Instructors

Han Yu is a first-year PhD student in the Quantitative Life Sciences program at McGill University. She holds a BSc in Mathematics and Applied Mathematics from Beijing Forestry University and a MSc in Biostatistics from Yale University. Han has supported graduate teaching and contributed to enhancing data visualization in clinical research through industry internships.

My research interests are in next-generation sequencing technologies and pipelines and in better understanding genetic diseases such as cancer. I have a BSc in Cellular, Molecular and Microbial Biology from the University of Calgary and an MBinf (Bioinformatics) from the University of Guelph. I am currently completing my PhD at the Ontario Institute for Cancer Research and the University of Toronto.

She graduated from Carnegie Mellon University in 2017 with a dual degree in Computational Biology and Chemistry. She is interested in developing machine learning models for improving current strategies of neoantigen design and prioritization for cancer immunotherapy.

Dr. Ido Hatam holds a PhD in microbiology and biotechnology from the University of Alberta and serves as an Instructor in the Department of Biology and Bioinformatics program at Langara College, where he is also a Principal Investigator at the College’s Applied Research Center. Dr. Hatam has developed multiple courses for the College’s Bioinformatics program focused on using R-based tools to analyze high-throughput biological data. His research group uses bioinformatics tools to construct and analyze synthetic microbial communities, and specializes in “Guerrilla Bioinformatics” – generating value-added knowledge through meta-analysis of large, publicly available biological datasets.

Ishu has a BSc in electrical engineering and has interest in digital signal processing and data science. He has worked in the Wishart Research Group to apply machine learning to various applications in bioinformatics, biology, and metabolomics.

Jacqueline is a postdoctoral fellow in Dr. William Wong’s lab at University of Waterloo’s School of Pharmacy. Her current work focuses on the development of pharmacoeconomic models for health outcomes research. Her PhD thesis entailed a broad-scale comparison of different imputation methods on trait datasets and an investigation of how these methods impact statistical inferences.

Our research focuses on the development of new algorithms, methods and software for analyzing genome sequencing data.

Jasmine received her Bachelor’s degree in Biology, majoring in Molecular Biology and minoring in Marine Biology, from the University of New Brunswick in April 2013. She then pursued her Master’s degree in Epidemiology from the Department of Epidemiology, Biostatistics and Occupational Health from McGill University in May 2016. Her research interest is integrating microbiome and metabolomics data to gain deep functional insights.

Dr. Jennifer Geddes-McAlister is an Associate Professor in the Department of Molecular and Cellular Biology at the University of Guelph and the Canada Research Chair in the Proteomics of Fungal Disease in One Health. Her lab applies mass spectrometry-based proteomics and bioinformatics tools to investigate host-pathogen interactions with a focus on One Health approaches to overcoming fungal disease. She was recently awarded an Alumni Achievement Award from the University of Lethbridge, a Research Excellence Award from the University of Guelph and multiple early career researcher awards from the Government of Ontario and scientific societies. She is Director of the Bioinformatics Graduate Programs at the University of Guelph, President of the Canadian National Proteomics Network, co-founder of the Canadian Proteomics and Artificial Intelligence Consortium, and founder of ‘Moms in Proteomics’ an initiative dedicated to recognizing and supporting mothers in STEM.

During Jermiah’s time at Western University, he earned a Masters in Medical Biophysics after completing his Bachelors of Science in Integrated Science with an Honors Specialization in Computer Science. With his passion for interdisciplinary science, the Haibe-Kains lab has provided him with the opportunity to use his toolkit of computational skills to solve problems in healthcare.

His research focuses on statistics and bioinformatics for metabolomics, microarray and next generation sequencing (RNA-seq) data analysis and integration. Some of the tools he developed in the past include MetaboAnalyst for statistical analysis of metabolomics data, MSEA for metabolite set enrichment analysis, MetPA for metabolic pathway analysis, ROCCET for ROC curve based biomarker analysis, and NetworkAnalyst for data integration and network analysis. His general interest is high-throughput omics data analysis using a variety of statistics, machine learning and data visualization technologies.