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Machine learning PhD at University of Toronto
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Toronto
Doctor of Philosophy - PhD, Machine Learning
January 1, 2019 – January 1, 2025
University of Toronto
Bachelor of Applied Science (B.A.Sc.), Engineering Science, Robotics Option
January 1, 2014 – January 1, 2019
University of Toronto
Teaching Assistant
January 1, 2019 – April 1, 2019
University of Toronto
Research Assistant
May 1, 2018 – June 1, 2019
aUToronto
Team Member
January 1, 2018 – April 1, 2019
Greater Toronto Area, Canada
Dessa
Software Developer & Machine Learning Engineer Intern
April 1, 2017 – April 1, 2018
Toronto, Canada Area
University of Toronto
Teaching Assistant
September 1, 2016 – December 1, 2016
Toronto, Canada Area
University of Toronto Institute for Aerospace Studies (UTIAS)
Undergraduate Researcher
May 1, 2016 – September 1, 2016
4925 Dufferin St, North York, ON, Canada
6th Orbis Challenge
October 1, 2015 – Present
Participated in the 6th Orbis Challenge in a team of 2. Developed a mathematical model for the problem and wrote an AI program controlling one of the players in a battle game using Python.
Sketching App Development
July 1, 2015 – August 1, 2015
Developed a sketching app using Microsoft Foundation Classes (MFC).
Vermicompost Stack Design
February 1, 2015 – April 1, 2015
In a team of 4, designed a vermicomposting stack to maximize the efficiency of compost production and minimize human labor. Engaged with Evergreen community, used various design and decision tools, carried out research, made a model, and showcased the project.
Request for Proposal for Cat Trap Design
January 1, 2015 – February 1, 2015
In a team of 4, engaged with stakeholders at the Toronto Humane Society and identified a problem with capturing and neutralizing feral cats. Did research, consulted professionals, developed objectives and requirements, and wrote a Request for Proposal for cat trap design.
Pong AI vs. AI
November 1, 2014 – Present
In a team of 2, wrote an AI program to control one of the players in a Pong game using Python. Got honorable mention in a class-wise competition.
Truss Bridge Design
October 1, 2014 – Present
In a team of 3, designed a truss bridge in response to a Request for Proposal as a course assignment. Calculated and designed for vertical truss, wind bracing, deflection, cost, etc.
Cultural Fit Analysis
The candidate's background is heavily skewed towards Machine Learning, AI, and Robotics, with significant academic and research experience. While this demonstrates strong technical capabilities, the target role is 'Data Analyst'. The projects and experience do not explicitly highlight core data analysis skills such as advanced SQL, data visualization, statistical analysis for business insights, or specific data manipulation tools commonly used by data analysts. The focus on AI/ML might indicate a preference for more complex modeling over traditional data analysis, which could be a mismatch for a typical Data Analyst role. The project diversity shows a willingness to engage in varied tasks, but the technical alignment with a Data Analyst role is limited.
Soft Skills & Operational Fit
The candidate's project descriptions indicate strong collaboration skills (e.g., 'In a team of 4', 'In a team of 2'). Experience as a Teaching Assistant suggests good communication and mentoring abilities. Leadership roles in projects like 'Capture Go' and SLAM demonstrate initiative and problem-solving. The diverse range of projects, from app development to vermicomposting, indicates a broad interest and adaptability, which could translate to a flexible operational fit.