Education
- 2023: Postdoc at Western University, Canada
- 2023: PhD from the University of Manitoba, Canada
- 2019: MSc from the University of Manitoba, Canada

Dr. Qian Liu is an Assistant Professor in the Department of Applied Computer Science at the University of Winnipeg. She is trained in machine learning, deep learning, applied statistics, bioinformatics, computational biology, and medical imaging. Dr. Liu holds a Ph.D. in Individual Interdisciplinary Studies, which integrates Computer Science, Statistics, and Medical Genetics.

Dr. Liu's research lab is dedicated to developing and applying advanced data science techniques, such as multi-modal data integration (including genomics, imaging, time-series, and graph data), joint statistics and machine learning, and interpretable artificial intelligence (AI). Her work addresses specific challenges in healthcare and material science, aiming to improve diagnostic accuracy, treatment planning, and the development of new materials.

Dr. Liu’s expertise in AI, statistics, and bioinformatics synergizes with the diverse skills of her collaborators. Her multidisciplinary and collaborative framework enhances the impact of her research, making significant contributions to both healthcare and material science.


Qian Liu

Ph.D.

Department of Applied Computer Science
University of Winnipeg
Winnipeg, MB, Canada
Email: qi.liu~at~uwinnipeg.ca

Publications

* co-first author
** co-corresponding author

2024

29. Y Li, L Lac, Q Liu, P Hu
ST-CellSeg: Cell segmentation for imaging-based spatial transcriptomics using multi-scale manifold learning
Plos Computational Biology.https://doi.org/10.1371/journal.pcbi.1012254.
28. YW Jin, P Hu, Q Liu
NNICE: a deep quantile neural network algorithm for expression deconvolution
Scientific Reports. 14, 14040. https://doi.org/10.1038/s41598-024-65053-w.
27. R Qiu, X Zhang, C Song, H Nong, Y Li, X Xing, K Mequanint, Q Liu, X Sun, M Xing, L Wang
E-cardiac patch to sense and repair infarcted myocardium
Nature Communications. 15, 4133. https://doi.org/10.1038/s41467-024-48468-x.
26. J Chowdhury, Q Liu, S Ramanna
Simple histogram equalization technique improves performance of VGG models on facial emotion recognition datasets
Algorithms. 17, 6: 238. https://doi.org/10.3390/a17060238.
25. Z Huang, L Chen, Y Sun, Q Liu**, P Hu**
Conditional generative adversarial network driven radiomic prediction of mutation status based on magnetic resonance imaging of breast cancer
Journal of Translational Medicine. 22:226. https://doi.org/10.1186/s12967-024-05018-9.

2023

24. Q Liu, S Huang, D Desautels, KJ McManus, L Murphy, P Hu
Development and validation of a prognostic 15-gene signature for stratifying HER2+/ER+ breast cancer
Computational and Structural Biotechnology Journal. 21:2940-2949.
23. D Fung, Q Liu, L Lac, L O'Neil, C Hitchon**, P Hu**
Deep learning-based joint detection in Rheumatoid arthritis hand radiographs
AMIA (American Medical Informatics Association) Jt Summits Transl Sci Proc . 206-215. PMID: 37350925. Seattle, Washington, USA.
22. I Paul, D Bolzan, A Youssef, KA Gagnon, H Hook, G Karemore, MUJ Oliphant, W Lin, Q Liu, S Phanse, C White, D Padhorny, S Kotelnikov, CS Chen, P Hu, GV Denis, D Kozakov, B Raught, T Siggers, S Wuchty, SK Muthuswamy, A Emili
Parallelized multidimensional analytic framework applied to mammary epithelial cells uncovers regulatory principles in EMT.
Nature Communications, 14:688.
21. Q Liu, S Huang, Z Zhang, T Lakowski, W Xu, P Hu
Multiomics-based tensor decomposition for characterizing breast cancer heterogeneity
Invited chapter for “Machine Learning Methods for Multi-Omics Data Integration” edited by Luis Rueda. Nature Springer -Verlag Press. 133-150.
20. Q Liu, P Hu
Radiogenomic association of deep MR imaging features with genomic profiles and clinical characteristics in breast cancer
Biomarker Research, 11:9

2022

19. Q Liu*, M Reed*, H Zhu*, Y Cheng, J Almeida, G Fruhbeck, R Ribeiro, P Hu
Epigenome-wide DNA methylation and transcriptome profiling of localized and locally advanced prostate cancer: uncovering new molecular markers
Genomics, 114(5):110474.
18. Y Su, Q Liu, W Xie, P Hu
YOLO-LOGO: A transformer-based YOLO segmentation model for breast mass detection and segmentation in digital mammograms
Computer Methods and Programs in Biomedicine,221:106903
16. Q Liu, P Hu
An integrative computational framework for breast cancer radiogenomic biomarker discovery
Computational and Structural Biotechnology Journal, 20:2484-2494
15. J Zammit, DLX Fung, Q Liu, CKS Leung, P Hu
Semi-Supervised COVID-19 CT Image Segmentation Using Deep Generative Models
BMC Bioinformatics, 23:343
14. N Feizi, Q Liu, L Murphy, P Hu
Computational prediction of the pathogenic status of cancer-specific somatic variants
Frontiers in Genetics. 12:805656
13. B Blum, W Lin, ML Lawton, Q Liu, J Kwan, I Turcinovic, R Hekman, P Hu, A Emili
Multi-omic metabolic enrichment network analysis reveals metabolite-protein physical interaction subnetworks altered in cancer
Molecular & Cellular Proteomics. 21 (1):100189
12. Q Liu, P Hu
Interpretable and extendable deep learning for pan-cancer radiogenomics research
Current Opinion for Chemical Biology. 66:102111
11. Q Liu*,B Cheng*, Y Jin, P Hu
Bayesian tensor factorization-driven breast cancer subtyping by integrating multi-omics data
Journal of Biomedical Informatics. 125:103958

2021

10. LJ Oneil, P Hu, Q Liu, M Islam, V Spicer, J Rech, A Hueber, V Anaparti, I Smolik, H EI-Gabalaway, G Schett, JA Wilkins
Proteomic Approaches to Defining Remission and the Risk of Relapse in Rheumatoid Arthritis
Frontiers in Immunology, 12:729681
9. Q Liu*, D LX Fung*, L Lac*, P Hu
A novel matrix profile-guided attention LSTM model for forecasting COVID-19 cases in USA
Frontiers in Public Health, 9:741030
8. D LX Fung*, Q Liu*, J Zammit, CK Leung, P Hu
Self-supervised deep learning model for COVID-19 lung CT image segmentation highlighting putative causal relationship among age, underlying disease and COVID-19
Journal of Translational Medicine. 19:318
7. A Bruinooge*, Q Liu*, Y Tian, W Jiang, Y Li, W Xu, CN Bernstein, P Hu
Genetic predictors of gene expression associated with psychiatric comorbidity in patients with IBD: a pilot study
Genomics. 113: 919-932.
6. R Ajwad, M Domaratzki, Q Liu, N Feizi, P Hu
Identification of significantly mutated subnetworks in the breast cancer genome
Scientific Reports. 11:642

2020

5. Q Liu, CK Leung, P Hu
A two-dimensional sparse matrix profile DenseNet for COVID-19 diagnosis using chest CT image
IEEE Access. 8:213718-213728

2019

4. Q Liu, A Junker, K Murakami, P Hu
A novel convolutional regression network for cell counting
2019 IEEE 7th International Conference on Bioinformatics and Computational Biology. Hangzhou, China
Won Best Oral Presentation Paper
3. Q Liu, A Junker, K Murakami, P Hu
Automated cancer cell counting by ensembling deep features
Cells, 8(9):1019
2. Q Liu, P Hu
Association analysis of deep genomic features extracted by denoising autoencoders in breast cancer
Cancers. 11:494

2018

1. P Basak, S Chatterjee, V Bhat, A Su, H Jin, V Lee-Wing, Q Liu, P Hu, LC Murphy, A Raouf
H19 acts as an estrogen receptor modulator that is required for endocrine therapy resistance in ER+ breast cancer cells
Journal of Cellular Physiology and Biochemistry. 51:1518-1532

News

2024.5.31 Dr. Qian Liu won the University of Manitoba Distinguished Dissertation Award. Congratulations!

2024.3.5 Our undergraduate student Xiao Zhang won the NSERC USRA award. Congratulations!

2023.8.4 Dr. Qian Liu's lab has now been established and is accepting graduate students, welcoming visiting scholars, and providing research opportunities for undergraduate students. If you are interested in engaging in research with Dr. Liu, please reach out via email to explore potential opportunities.

Members

Undergraduate Student
Xiao Zhang (Applied Computer Science, University of Winnipeg)
Recipient of the NSERC USRA Award

MSc Student
Huanjing Liu (Applied Computer Science, University of Winnipeg)

Positions

Dr. Liu is currently open to accepting graduate students, welcoming visiting scholars, and providing research opportunities for undergraduate students. If you are interested in engaging in research with Dr. Liu, please reach out via email to explore potential opportunities.