Instructors
Letícia is a PhD candidate at Dalhousie University, investigating the genotype-phenotype evolution of whale acoustics. Her research combines genomics, bioinformatics and bioacoustics to understand how whales adapted their communication to different environments. Letícia is also active in teaching, science communication and outreach. She is the developer and instructor of the undergraduate course “Science Communication for Social Change” at Dalhousie, runs a bilingual science communication page (@leticiamagpali) and the outreach program “Evolution for Everyone”, which offers free training in bioinformatics to equity-seeking students.
Prior to joining OICR in 2006, Dr. Stein played an integral role in many large-scale data initiatives at Cold Spring Harbor Laboratory and at the Massachusetts Institute of Technology (MIT) Genome Center. He led the development of the first physical clone map of the human genome, and ran the data coordinating centre and the data portal for the SNP Consortium and the HapMap Consortium. Dr. Stein has also led the creation and development of Wormbase, a community model organism database for C. elegans, and Reactome, which is now the largest open community database of biological reactions and pathways.
At OICR, Dr. Stein has led several international cancer data sharing and research initiatives, including the creation and development of the data coordination centre for the International Cancer Genome Consortium and other related projects. He continues to collaborate with national and international partners to create and promote data sharing standards, protocols and implementations.
Dr. Linglong Kong is a Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta, holding a Canada Research Chair in Statistical Learning and a Canada CIFAR AI Chair. He is a Fellow of the American Statistical Association (ASA) and the Alberta Machine Intelligence Institute (Amii), with over 120 peer-reviewed publications in leading journals and conferences such as AOS, JASA, JRSSB, NeurIPS, ICML, and ICLR. Dr. Kong received the 2025 CRM-SSC Prize for outstanding research in Canada. He serves as Associate Editor for several top journals, including JASA and AOAS, and has held leadership roles within the ASA and the Statistical Society of Canada. Dr. Kong’s research interests include high-dimensional and neuroimaging data analysis, statistical machine learning, robust statistics, quantile regression, trustworthy machine learning, and artificial intelligence for smart health.
Lusine received her Ph.D. in Mathematics under the supervision of prof. V. Bogachev from Moscow State University in the area of nonlinear stochastic equations for measures. She works in Dr. D. Wishart’s computational group, where she learned machine learning and Python and developed tools for applications in bioinformatics. She also works in research involving applications of EPR spectroscopy at the Applied Pharmaceutical Innovation.
Mackenzie Tapp recently graduated from Dalhousie University with an Honours Co-Op Bachelor of Computer Science, with a minor in statistics and a certificate in intelligent systems. Throughout her undergraduate degree, she has participated in research involving computer vision, natural language processing, and speech diarization. She has recently begun a Masters of Applied Science in Biomedical Engineering at Dalhousie University, where she will be investigating applications of machine learning algorithms in neuroscience.
Mai obtained Ph.D. in Chemical Biology from McMaster University in 2019. Her Ph.D. research focused on metabolomics of irritable bowel syndrome and inflammatory bowel disease. Later, she worked as a postdoc under Dr. Jeff Xia at McGill University and became more familiar with R programming and computational work in the field of metabolomics. Currently, she works under Dr. David Wishart to make metabolomics-based personalized health assessment more accessible in partnership with an industrial partner.
Dr. Griffith’s research is focused on the development of genomics and bioinformatics methods as they apply to the study of cancer biology and medicine. A particular focus of his work is in the translation of genomics data from whole genome, exome and transcriptome sequencing into clinically actionable observations and personalized cancer therapies. He has led the development of key online informatics resources for cancer precision medicine such DGIdb, DoCM, CIViC and more.
He received a Ph.D. in Biochemistry from the University of Missouri-Columbia, USA, in 2002, where he studied the structure and dynamics of oncoviral proteins with high-resolution NMR methods. Mark conducted his post-doctoral research of protein structural biology in University of Michigan, USA, and then joined Dr. Wishart’s group at University of Alberta, Canada, to work on data analysis and software development in the fields of metabolomics, NMR, and protein structure and dynamics.
Mark Phillips works in comparative privacy and data protection law, particularly where it intersects with health data sharing. His academic background is in law and computer science, and he is a practicing member of the Quebec Bar Association. He works at the Centre of Genomics and Policy at McGill University as an Academic Associate, and is the co-chair of the Data Protection Task Team of the Global Alliance for Genomics and Health’s Research and Ethics Work Stream. His comparative legal research focuses on topics including cloud computing, the identifiability of personal data, bioinformatics, and open data.
Dr. Hirst’s research aims to further our understanding of the role of epigenetic dysfunction in cancer initiation and progression and to translate this knowledge into improved health outcomes for Canadians.
International efforts to characterize genetic lesions in cancer genomes have revealed recurrent mutations in epigenetic modifiers and in some cases these can represent the sole driver. Understanding the functional implications of these mutations, their contribution to abnormal cellular differentiation and how emerging epigenetic therapeutics may counteract their effects represent the next critical steps towards translating this knowledge. In this context, Dr. Hirst is studying cancers that harbor highly recurrent gain and loss of function mutations to epigenetic modifiers, such as acute myeloid leukemia, synovial sarcoma, malignant rhabdoid tumor. His research involves the development and application of molecular and computational tools to measure epigenetic features and drive new insights into normal and pathogenic epigenetic regulatory control.