowledge Distillation; Biologically Informed Neural Network, Physically Informed Neural Network; Knowledge Distillation, Biological LLM, Biomedical Image Processing; Computational Cell Biology, Single-cell Biology, Multi-omics, Virtual Cell, Spatial Omics; Brain-Computer Interface, Neuroscience, Brain Mapping; Cancer Genomics, Development, Aging)
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Van de Panne, Michiel (Computer Science and Statistics; Computer Sciences and Mathematical Tools; Robotics and Automation; simulation of human movement; computer animation; Robotics; deep reinforcement learning; motor control; computer graphics)
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Doctoral Citations
A doctoral citation summarizes the nature of the independent research, provides a high-level overview of the study, states the significance of the work and says who will benefit from the findings in clear, non-specialized language, so that members of a lay audience will understand it.
| Year | Citation |
|---|---|
| 2024 | Dr. Feng proposed an inexpensive method to reduce the amount of human labeling in the task of extracting relations from documents. He proposed a novel self-training method to improve the performance of text generation and relation extraction when few labeled data is used to train a machine learning model. |
| 2024 | Dr. He developed a self-supervised machine learning tool that minimizes the need for extensive human annotation, thereby alleviating the reliance on costly human labor during the machine learning development process. |
| 2023 | Dr. Xiao made notable contributions in the field of text summarization through her innovative application of machine learning techniques. She enhanced AI summarizers with discourse information. Her impactful research is a valuable asset in our data-driven and time-constrained society, offering an effective solution for managing information overload. |
| 2023 | Dr. Munk studied scientific simulators, probabilistic models, and their stochastic inversion via probabilistic programming. His research has led to novel contributions to the field of probabilistic programming. These contributions may impact diverse disciplines, ranging from physics to finance. |
| 2023 | Artists often start creation by sketching digitally. Dr. Liu studied how humans mentally see sketches without being confused by busy, inaccurate lines and built computational methods to automate this process. These methods benefit various sketch-related computer applications, from colourizing 2D animation frames to lifting design sketches into 3D. |
| 2023 | Dr. Lin's work focused on developing the theory and practice of geometric methods in machine learning. His research opens a new direction for exploiting hidden mathematical structures in real-world applications. His methodology was used to win the Bayesian Deep Learning Challenge in Neural Information Processing Systems 2021. |
| 2023 | Dr. Alomeir developed new ways to simplify database provenance using visual tools and summarization techniques. He focused on relational databases, making provenance easier for users of database systems to explore. His methods also help users gain a clearer understanding of a database's origins in a concise manner. |
| 2023 | The simulation of frictional contact is a challenging problem in computer graphics. Dr. Larionov developed methods to accurately simulate friction between objects with smooth surfaces and showed where current methods fail. This work pushed the boundaries of acceptable friction behaviour in graphics, and opened promising avenues for future research. |
| 2023 | Dr. Eremondi developed the theory of gradual dependently typed programming languages. Under this paradigm, programmers can use types to write correctness specifications, but can smoothly migrate the checking of those specifications between compile time and run time. This furthers the goal of making it easier to prove that software is free of errors. |
| 2023 | Dr. Janzen explored how users could better manage mobile notifications, which is difficult and time consuming despite extensive research on the subject. Through user centered design she identified that infrequent, targeted personalization sessions supported by visualizations of notification use could encourage and support notification management. |
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Sample Thesis Submissions
Further Information
Specialization
Computer Science covers Bayesian statistics and applications, bioinformatics, computational intelligence (computational vision, automated reasoning, multi-agent systems, intelligent interfaces, and machine learning), computer communications, databases, distributed and parallel systems, empirical analysis of algorithms, computer graphics, human-computer interaction, hybrid systems, integrated systems design, networks, network security, networking and multimedia, numerical methods and geometry in computer graphics, operating systems, programming languages, robotics, scientific computation, software engineering, visualization, and theoretical aspects of computer science (computational complexity, computational geometry, analysis of complex graphs, and parallel processing).
Faculty Overview
Academic Unit
Program Identifier
VGDPHD-FM
Classification
Program Enquiries
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