2026 UBC Advanced Research Computing Summer School

Monday, June 1, 2026

9:30 AM– 12 PM

Level of Difficulty: Introductory

Prerequisite: None

Instructor:  Jacob Boschee, Tannistha Nandi

Please note that this session will be recorded and shared on our YouTube channel after the event.

Monday, June 1, 2026

1:30 PM– 2:30 PM

Introduction to Digital Research Alliance of Canada

Level of Difficulty: Introductory

Prerequisite: None

Instructor: Michael Tang

Please note that this session will be recorded and shared on our YouTube channel after the event.

Tuesday, June 2, 2026

10:00 AM– 12:00 PM

Parallel Computing with MATLAB

Offered in partnership with MATLAB. This hands-on workshop introduces parallel and distributed computing in MATLAB, focusing on speeding up applications and offloading compute. Through common scenarios and live demos, participants will build a practical understanding of MATLAB’s parallel constructs and how to navigate common hurdles. 

Level of Difficulty: Intermediate

Prerequisite:   No prior experience is required, but familiarity with MATLAB is encouraged. We recommend completing the self-paced MATLAB Onramp before the session to get comfortable with the basics.

Technology Requirement: Access to a web browser. Google Chrome is recommended for the best experience.

Instructor: Evan Cosgrove (MATLAB)

Tuesday, June 2, 2026

1:30 PM– 3:30 PM

Introduction to Deep Learning with MATLAB

Offered in partnership with MATLAB. Deep learning enables automation across images, signals, text, and controls—achieving state-of-the-art accuracy in tasks from object recognition to path optimization. In this hands-on lab, participants will use MATLAB Online to build, train, and evaluate deep learning models from scratch and with transfer learning.

Level of Difficulty: Introductory

Prerequisite:   No prior experience is required, but familiarity with MATLAB is encouraged. We recommend completing the self-paced MATLAB Onramp before the session to get comfortable with the basics.

Technology Requirement: Access to a web browser. Google Chrome is recommended for the best experience.

Instructor: Dr. Elvira Garcia Osuna-Highley (MATLAB)

Wednesday, June 3, 2026

9:30 AM– 12:00 PM

Security, RDM and AI - Simple Right? Or is it?

Level of Difficulty: Introductory

Prerequisite:  None

Instructor: Luc Letarte, Michael Chuang, Scott Baker

Please note that this session will be recorded and shared on our YouTube channel after the event.

Wednesday, June 3, 2026

1:30 PM– 3:00 PM

Leveraging Classical Infrastructure in Quantum-Enabled Environments with Dell

Offered in partnership with Dell Technologies. This session will introduce and explore the concept of Hybrid Quantum-Classical Computing, which is a practice of integrating traditional High-Performance Computing (HPC) infrastructure closely with quantum accelerators. The session discusses some of the key advantages of this approach, including how quantum processing can be made more efficient and useful with CPU and GPU resources.

Level of Difficulty: Intermediate

Prerequisite:  None

Instructor: Burns Healy (Dell Technologies)

Thursday, June 4, 2026

9:30 AM– 10:30 AM

Finetuning Your Embedded Model for Better Search: Learning from Agentic Search at Dell 

Offered in partnership with Dell Technologies. This session introduces embedding models as a core component of modern machine learning systems for clustering, ranking, and large-scale information retrieval. It explains how embeddings are trained, covering representation learning theory, contrastive and metric-learning losses, and data preparation strategies that influence embedding quality. An EmbeddingGemma‑style code walkthrough illustrates dataset construction, pairing, and negative sampling, and connects training choices to retrieval performance using a real-world agentic search application at Dell.

Level of Difficulty: Beginner to Intermediate

Prerequisite:  None

Instructor: Rachel Shalom  (Dell Technologies)

Thursday, June 4, 2026

2:00 PM– 3:30 PM

Physical AI from Models to Systems and Real World Constraints

Offered in partnership with Dell Technologies. This session introduces Physical AI, a class of AI systems that perceive, reason, and act in the physical world under real-world constraints such as latency, uncertainty, and safety. It examines the emerging model and system stack behind Physical AI, including perception models, world models, vision-language-action models, and behavior models, and explains how these components form closed-loop systems over time. The session also addresses key system challenges, including real-time execution, feedback loops, deployment outside controlled environments, and the gap between simulation and reality.

Level of Difficulty: Intermediate

Prerequisite:  None

Instructor: Aruna Kolluru (Dell Technologies)

Friday, June 5, 2026

10:00 AM – 11:45 AM

Researcher Spotlight

The UBC ARC Summer School Researcher Spotlight features presentations from two UBC faculty members working in artificial intelligence research. The session includes a presentation by Dr. Purang Abolmaesumi, Professor in the Department of Electrical and Computer Engineering, on AI for echocardiography, followed by Dr. Vered Shwartz, Assistant Professor of Computer Science, on applications of large language models in the legal domain.

Prerequisite: None

Speakers: Dr. Purang Abolmaesumi, Dr. Vered Shwartz

Please note that this session will be recorded and shared on our YouTube channel after the event.