Welcome to the University of Toronto’s Department of Computer Science!
We invite you to learn more about the graduate student experience through a series of sessions — from the academic details of your program, to information about finances, and health and wellness. Sessions are outlined in the schedule below.
Orientation Schedule
Day 1: Tuesday, September 1, 2026 (MSc, MScAC, PhD)
First Floor, Bahen Centre for Information Technology, 40 St. George St.
9:00–9:20 Breakfast and Registration
In the Atrium outside BA1160
9:20–9:40 Ice-Breaker
BA1160
Hosted by the Computer Science Graduate Student (CSGS) Union.
9:40–9:55 Departmental Welcome
Welcome to the Department by Faculty Leadership and Student Leadership.
Prof. Angela Demke Brown, Associate Chair, Graduate Studies
Prof. Arvind Gupta, Academic Director, Professional Programs and Director, Strategic Initiatives
9:55–10:25 Graduate Office Admin Presentation
Introduction to the Graduate Office staff and our role in student success.
10:25–10:35 Communications
An overview of the Marketing Communications Office and services provided to graduate students in the Department.
Presenter: Rebecca Heiman-Hull, Communications Manager
10:35–10:45 IT Orientation
Introduction to computing at DCS, including the Point of Contact (PoC) team.
Presenter: John DiMarco, Director, Information Technology
10:45–11:00 Space
Overview of space and who to connect with regarding offices, access, and maintenance.
Presenter: Joseph Raghubar, Facilities Coordinator
11:00–11:10 Break
11:10–11:30 Health & Wellness
Introduction to Health and Wellness at U of T providing information regarding medical services, mental health resources, and peer supports.
Presenter: Allan McKee, Health Communications Coordinator
11:30–11:50 Centre for International Experience
Information regarding CIE, services to both domestic and international students, including immigration advising.
Presenter: Katharine Lauder, UHIP Team Lead, CIE
12:00–14:00 Grad Student Lunch and Ice-Cream Social
In the Atrium outside BA1160
Enjoy lunch and meet current students at the tasty ice-cream social!
14:00–14:30 Centre for Graduate Mentorship and Supervision
BA1160
How do you form a good supervisory relationship? Who can you connect with to discuss concerns regarding supervision that is confidential and separate from the Department? CGMS will provide an overview of the services.
Presenter: Aziza Kajan, Director, Centre for Graduate Mentorship and Supervision
14:30–15:00 Graduate Professional Development & Student Success
Providing an overview of the opportunities available to graduate students to deepen their professionalization and resources for their graduate career and beyond.
Presenter: Joel Rodgers, Coordinator, Graduate Student Professional Development
15:00–15:20 Safety Abroad
Travelling outside of Canada on research or conferences? Safety Abroad's presentation will provide an introduction to the policies and supports for all graduate students travelling outside of Canada.
Presenter: Jasmine Shen, Learning Abroad Coordinator, CIE
15:20–15:30 Break
15:30–16:30 Teaching Assistantship (TA) Orientation
This mandatory TA training session will give you important information on being a TA in the Department of Computer Science.
Presenter: Prof. Alice Gao, Asst. Professor, Department of Computer Science
Patrina Seepersaud, Interim TA Coordinator
Matthew Varona, CUPE Steward Representative
16:30–17:00 Wrap up and Final Questions
Day 2: September 2, 2026 (MSc, PhD)
Third Floor Bahen Centre for Information Technology, 40 St. George St.
9:30–9:50 Breakfast
In BA3201, 40 St. George St.
10:00–10:35 Program Overview
An overview of the research-stream programs and requirements from our Associate Chair, Graduate Studies.
Presenter: Prof. Angela Demke Brown, Associate Chair, Graduate Studies
10:35–11:15 Student Funding
Funding is an important part of the research-stream programs. Learn what components make it up, how to understand your funding letters, and how tuition and fees works.
11:15–11:30 Awards
Awards are a critical piece of graduate work. What awards are students required to apply for? How many award opportunities are available? This presentation will provide the details.
11:30–11:35 Break
11:35–12:05 Graduate Student Research Talks
Research presentations from current graduate students.
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Talk Title: “Practical Sketching Data Structures Beyond the Worst Case”
Abstract: Succinct sketching data structures are fundamental to modern data systems, offering significant speed and space advantages by trading off a controlled amount of accuracy. Bloom filters are the classic example—ideal for answering "Is this key in my dataset?" Yet, a gap exists between theory and practice: many practical sketches rely on heuristics that compromise accuracy, while theoretically sound sketches often under-perform because they are optimized solely for worst-case scenarios.
Bio: Navid is a fourth-year PhD student in the SysNet group at the University of Toronto. A member of the ORCA Lab, where he has the pleasure of being supervised by Prof. Niv Dayan. He designs data structures tailored to database systems, focusing on randomized and sketching data structures. He also optimize his data structures to leverage the power and speed of modern hardware to the fullest, making them lightning-fast!
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Talk Title: “Mathematically Structured Learning for Fast and Generalizable Physical Simulation”
Abstract: Physical simulation allows us to model how objects move, deform, and interact, but high-fidelity simulations can be computationally expensive. Reduced-order simulation can significantly accelerate these computations, but often requires expensive precomputation for each new shape or scenario. My research explores mathematically structured learning as a way to build simulation models that are both fast and generalizable. Rather than relying on purely data-driven models, I incorporate mathematical and geometric structure into learned representations of physical systems. This enables compact models that can generalize across shapes, discretizations, and dynamics while retaining important physical behavior. In this talk, I will share several examples from my research and discuss how combining mathematical structure with machine learning can provide a path toward efficient and generalizable physical simulation.
Bio: Chang Yue is a PhD student in Computer Science at the University of Toronto, advised by Prof. Eitan Grinspun. Her research focuses on mathematically structured learning for fast and generalizable physical simulation. She develops computational models that combine mathematical and geometric structure with machine learning to build compact representations of complex physical systems. Her work spans reduced-order modeling, spectral geometry, and data-driven dynamics. Her first-authored research has received both a Best Paper Award and a Best Paper Honorable Mention at ACM SIGGRAPH, the premier conference in computer graphics.
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Talk Title: “Quantum Neural ODE”
Abstract: Training and running frontier AI models requires enormous computing resources. Could quantum computers help overcome this bottleneck? In this talk, I'll share my research on new quantum algorithms for inference and learning in exponentially large neural networks.
Bio: Abhinav Muraleedharan is a PhD student at the University of Toronto, supervised by Prof. Nathan Wiebe. His research focuses on quantum algorithms for machine learning and simulation.
12:05–13:45 Faculty Mentor Lunch
Lunch in BA3200 for incoming students and faculty mentors
13:45–15:45 NSERC Grant Writing Workshop
Workshop open to new and returning CS graduate students on how to apply for the NSERC awards.
Presenter: Danielle Martak, Acting Director of Graduate Writing Support
19:00–onward CSGS Pub Night
Details to be provided separately