- Provides data science and technology expertise to support data-driven strategies for constituent engagement and fundraising at Concordia.- Assists the data analytics manager in initiating innovative analytics projects to drive strategic impact.- Leads data projects by developing descriptive and predictive models to guide University Advancement (UA) initiatives.- Establishes standards to ensure data integrity across processes and reporting.- Designs, develops and optimizes data… Show more - Provides data science and technology expertise to support data-driven strategies for constituent engagement and fundraising at Concordia.- Assists the data analytics manager in initiating innovative analytics projects to drive strategic impact.- Leads data projects by developing descriptive and predictive models to guide University Advancement (UA) initiatives.- Establishes standards to ensure data integrity across processes and reporting.- Designs, develops and optimizes data pipelines to improve analytics efficiency and accuracy.- Develops data models to enhance the prospect pipeline and inform UA strategy.- Supports other teams with full-stack solutions, including data collection, cloud storage, integration, modelling, processing pipelines, AI-powered insights and reporting dashboards. Show less

- Uses innovative analytics and data science to boost donations, engagement, and organizational efficiency.- Builds descriptive and prescriptive BI and AI models to drive data-informed decisions.- Identifies and prioritizes high-value donor prospects through comprehensive data mining.- Implements automated data pipelines to streamline processes and optimize resources.- Develops advanced visual dashboards and reports to support strategic planning.- Extracts actionable… Show more - Uses innovative analytics and data science to boost donations, engagement, and organizational efficiency.- Builds descriptive and prescriptive BI and AI models to drive data-informed decisions.- Identifies and prioritizes high-value donor prospects through comprehensive data mining.- Implements automated data pipelines to streamline processes and optimize resources.- Develops advanced visual dashboards and reports to support strategic planning.- Extracts actionable insights from big data by merging diverse datasets.- Communicates findings clearly to shape strategic and tactical decisions. Show less

- Data Manager of Leucegene Project: Responsible for the data centralization solution of Leucegene project. - Engaged with stakeholders to understand data needs and research goals.- Designed and implemented data science solutions to enhance organization and usability.- Developed data pipelines and applied computational, bioinformatics, and machine learning techniques to identify biological markers.- Utilized explainable AI, visualizations, and documentation to communicate… Show more - Data Manager of Leucegene Project: Responsible for the data centralization solution of Leucegene project. - Engaged with stakeholders to understand data needs and research goals.- Designed and implemented data science solutions to enhance organization and usability.- Developed data pipelines and applied computational, bioinformatics, and machine learning techniques to identify biological markers.- Utilized explainable AI, visualizations, and documentation to communicate findings and foster collaboration. Show less

Explore the RNA-seq dataset of Leucegene project (Quebec-based Acute myeloid leukemia cohort) using different computational methods and bioinformatics tools. Mine the dataset by machine learning models to identify gene modules whose expression correlates with clinical annotations therefore might be used to better understand the disease and to identify potential gene signatures or markers.

Research project: Using a simulation method to study the impact of epidemic frequency and dispersal capacity over pest population genetic structure.Languages and software used: R, Python, CDmetaPOP, ComputeCanada, GlobusJan 2018 - Aug 2018Filtered simulation data, converted sampled data into different data structures for different statistic tests needs. Analyzed, using bio-statistics tests, the simulation data under R programming environment. Interpreted the statistic… Show more Research project: Using a simulation method to study the impact of epidemic frequency and dispersal capacity over pest population genetic structure.Languages and software used: R, Python, CDmetaPOP, ComputeCanada, GlobusJan 2018 - Aug 2018Filtered simulation data, converted sampled data into different data structures for different statistic tests needs. Analyzed, using bio-statistics tests, the simulation data under R programming environment. Interpreted the statistic results.Jan 2017 - Aug 2017Simulated population genetic data using python-based simulator program CDmetaPOP. Coded a R pipeline to take different biological scenario inputs and to output the corresponding simulation data.Achievement: Presented, as the only undergraduate researcher from UdeM, the project in CSEE 2018 (Canadian Society for Ecology and Evolution) at Guelph, Ontario. Show less