Three UBC researchers awarded 2025 Killam Prizes and Dorothy Killam Fellowship

March 19, 2025

The National Killam Program has announced the winners of the 2025 Killam Prizes and Dorothy Killam Fellowships, recognizing 13 researchers across Canada for their research excellence. 

The winners include UBC researchers Drs. Marco Marra and Peter Zandstra, who have been awarded a Killam Prize, and Dr. Mark Schmidt, who has been awarded a Dorothy Killam Fellowship.

The Killam Prizes are awarded to active Canadian scholars who have distinguished themselves through sustained research excellence, making a significant impact in their respective fields of engineering, health sciences, humanities, natural sciences, and social sciences. 

The Dorothy Killam Fellowships support scholars of exceptional ability by granting them time to pursue research projects of broad significance and widespread interest within the disciplines of the humanities, social sciences, natural sciences, health sciences, engineering or studies linking any of these disciplines.

See the Killam Program's announcement

Introducing UBC's 2025 Killam Prize and Dorothy Killam Fellowship Recipients

 

Prof. Marra wearing a white shirt against a blue background
Marco Marra - Killam Prize in Health Sciences

Marco Marra is a University of British Columbia Killam Professor in Medical Genetics and the Michael Smith Laboratories and is the Terry Fox Leader in Cancer Genome Science. Co-founder and Director of Canada’s Michael Smith Genome Sciences Centre for more than 2 decades, Marra is known for his work in genomics and precision cancer medicine. He has driven the expansion of genomics in Canada. Marra led or co-led numerous cancer projects, revealing new mutations, biomarkers and therapeutic targets in ovarian cancers, B cell lymphomas, brain cancers, breast cancers, medulloblastomas, leukemias, rhabdoid tumours and cervical cancers. 

Marra currently co-leads the Personalized OncoGenomics (POG) program, the first to demonstrate the use of whole genome and transcriptome sequencing to personalize cancer medicine. He now participates in the Terry Fox Research Institute Marathon of Hope Cancer Centres Network, aiming to make precision cancer genomic medicine available to cancer patients across Canada.

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peter zandstra

 

Peter Zandstra - Killam Prize in Engineering

Peter Zandstra is a professor and Director of the School of Biomedical Engineering at the University of British Columbia. He is a globally recognized leader in cell therapy bioprocess engineering, with pioneering contributions that are shaping the future of regenerative medicine and immunotherapy. His research is advancing regenerative medicine as a fundamental component of modern healthcare, alongside disease prevention, diagnosis and treatment. His work has led to innovative therapeutic strategies, particularly in harnessing blood-forming cells to treat cancer and autoimmune diseases. By integrating engineering design principles, computational modeling and stem cell biology, Zandstra’s research explores the mechanisms that govern cell fate decisions. 

Beyond his scientific achievements, Zandstra has played a key role in building sustainable, inclusive and internationally respected biomedical research initiatives in Canada. His work is transforming the accessibility of life-saving cell-based therapies, making them more widely available to patients in need.

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mark schmidt
Mark Schmidt - Dorothy Killam Fellow

Addressing hyper-parameters in machine learning (ML)

Mark Schmidt is a Professor in the Department of Computer Science at the University of British Columbia. He has made significant impacts in the fields of both machine learning and numerical optimization.

Machine learning (ML) is a key tool we use to analyze the unprecedented amounts of data being collected in nearly all fields. ML is used in every day applications, such as automatic Zoom captioning, speech recognition on smart phones, face detection in cameras, product recommendations on websites, and car/pedestrian detection in cars. Advances in fundamental ML tools often lead to downstream impacts on many applications, and new applications will range from domains such as physics to biology and from education to human-computer interaction.

However, ML has a problem with what are known as hyper-parameters. The performance of modern ML models is very sensitive to these hyper-parameters. This situation will get much worse in the future as we use larger datasets, use models with more hyper-parameters to tune, and we use these models in more applications.

Schmidt’s work focuses on the development of substantially faster methods to deal with hyper-parameters. The key innovation of his work is adapting hyper-parameters at the same time as the model is learning from data. This has the potential to give similar performance to existing methods at a fraction of the cost.

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First Nations land acknowledegement

We acknowledge that UBC’s two main campuses are situated within the ancestral and unceded territory of the Musqueam people, and in the traditional, ancestral, unceded territory of the Syilx Okanagan Nation and their peoples.



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