Experience

BC Cancer

• Canada
• Hospitals and Health Care
• 700 & Above Employee

• Statistician, Machine Learning Researcher

  • Apr 2019 - Present

  - Research on Interpretable Latent Variable Model for High-dimensional Biology - Proposed and developed a deep-learning-based probabilistic topic model to unveil dynamic transcriptomic patterns, first-author publication in Cell Genomics. - Developed a Python package deltatopic to implement topic analysis for single-cell data - Developed a deep learning approach for interpretable representation of gene expression, selected for presentation at ISBM conference, Machine Learning in… Show more - Research on Interpretable Latent Variable Model for High-dimensional Biology - Proposed and developed a deep-learning-based probabilistic topic model to unveil dynamic transcriptomic patterns, first-author publication in Cell Genomics. - Developed a Python package deltatopic to implement topic analysis for single-cell data - Developed a deep learning approach for interpretable representation of gene expression, selected for presentation at ISBM conference, Machine Learning in Computational and Systems Biology (MLCSB) track. - Collaborated on a tree-structured latent topic model to derive hierarchical structures for immune activities; paper submitted. Show less - Research on Interpretable Latent Variable Model for High-dimensional Biology - Proposed and developed a deep-learning-based probabilistic topic model to unveil dynamic transcriptomic patterns, first-author publication in Cell Genomics. - Developed a Python package deltatopic to implement topic analysis for single-cell data - Developed a deep learning approach for interpretable representation of gene expression, selected for presentation at ISBM conference, Machine Learning in… Show more - Research on Interpretable Latent Variable Model for High-dimensional Biology - Proposed and developed a deep-learning-based probabilistic topic model to unveil dynamic transcriptomic patterns, first-author publication in Cell Genomics. - Developed a Python package deltatopic to implement topic analysis for single-cell data - Developed a deep learning approach for interpretable representation of gene expression, selected for presentation at ISBM conference, Machine Learning in Computational and Systems Biology (MLCSB) track. - Collaborated on a tree-structured latent topic model to derive hierarchical structures for immune activities; paper submitted. Show less



The University of British Columbia

• Canada
• Higher Education
• 700 & Above Employee

• Senior Statistical Consultant

  • Apr 2019 - Present

  - Helped clients to formulate research proposals, study design, and appropriate statistical methodologies. - Conducted data analyses across various study designs, using models such as GLMs, mixed effects, and survival proportional hazards. - Wrote statistical reports. - Supervised junior consultants.

• Senior Teaching Assistant

  • Sep 2018 - Apr 2019

  Head and co-head TA for multiple statistics courses.



Huawei Technologies Canada Co., Ltd.

• Canada
• Telecommunications
• 500 - 600 Employee

• Machine Learning Researcher

  • Apr 2022 - Aug 2022

  - Achieved 2nd place in the CVPR ActivityNet Challenge focusing on Temporal Action Localization. - Fine-tuned and aggregated multiple video classification models, including Timesformer and Video Swin Transformer, for improved performance on video classification. - Achieved 2nd place in the CVPR ActivityNet Challenge focusing on Temporal Action Localization. - Fine-tuned and aggregated multiple video classification models, including Timesformer and Video Swin Transformer, for improved performance on video classification.



NanoString Technologies, Inc

• United States
• Biotechnology Research
• 500 - 600 Employee

• Biostatistician

  • Oct 2017 - Jun 2018

  - Collaborated with a pharmaceutical company on a report to the FDA; my duty included implementing posterior inference and performing model diagnosis to validate a Bayesian hierarchical model. - Developed a data pipeline using Shiny for efficient data storage, formatting, and statistical reporting. - Proposed a cell deconvolution method for NanoString data, improved on existing method in higher accuracy. - Provided statistical consulting, implemented and interpreted the results of… Show more - Collaborated with a pharmaceutical company on a report to the FDA; my duty included implementing posterior inference and performing model diagnosis to validate a Bayesian hierarchical model. - Developed a data pipeline using Shiny for efficient data storage, formatting, and statistical reporting. - Proposed a cell deconvolution method for NanoString data, improved on existing method in higher accuracy. - Provided statistical consulting, implemented and interpreted the results of statistical models, including Elastic net and survival analysis. Show less - Collaborated with a pharmaceutical company on a report to the FDA; my duty included implementing posterior inference and performing model diagnosis to validate a Bayesian hierarchical model. - Developed a data pipeline using Shiny for efficient data storage, formatting, and statistical reporting. - Proposed a cell deconvolution method for NanoString data, improved on existing method in higher accuracy. - Provided statistical consulting, implemented and interpreted the results of… Show more - Collaborated with a pharmaceutical company on a report to the FDA; my duty included implementing posterior inference and performing model diagnosis to validate a Bayesian hierarchical model. - Developed a data pipeline using Shiny for efficient data storage, formatting, and statistical reporting. - Proposed a cell deconvolution method for NanoString data, improved on existing method in higher accuracy. - Provided statistical consulting, implemented and interpreted the results of statistical models, including Elastic net and survival analysis. Show less