resume

General Information

Full Name Stefan Vladusic
Location Toronto, ON Canada
Languages English (Native), Serbo-Croatian (Fluent), French (Professional Working Proficiency)

Education

  • Sept 21 - Dec 22
    Master in Computational Mathematics
    University of Waterloo, waterloo, Canada
    • Co-supervised by Professors Chris Bauch and Chris Fletcher.
    • Recipient of Keith & Debbie Geddes and Waterloo Graduate Scholarships (valued at $6,000).
    • Graduated with 4.0/4.0 cGPA
    • Coursework
      • AMATH 651 - Introduction to Dynamical Systems
      • CM 740/CO 602/CS 795 - Fundamentals of Optimization
      • CM 763/STAT 841 - Statistical Learning - Classification
      • CM 750/AMATH 741/CS 778 - Numerical Solutions of Partial Differential Equations
      • CM 770/AMATH 740/CS 770 - Numerical Analysis
      • GEOG 652 - Climate Prediction, Modeling and Scenarios
  • Sept 20 - Aug 21
    Master in Financial Mathematics
    McMaster University, Hamilton, Canada
    • Completed industrial research project on deriving ISDA's SIMM model from Gaussian Value-at-Risk models.
    • Graduated with 11.875/12.0 cGPA.
    • Coursework
      • MFM 701 - Foundations of Financial Mathematics
      • MFM 702 - Risk and Financial Markets
      • MFM 703 - Computational Finance I
      • MFM 704 - Statistics of Financial Data
      • MFM 711 - Portfolio Theory and Optimization
      • MFM 712 - Credit Risk Modelling
      • MFM 713 - Computational Finance II
      • MFM 714 - Topics in Risk Management
  • Sept 15 - Jan 20
    Physics and Philosophy Specialist (Bachelors of Science)
    University of Toronto, Toronto, Canada
    • Under the supervision of Prof. Micheal Miller, completed a research project focusing on causal explanations of quantum correlations
    • Received six $1,000 merit-based scholarships, one $2,000 grant for a humanities research position.
    • Graduated with High Distinction and a 3.71/4.0 cGPA.

Experience

  • Sept 22 - Dec 22
    Research Assistant
    University of Waterloo, Waterloo, Canada
    • Trained hybrid CNN-LSTM neural networks to detect climate early warning signals of tipping points of Atlantic circulation.
    • Wrote a numerical solver for low-order Atlantic circulation models.
    • Generated a database of 500,000 time series to train and test the hybrid networks using HPC cluster.
    • Hybrid neural networks outperform more generic state-of-the-art network in accuracy, precision, and recall (~13%, ~11.5%, ~19% improvements, respectively).
  • May 22 - Aug 22
    Junior Data Scientist
    Praemo Inc., Kitchener, Canada
    • Created a production-level anomaly detection model for industrial time series data in a two-member team.
    • Model uses a combination of machine learning clustering techniques and traditional statistical methods (bootstrapping, Levene’s test, etc.).
    • Involved both in the formal mathematical model components, as well as the model’s implementation in Python.
  • Sept 21 - Apr 22
    Teaching Assistant
    University of Waterloo, Waterloo, Canada
    • Responsibilities include grading students and running office hours for first year linear algebra and introductory proof courses (MATH 115, MATH 135, and MATH 136).
  • May 21 - Aug 21
    Model Analyst Intern
    Bank of Nova Scotia (Scotiabank), Toronto, Canada
    • Created and maintained data pipeline and scripts to generate reports on market trends and key risk metrics for bank portfolios. Implemented in Python, SQL and Bash.
    • Wrote Python script that computes initial margin for large derivatives transactions with small team.
    • Wrote reports summarizing quantitative features and limitations of exotic option pricing models for internal audits.

Skills

  • Programming Languages (In order of Proficiency)
    • Python
    • MATLAB
    • R
    • SQL
  • Libraries
    • TensorFlow
    • NumPy
    • Scikit-learn
  • Tools
    • Git
    • Bash
    • SLURM
    • LaTeX
    • Markdown
    • Microsoft Office
  • Technical Knowledge
    • Familiar with numerical methods used to solve linear systems, non-linear equations, PDEs.
    • Familiar with regression analysis, neural networks, tree-based classifiers, time series analysis.

Other Interests

  • Hobbies: Sound Design, Tetris, Basketball, Cycling.