Hassaan Maan

Hassaan Maan

PhD Candidate at The University of Toronto

University of Toronto

Vector Institute

I’m a fourth year PhD candidate in the Bo Wang Lab, Department of Medical Biophysics, at the University of Toronto and Vector Institute. I’m also co-supervised by Kieran Campbell and Michael D. Taylor.

My research involves the development and application of machine learning and computational biology methods in single-cell genomics, particularly on integrating disparate and multi-modal single-cell datasets.

I’ve previously interned at Microsoft Research (x2), where I worked on the Antigen Map Project, and The Vector Insitute’s AI Engineering Team where I extended a COVID-19 genome analysis tool that I developed.

Download my CV to see full details of my academic and industry experience.

See my Google Scholar for a complete list of publications.

Please get in touch if you’d like to chat about research!

Interests
  • Computational biology
  • Single-cell genomics
  • Representation learning
Education

  • PhD in Medical Biophysics, 2020-

    University of Toronto

  • Master of Bioinformatics (M.Binf), 2019

    University of Guelph

  • Bachelor of Science (BSc.), 2017

    University of Waterloo

Experience

 
 
 
 
 
Microsoft Research
Graduate Research Intern - Immunomics
Microsoft Research
Jun 2023 – Sep 2023 Redmond, Washington, United States (In-person)
Generative modelling for disentangling factors of variation in TCR-repertoire data.
 
 
 
 
 
Microsoft Research
Graduate Research Intern - Immunomics
Microsoft Research
May 2022 – Aug 2022 Redmond, Washington, United States (Virtual)
Analyzing and incorporating HLA-interactions in machine-learning models for TCR-repertoire-based disease prediction.
 
 
 
 
 
Vector Institute
Applied Machine Learning Intern
Vector Institute
Sep 2021 – Dec 2021 Toronto, Ontario, Canada
Implementing a framework and projection methods for analyzing COVID-19 genome sequencing data.
 
 
 
 
 
University Health Network
Machine Learning Research Intern
University Health Network
Jan 2020 – Sep 2020 Toronto, Ontario, Canada
Various projects on utilizing single-cell sequencing data in clinically relevant settings and analysis of SARS-CoV-2 viral genomes.
 
 
 
 
 
Ontario Institute for Cancer Research
Computational Biology Intern
Ontario Institute for Cancer Research
Apr 2019 – Dec 2019 Toronto, Ontario, Canada
Developed a framework for assessing impacts of non-coding RNA interactions with regulatory elements through RNA-sequencing data of cancer genomes.

Presentations & Talks

The differential impacts of dataset imbalance in single-cell data integration
Single-cell transcriptomic data measured across distinct samples has led to a surge in computational methods for data integration. Few …
Oct 18, 2022 12:00 AM TivoliVredenburg, Utrecht, Netherlands
Hassaan Maan, Lin Zhang, Chengxin Yu, Michael Geuenich, Kieran R. Campbell, Bo Wang
The differential impacts of dataset imbalance in single-cell data integration
A Deep Learning Framework for Estimating Cell-specific Kinetic Rates of RNA Velocity
Existing RNA velocity estimation methods rely on strong assumptions of predefined dynamics and cell-agnostic constant transcriptional …
Jul 22, 2022 12:00 AM Baltimore Convention Center, Baltimore, MD
Haotian Cui (equal contribution), Hassaan Maan (equal contribution), Michael D. Taylor, Bo Wang
A Deep Learning Framework for Estimating Cell-specific Kinetic Rates of RNA Velocity
Modelling complex biological systems with machine learning and integrative single-cell genomics
The advent of genome sequencing revolutionized our understanding of human genetics. Recently, experimental advances have allowed for …
Aug 12, 2021 12:00 AM Virtual
Hassaan Maan
Modelling complex biological systems with machine learning and integrative single-cell genomics
Disrupted chromatin insulated interactions of long non-coding RNAs and protein-coding genes indicate transcriptional rewiring of oncogenic and tumor-suppressive pathways
Long non-coding RNAs (lncRNAs) have diverse roles in gene regulation, but remain poorly annotated in the context of healthy human …
Dec 12, 2019 12:00 AM MaRS Center, Toronto, ON
Hassaan Maan, Krassimir Yankulov, Stefan C. Kremer, Jüri Reimand
Disrupted chromatin insulated interactions of long non-coding RNAs and protein-coding genes indicate transcriptional rewiring of oncogenic and tumor-suppressive pathways

Selected Publications

Haotian Cui, Chloe Wang, Hassaan Maan, Kuan Pang, Fengning Luo, Bo Wang (2023). scGPT: Towards Building a Foundation Model for Single-Cell Multi-omics Using Generative AI. bioRxiv.

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Hassaan Maan, Lin Zhang, Chengxin Yu, Michael Geuenich, Kieran R. Campbell, Bo Wang (2022). The differential impacts of dataset imbalance in single-cell data integration. bioRxiv.

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Takuo Emoto, Jessie Lu, Tharini Sivasubramaniyam, Hassaan Maan, Aniqa B. Khan, Amina A. Abow, Stephanie A. Schroer, Sharon J. Hyduk, Marwan G. Althagaf, Trevor D. McKee, Fred Fu, Shiva Shabro, Antigona Ulndreaj, Felix Chiu, Elvira Paneda, Shaun Pacheco, Tao Wang, Angela Li, Jean X. Jiang, Peter Libby, Mansoor Husain, Bo Wang, Barry B. Rubin, Myron I. Cybulsky, Clinton S. Robbins (2022). Colony stimulating factor-1 producing endothelial cells and mesenchymal stromal cells maintain monocytes within a perivascular bone marrow niche. Cell - Immunity.

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Haotian Cui, Hassaan Maan, Michael D. Taylor, Bo Wang (2022). DeepVelo: Deep Learning extends RNA velocity to multi-lineage systems with cell-specific kinetics. bioRxiv.

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Hassaan Maan, Hamza Mbareche, Amogelang R. Raphenya, Arinjay, Banerjee, Jalees A. Nasir, Natalie Knox, Samira Mubareka, Andrew G. McArthur, Bo Wang (2020). Genotyping SARS-CoV-2 through an interactive web application. The Lancet Digital Health.

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