Skills

Programming Languages and Software: Python, SQL, Tableau, PowerBI, Mathematica, MATLAB, Excel, LabVIEW

Python Data Science Libraries: pandas, NumPy, SciPy, Matplotlib, seaborn, Plotly, scikit-learn, XGBoost

Python Integrated Development Environments: Jupyter Notebook, Spyder, PyCharm

Relational Database Management Tools: Microsoft Access, MySQL

Machine Learning Concepts: feature selection, feature generation, categorical encoding, pipelines, cross-validation, parameter tuning, regression, SVM, decision trees, random forests, gradient descent, kNN, PCA, clustering, NLP

Version Control: Git, GitHub

Mathematics: calculus, linear algebra, differential equations, probability, statistics, numerical methods

Experience

Research Assistant York University (Toronto, Canada), Sep 2014 – Aug 2020 (writing thesis)

• Created and managed a Microsoft Access database to store and query experiment data using SQL. Implemented a schema for communicating with instrumentation with device calibration parameters.
• Analyzed large volumes of data with various statistical methods to detect signal signature using Python.
• Wrote parameter optimization programs such as gradient descent, principle component analysis to simplify experiment controls, and for stability.
• Performed Monte-Carlo simulations in Python to design a detector system that improves that enhances signals by a factor of >6.
• Trained a random forest machine learning model to classify signals due to experiment or from background using regression-analyzed, labelled data, with an accuracy of >90%.

Visiting Researcher (upon urgent request) CERN (Geneva, Switzerland), Sep 2017 – Oct 2017

• Provided management and training for a team of graduate students to operate experiments, analyze data, and how to troubleshoot. Developed experimental methods to re-establish high-priority experiments within two weeks of arrival.

Research Assistant McMaster University Nuclear Reactor (Hamilton, Canada), Mar 2017 – Aug 2017

• Performed proof-of-principle experiments to collect data from the nuclear reactor running at low power. Detected the first reactor-based antimatter beam in Canada.
• Analyzed data to optimize the apparatus for permanent installation. Forecasted large number of antimatter generated for the reactor operating at full power.

Education

PhD Candidate (Experimental Physics), York University, GPA: 3.5/4, Sep 2014 – Present (writing thesis)

Honours Bachelor of Science (Physics), York University, GPA: 3.7/4, Sep 2010 – May 2014