Mohamed Shakir
Computer Science and Mathematics
University of Ottawa
About
I'm a fourth year Computer Science and Mathematics student at uOttawa My current professional and research interests broadly are on high performance compute, machine learning systems, ML accelerators, and graphics processing.
Currenlty, I work as a Software Engineer Intern at Qualcomm, working on DSP and AI applications for video and image processing.
Experience
Software Engineer Intern
Qualcomm
AI and DSP applications
Software Developer Intern
Government of Canada
High Performance Compute
- •Containerized Elasticsearch, database services, and full-stack Java applications used by scientists for data ingestion and retrieval, and deployed them to production Kubernetes clusters.
- •Rewrote APIs (Java, Python, Node.js) and improved performance by 30% using autoscaling and caching strategies.
- •Built distributed storage services (PostgreSQL) to scale internal tools for researchers across departments.
Software Developer Intern
Government of Canada
High Performance Compute
- •Developed and deployed a full-stack server dashboard (React, Express.js, MySQL) to monitor infrastructure supporting clusters used by researchers.
- •Automated health checks for distributed infrastructure with Python, improving system uptime and proactive failure detection.
- •Containerized internal tools with Docker and deployed to Kubernetes clusters as part of national server migration efforts.
Research Experience
Deep Learning for Video and Image Processing
Ross Video
- •Conducting research on deep learning for streaming video super resolution. Cosupervised by uOttawa.
Stochastic Optimization & Differential Privacy
University of Ottawa
- •Proving convergence of stochastic gradient descent & differential privacy algorithms in online and offline settings.
- •Deriving theoretical results for non-smooth functions and implementing simulations to show algorithm performance.
Financial Mathematics & Quantitative Risk
Carleton University
- •Studied risk metrics including Value-at-Risk, Expected Shortfall, Conditional Value-at-Risk, and Marginal Expected Shortfall.
- •Developed dynamic volatility Bayesian models (parametric and non-parametric) based on academic papers to forecast risk metrics.
- •Back-tested models and created simulations to assess robustness and predictive accuracy under varying market condition.
Education
Honours BSc - Computer Science and Mathematics
University of Ottawa
GPA: 4.0/4.0
- •Relevant Coursework: Data Structures, Algorithms, Databases, Operating Systems, Networking, Machine Learning, Time Series Analysis, Bayesian Inference, Probability Theory
- •Awards: Dean's Honours List (every term), Merit Scholarship ($1000, every term), Admissions Scholarship ($4000), Faculty of Engineering Dean's Merrit Admission Scholarship ($4000)
Projects
findmyprof.ca
PythonOllamaCohereTypeScriptNextjs
Built a semantic search platform using LLMs and Cohere embeddings to match students with professors by research interests; scaled to 1,000+ monthly users and 8,000 searches.
