AML-TN highlights research collaboration and the exchange of knowledge—not only within UBC, but also beyond its borders. Our Research Mobility Program exposes graduate students to diverse perspectives, with the opportunity to gain international research experience and expand their professional networks. These stays focus on mentorship while advancing projects in artificial intelligence and machine learning.
Note: Students are open to undergo research stays at institutions not listed, but these stays must be pre-approved to ensure alignment with goals and adequate supervision.
Contributions & Support
To ensure a successful and productive experience, AML-TN provides:
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$4,000 financial support to cover student costs associated with the stay
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Assistance in organizing and planning the visit, including coordination with the host institution
Host institutions provide in-kind support that typically includes:
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Supervision by a collaborating faculty member at the host institution
- Research and office space, computing resources, and administrative facilitation
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Exchange of scholarly information, including research papers, indices to theses, and relevant books
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Invitations to attend scholarly and technical meetings, including seminars, talks, and events
These contributions ensure that students fully engage with the research community, gain hands-on experience, and develop professional relationships that last throughout their careers.
Applications are open year round, and reviewed consistently. All graduate students supervised by participating UBC faculty are encouraged to apply via the link below!
Research Stays
| Graduate Student | Host Faculty | Research Stay Location | Research Topics |
|---|---|---|---|
| Amman Yusuf Ph.D., Computer Science Mi Jung Park (Supervisor) | Mingyu Kim | Kookmin University Seoul, South Korea | Privacy, memorization, and safety in text based generative models, with focus on discrete diffusion models |
| Cedar Turek Ph.D., Computer Science Frank Wood (Supervisor) | George Constantinides | Imperial College London London, England | |
| Donney Fan Ph.D., Computer Science Geoff Pleiss & Mark Schmidt (Co-Supervisors) | Jacob Gardner | University of Pennsylvania Philadelphia, USA | Bayesian optimization, machine learning agents, black box optimization |
| Luna Peck Ph.D., Computer Science Danica Sutherland (Supervisor) | Michael Biehl, Caroline Rowland, & Paul Smolensky | Chalmers University of Technology Gothenburg, Sweden | Perspectives on language acquisition in analytical connectionism, with a emphasis on LLM learning |
| Pierre Mackenzie Ph.D., Computer Science Kevin Leyton-Brown & Serena Wang (Co-Supervisors) | Ariel Procaccia | Harvard University Cambridge, USA | Evaluation and Metrics for ML |
| Taylor Lundy Ph.D., Computer Science Kevin Leyton-Brown (Supervisor) | Sageev Oore | Dalhousie University Halifax, Canada | LLM evaluation |
| William Cheng MSc., Computer Science Mi Jung Park (Supervisor) | Mingyu Kim | Kookmin University Seoul, South Korea | Privacy and Security in Machine Learning for diffusion models, adaptation, and LLMs |
| Zhejun Jiang MSc., Computer Science Mi Jung Park (Supervisor) | Jinseong Park | Korean Institute for Advanced Study (KIAS) Seoul, South Korea | Diffusion Language Models, Trustworthy AI |
| Saiyue Lyu Ph.D., Computer Science Mathias Lécuyer (Supervisor) | Martin Vecehv | ETH Zürich Zürich, Switzerland | Trustworthy AI, in particular, certified robustness against adversarial attack during test time adaption; and certified training for universal adversarial robustness; possibly VLM/LLM alignments |
| Graduate Student | Host Faculty | Research Stay Location | Research Topics |
|---|---|---|---|
| Tiange (Ivy) Liu MSc., Statistics Trevor Campbell (Supervisor) | Jonathan Huggins | Boston University Boston, USA | Bayesian Inference for a Challenging Biosignature Recovery Problem Using MCMC |
| Zheng He MSc., Computer Science Danica Sutherland (Supervisor) | Arthur Gretton | Gatsby Computational Neuroscience Unit London, England | Kernel based conditional independence testing |
| Graduate Student | Host Faculty | Research Stay Location | Research Topics |
|---|---|---|---|
| Frederik Kunstner Ph.D., Mark Schmidt (Supervisor) | Jorge Ignacio González Cázares | Alan Turing & Isaac Newton Institutes London & Cambridge, England | The emergence of heavy-tails in optimization for machine learning and its impact on training |
| Nathaniel Xu Ph.D., Computer Science Danica Sutherland (Supervisor) | David Ginsbourger | University of Cambridge Cambridge, England | Kernel Methods |