Kieran Campbell Lab Toronto


Jun 17, 2024
New lab publication

Congratulations to Cindy and Alina for their paper Beyond benchmarking and towards predictive models of dataset-specific single-cell RNA-seq pipeline performance now published in Genome Biology.

Jun 8, 2024
Kieran presenting at Spatial Biology East Coast 2024

Kieran will be giving a talk on Machine learning tools for the analysis and interpretation of highly multiplexed imaging data at Spatial Biology East Coast 2024.

May 12, 2024
Welcome Cece and Elliot

Welcome to Cece and Elliot who join as summer undergraduate research students.

Apr 15, 2024
Lab presentations at RECOMB 2024

Michael and Jett will be presenting posters/short talks on their work on mapping loss of antigen presentation at single cell resolution and on segmentation aware clustering for multiplexed imaging at RECOMB and RECOMB-CCB 2024.

Mar 5, 2024
New preprint on cell segmentation aware clustering for spatial expression assays

Our preprint on STARLING - a new method for clustering highly multiplexed imaging data while accounting for segmentation errors - is now up on bioRxiv along with a corresponding twitter thread.

Mar 1, 2024
New paper on single-cell data integration in imbalanced settings

Congratulations to Hassaan, Michael, and Chengxin whose paper understanding the impacts of dataset imbalanced on single-cell data integration is now published in Nature Biotechnology.

Feb 3, 2024
New paper on active and self-supervised learning for single-cell expression data

Congratulations to Michael and Sean whose work understanding the impact of active and self-supervised learning on efficient annotation of single-cell expression data has been published in Nature Communications.

Jan 16, 2024
Welcome to Sarah

Welcome to Sarah Asbury who joins as a graduate student developing methods to map T cell exhaustion from multi-modal data.

Jan 9, 2024
New preprint on automated machine learning for scRNA-seq analysis

Congratulations to Cindy and Alina for their new preprint on automated machine learning for scRNA-seq analysis!.

Sep 12, 2023
Scholarship successes

Congratulations to Shanza for being awarded a 3 year Canada Graduate Scholarships — Doctoral award and to Michael for being awarded a TFRI MOHCCN Data Science fellowship.

Jul 27, 2023
Alina's work accepted to AutoML 2023

Congratulations to Alina who's work published in TMLR has been accepted in the journal track of the 2023 AutoML conference.

Jun 1, 2023
Welcome to Haifen and Kevin

Welcome to Haifen Chen and Kevin Sun who join as a Research Associate and NSERC summer student respectively. Haifen will be working on a range of collaborations around single-cell and spatial omics, and Kevin will be working on methods development for learning cell representations from highly-multiplexed imaging data.

Apr 10, 2023
Kieran presenting at AACR 2023

Kieran will be presenting at AACR 2023 in Orlando, Florida at the “Multiplexed Imaging: Ready for Prime Time?” educational session.

Mar 20, 2023
Paper on Multi-objective Bayesian optimization of heuristic objectives accepted to TMLR

Congratulations to Alina Selega whose paper on Multi-objective Bayesian optimization of heuristic objectives has been accepted to Transactions on Machine Learning Research (TMLR). You can read the paper here.

Jun 14, 2022
New preprint: AutoML for genomic data analysis

We have a new preprint on Multi-Objective Bayesian Optimization methods over heuristic objectives with applications in genomics. Check out the paper and the tweetorial.

Jun 13, 2022
Lab conference presentations summer 2022
  • Cindy Fang will be presenting our work on predicting what pipeline is best to analyze a scRNA-seq dataset at Bioc 2022.
  • Jett Lee will be presenting our work on segmentation error aware clustering for highly multiplexed imaging at the MLSCB COSI at ISMB 2022.
  • Kieran is presenting at the Stanford Computational and Systems Immunology Seminar on August 2nd.
Apr 26, 2022
Chengxin presenting at RECOMB and RECOMB-CCB

Chengxin Yu will be in San Diego at RECOMB 22 and the CCB satellite to present our work on using single-cell counterfactuals to dynamically evaluate the accuracy of bulk RNA-seq deconvolution methods.

Jan 21, 2022
Undergraduate summer research opportunity available

We are looking for an undergraduate student researcher to join us for a summer internship to build classification models of YAP-dependent cancer subtypes via the University of Toronto Data Science Institute SUDS program. Please see here for details and eligibility, our project is entitled AI classification of cancer patients into novel YAP-dependent subtypes. The deadline to apply is February 7th and applications may be submitted here.

Jan 6, 2022
Welcome to Darren

Welcome to Darren Chan who joins as a PhD student jointly supervised by Hartland Jackson.

Oct 14, 2021
Welcome to Morris & Eunice

A big welcome to Morris Greenberg who joins as a PhD student in statistical sciences co-supervised with Radu Craiu and Eunice Poon who joins for the term as an undergraduate co-op student.

Sep 22, 2021
New lab publication

Our work on automated cell type assignment for highly multiplexed imaging data has been published in Cell Systems. Congratulations to Michael, Jinyu, Sunyun, and Shanza.

Jul 27, 2021
Scholarship success

Congratulations to Cait and Chengxin on receiving Ontario Graduate Scholarships and to Shanza for receiving a OSOTF award!

Jun 10, 2021
Welcome to Benjamin and Sean

Welcome to Benjamin Zheng and Sean Gong who join the lab as an Amgen scholar and for BCB 330 projects respectively.

Mar 31, 2021
Alina becomes Vector Institute postgraduate affiliate researcher

Congratulations to Alina Selega who has been selected for the 2021 Vector Institute Postgraduate Affiliate Program.

Mar 5, 2021
CIHR project grant success

We have been awarded a 5 year CIHR project grant (with Hartland Jackson and Daniel Schramek) to use computational and experimental approaches to understand immune escape in pancreatic cancers. Congratulations all!

Feb 1, 2021
Welcome to Alina

Welcome to Alina Selega who joins as a postdoctoral fellow to work on AutoML approaches for biomedical data analysis.

Jan 19, 2021
Stanford BIMR seminar

Kieran is speaking at the Stanford Center for Biomedical Informatics Research Colloquium on January 21st.

Jan 15, 2021
Congratulations Joanne on AAI Intersect fellowship

Joanne Leung has been awarded an AAI Intersect Fellowship. Congratulations!

Dec 22, 2020
Canada Research Chair success

Kieran has been awarded a 5 year Canada Research Chair in Machine Learning for Translational Biomedicine from CIHR.

Dec 8, 2020
Michael joins the lab for PhD

Congratulations to Michael Geuenich who will be staying on in the lab to complete his PhD working on machine learning models for cancer genomics.

Sep 7, 2020
Welcome to new students!

Welcome to Shanza Ayub and Chengxin Yu who join as PhD students in the Computational Biology in Molecular Genetcs (CBMG) program, and to Aisha Faruqui and Cindy Fang who join as undergraduate research students for 2020-2021!

Jun 18, 2020
NSERC success

We have been awarded a 5 year NSERC Discovery grant Accelerating biological discovery with automated machine learning for single-cell data analysis to develop and apply AutoML methods in the field of single-cell data analysis.

May 19, 2020
Welcome & congratulations to Sunyun

Welcome Sunyun Lee who is a 3rd year Toronto Computer Science student, who joins the lab having won an NSERC Undergraduate Student Research Award!

May 19, 2020
Michael joins the lab

Welcome Michael Geuenich who joins the lab as a summer student before continuing his PhD in Molecular Genetics here in Toronto.

May 5, 2020
New review paper on computational modelling for single-cell cancer genomics

Our review paper Computational modelling in single-cell cancer genomics: methods and future directions is now online as a preprint.

Apr 25, 2020

We are pleased to host the second workshop on single-cell cancer genomics (SCANGEN) at ISMB2020. Abstract submission is open until June 5th.

Apr 23, 2020
Jinyu joins the lab

Welcome Jinyu Hou who is a UofT CS student and joins the lab for a summer project in machine learning modelling of spatial proteomics data.