📍 VANCOUVER, CANADA

WELCOME TO ESTER LAB

MACHINE LEARNING AND DATA MINING RESEARCH GROUP

SIMON FRASER UNIVERSITY

Principal Investigator

Welcome! My name is Martin Ester, and I am a 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.

I am a co-director of the Databases and Data Mining Laboratory and member of the Omics Data Science Research Cluster. My research interests are in Data Mining and Machine Learning, in particular causal pattern discovery, transfer learning, network analysis, and recommender systems. Much of my research is driven by bio-medical applications such as patient stratification and drug response prediction. Our methods are typically based on Probabilistic Graphical Models and Deep Neural Networks.

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.


NEWS

Recent Updates

We are pleased to welcome the following new members to our lab:
Raphaella Carvalho, Yuzhen Mao and Amirreza Kazemi!

The Ester Lab would like to congratulate Dr. Hossein Sharifi Noghabi on successfully defending his thesis entitled "Deep Transfer Learning for Drug Response Prediction"!

Jobs Updates

Sep 2021 - Congrats to Lai Wei for his new position as an intern at Huawei, Toronto Office - Canada.

Sep 2021 - Congrats to Hossein Sharifi for his new position as an AI4Life Resident at Novartis - Switzerland.

Aug 2021 - Congrats to Oliver Snow for his new position as a Machine Learning Researcher at Terramera, Vancouver Office - Canada.

Jul 2021 - Congrats to Jialin Liu for his new position as a Software Engineer at Huawei, Vancouver Office - Canada.

May 2021 - Congrats to Raquel Aoki for her new position as a Research Intern at Google Brain, Cambridge Office - US.

Recent Publications - Last 24 months

[Paper] Snow, Oliver, Hossein Sharifi-Noghabi, Jialin Lu, Olga Zolotareva, Mark Lee, and Martin Ester. "Interpretable Drug Response Prediction using a Knowledge-based Neural Network." In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, pp. 3558-3568. 2021.


[Paper] Arab, Ali, Betty Chinda, George Medvedev, William Siu, Hui Guo, Tao Gu, Sylvain Moreno, Ghassan Hamarneh, Martin Ester, and Xiaowei Song. "A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CT." Scientific Reports 10.1 (2020): 1-12.


[Paper] Aoki, Raquel, and Martin Ester. "ParKCa: Causal Inference with Partially Known Causes." Pac Symp Biocomput. 2021


[Preprint] Peng, Shuman, Weilian Song, and Martin Ester. "Combining Domain-Specific Meta-Learners in the Parameter Space for Cross-Domain Few-Shot Classification." arXiv preprint arXiv:2011.00179 (2020).


[Preprint] Sharifi-Noghabi, Hossein, Hossein Asghari, Nazanin Mehrasa, and Martin Ester. "Domain Generalization via Semi-supervised Meta Learning." arXiv preprint arXiv:2009.12658 (2020).


[Paper] Mansouri, Mehrdad, Ali Arab, Zahra Zohrevand, and Martin Ester. "Heidegger: Interpretable Temporal Causal Discovery." In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 1688-1696. 2020.


[Paper] Sharifi-Noghabi, Hossein, Shuman Peng, Olga Zolotareva, Colin C. Collins, and Martin Ester. "AITL: Adversarial Inductive Transfer Learning with input and output space adaptation for pharmacogenomics." Bioinformatics 36, no. Supplement_1 (2020): i380-i388.


[Paper] Snow, Oliver, Nada Lallous, Martin Ester, and Artem Cherkasov. "Deep learning modeling of androgen receptor responses to prostate cancer therapies." International journal of molecular sciences 21, no. 16 (2020): 5847.


[Preprint] Snow, Oliver, Hossein Sharifi, Jialin Lu, Olga Zolotareva, Mark Lee, and Martin Ester. "BDKANN-Biological Domain Knowledge-based Artificial Neural Network for drug response prediction." bioRxiv (2020): 840553.


[Paper] Zolotareva, Olga, Sahand Khakabimamaghani, Olga I. Isaeva, Zoe Chervontseva, Alexey Savchik, and Martin Ester. "Identification of Differentially Expressed Gene Modules in Heterogeneous Diseases." bioRxiv (2020).


[Award] SFU COMPUTING SCIENCE PROFESSOR MARTIN ESTER NAMED ROYAL SOCIETY OF CANADA FELLOW [link]


[Paper] Khakabimamaghani, Sahand, Dujian Ding, Oliver Snow, and Martin Ester. "Uncovering the subtype-specific temporal order of cancer pathway dysregulation." PLoS computational biology 15, no. 11 (2019): e1007451.


[Paper] Khakabimamaghani, Sahand, Yogeshwar D. Kelkar, Bruno M. Grande, Ryan D. Morin, Martin Ester, and Daniel Ziemek. "SUBSTRA: Supervised Bayesian Patient Stratification." Bioinformatics 35, no. 18 (2019): 3263-3272.


[Poster] Lu, Jialin, and Martin Ester. "An Active Approach for Model Interpretation." arXiv preprint arXiv:1910.12207 (2019). in Human-centric machine learning (HCML2019) workship, co-located with NeurIPS, 2019.


[Poster] Lu, Jialin, and Martin Ester. "Checking Functional Modularity in DNN By Biclustering Task-specific Hidden Neurons." (2019). in AI Workshop, co-located with NeurIPS, 2019.


[Poster] Aoki, Raquel, and Martin, Ester. "Bayesian Predictive Model combined with Matrix Factorization for Causal Inference Analysis." in 14th Machine Learning in Computational Biology (MLCB) meeting, co-located with NeurIPS, 2019.


[Paper] Khakabimamaghani, Sahand, Salem Malikic, Jeffrey Tang, Dujian Ding, Ryan Morin, Leonid Chindelevitch, and Martin Ester. "Collaborative intra-tumor heterogeneity detection." Bioinformatics 35, no. 14 (2019): i379-i388.

For older publications, please check Martin Ester's Google Scholar here.