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WELCOME TO ESTER LAB
MACHINE LEARNING AND DATA MINING RESEARCH GROUP
SIMON FRASER UNIVERSITY
Principal Investigator
Principal Investigator
Welcome! My name is Martin Ester, and I am a Distinguished Professor of Computing Science at Simon Fraser University in Burnaby, British Columbia. I got my Diplom (M.Sc.) in Computer Science from University of Dortmund, Germany, in 1984 and my Ph.D. in Computer Science from ETH Zurich, Switzerland, in 1990.
My research interests are in Data Mining and Machine Learning. The style of my research is use-case inspired basic research: we identify open problems that have use cases in important applications and solve these problems in a principled, innovative manner. The current focus of our basic research is on transfer learning, continual learning, agents for science, and generative molecule models. Our main driving applications are in biology and medicine, in particular for precision medicine, such as drug response prediction, prediction of genetic causes of adverse drug reactions, and drug discovery.
Since my move to Vancouver in 2001, I am enjoying "Beautiful BC" and especially the many hiking trails around the Vancouver area. Our campus lies in the middle of the "wilderness" of the Burnaby Mountain conservation area, and I am commuting to and from work on my mountain bike.
Please, check out our website to know more about our research and our people!
NEWS
NEWS
Recent Updates
Recent Updates
September 2026. Welcome to our new MSc student Ece Çelik!
May 2026. Welcome to our new PhD student AmirHossein Kashani!
July 2026. Congratulations to Arash Khoeini on successfully defending his Ph.D. Thesis, titled Contrastive Learning for Biomedical Applications. He started a job as Machine Learning Research Engineer at RBC Borealis, Vancouver.
April 2026. Congratulations to Tongzhou (Tony) Shen on successfully defending his Ph.D. Thesis, titled A Generative Flow Approach for Practical Drug Design. He started a job as Research Scientist at Isomorhic Labs, London, UK.
Recent Publications
Recent Publications
Mao, Yuzhen, Qitong Wang, Martin Ester, and Ke Li. "IceCache: Memory-efficient KV-cache Management for Long-Sequence LLMs." ICLR 2026.
Diniz, Raphaella, Jackson de Faria, and Martin Ester. "PAS: Estimating the target accuracy before domain adaptation." ICLR 2026.
Seong Joon Oh, Shuman Peng, Arnas Uselis, Darina Koishigarina, Martin Ester.
CLIP Models Generalize Less Than Compositional Benchmarks Suggest. ICML Workshop on Compositional Learning: Safety, Interpretability, and Agents 2026.
Du, Yuanqi, Botao Yu, Tianyu Liu, Tony Shen, Junwu Chen, Jan G. Rittig, Kunyang Sun et al. "Accelerating scientific discovery with autonomous goal-evolving agents." arXiv preprint arXiv:2512.21782 (2025).
Pandey, Mohit, Gopeshh Subbaraj, Artem Cherkasov, Martin Ester, and Emmanuel Bengio. "Pretraining generative flow networks with inexpensive rewards for molecular graph generation." ICLR 2025.
Pandey, Mohit, Jane Foo, Shabnam Massah, Morgan A. Alford, Hazem Mslati, Gopeshh Subbaraj, Mira Saba et al. "A scalable reinforcement learning approach for screening large peptide libraries for bioactive peptide discovery." Nature Communications 16, no. 1 (2025): 11685.
Arash Khoeini, Funda Sar, Yen-Yi Lin, Colin Collins, and Martin Ester. "scMUSCL: multi-source transfer learning for clustering scRNA-seq data." Bioinformatics 41, no. 5 (2025).
Seonghwan Seo, Minsu Kim, Tony Shen, Martin Ester, Jinkyoo Park, Sungsoo Ahn, Woo Youn Kim. "Generative Flows on Synthetic Pathway for Drug Design", ICLR 2025
Arash Khoeini, Shuman Peng, Martin Ester. "Informed Augmentation Selection Improves Tabular Contrastive Learning" PAKDD 2025: 306-318
Yuzhen Mao, Yen-Yi Lin, Nelson K. Y. Wong, Stanislav Volik, Funda Sar, Colin C. Collins, Martin Ester. "Phenotype prediction from single-cell RNA-seq data using attention-based neural networks", Bioinform. 40(2) (2024)
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