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Hi, I'm Gursimar

Gursimar Singh

Computer Science Undergraduate @ University of Toronto

I am an undergraduate student passionate about research in Machine Learning, particularly in the fields of Natural Language Processing, Computer Vision and Implicit Neural Representations.

I currently hold the following positions;

Skills
Python
PyTorch
OpenCV
Tensorflow
Java
Rust

Experience

1
Machine Learning Research Assistant
Cognitive Neuroscience & Sensorimotor Integration Laboratory

September 2023 - Present
Toronto, ON

ML Research assistant for a Computational Neuroscience Research Project under Professor Matthias Niemeier.

Responsibilities:
  • Using state-of-the-art convolutional architectures to model the ventral and dorsal streams in the human brain for object classification and robotic grasping tasks using PyTorch
  • Working on novel, task-agnostic architectures and data visualization and analysis methods to compare the emergence of separate neural pathways to EEG data from the human brain.

Director of Education
UofT AI Group

June 2023 - Present
Toronto, ON

Responsibilities:
  • Leading a team of 7 associates to develop and deliver course content to over 150 students on topics like Neural Networks, Computer Vision, Natural Language Processing (NLP) and Generative AI.
2

3
Machine Learning Engineer
Photografirst

May 2023 - July 2023
Toronto, ON

Responsibilities:
  • Applied Vision and Swin Transformers to Computer Vision tasks like duplicate detection, semantic segmentation, and ensembling using PyTorch, Tensorflow, Scikit-Learn and Pandas.

Project Director
University of Toronto Machine Intelligence Student Team (UTMIST) $\times$ Photografirst

September 2022 - May 2023
Toronto, ON

Responsibilities:
  • Led a team of 9 developers to make image culling software with complex Computer Vision models like depth detection, semantic segmentation and neural style extraction in PyTorch, Tensorflow and OpenCV.
4

Education

Bachelor of Science, Computer Science with a focus in AI, Minor in Mathematics
CGPA: 4.0 / 4.0
Honors and Awards:
  • Dean's List Scholar
  • J.S. Mclean Scholarship
  • Gordon Southam Leadership Scholarship
  • Dr. James A. & Connie P. Dickson Scholarship In Science & Mathematics
Taken Courses:
  • Introduction to Computer Science I & II
  • Introduction to the Theory of Computation
  • Data Structures and Analysis
  • Software Design, Tools and Systems Programming
  • Calculus (Single & Multivariable) with Proofs
  • Linear Algebra I & II
  • Probability, Statistics and Data Analysis I

Projects

ML Paper Implementations

PyTorch implementations of popular ML papers, including Transformers, Attention, GPT, BERT, ELMo, Vision Transformers and more.

Studeasy

A webapp that uses Large Language Models to help students streamline studying by automating the boilerplate tasks. Winner of Second Best Overall Hack at Hack the Mist 2023

Virtual Whiteboard

An app that uses hand pose estimation and a live video feed to allow the user to draw in thin air.

Pose2Play

An app that uses pose estimation and a live video feed to allow the user to play their favourite video games with tangible actions.

Autograd-rs

An implementation of an autograd engine that can compute gradients for arbitrary functions. Written in Rust.

Physarum simulation

A simulation of the Physarum polychephalum slime. Written in Rust and rendered with the Bevy game engine (Video demo).

Pandemic simulation

A simple pandemic simulation written in Rust and rendered with Raylib.

Stonks

A mock stock trading app with real-time stock prices fetched with a stock API. Written in Java, structured according to the Clean Architecture and SOLID design principles. Course Project for CSC207 (Software Design).

COVID-19 and Stock price data analysis

A detailed statistical analysis of the relation between the spread of COVID-19 and stock prices of tech companies. Course project for STA130 (Statistical Reasoning).

Awards and Scholarships

Dr. James A. & Connie P. Dickson Scholarship In Science & Mathematics
University of Toronto November 2023

Gordon Southam Leadership Scholarship

Dean's List Scholar
University of Toronto September 2022 - April 2023

Second Place - Hack the Mist 2023

J.S. Mclean Scholarship
University of Toronto September 2022

Rookie Trailblazer Award

Certifications

Machine Learning with Python

Introduction to Deep Learning & Neural Networks with Keras

Scalable Machine Learning on Big Data using Apache Spark

Deep Neural Networks with PyTorch

Building Deep Learning Models with Tensorflow

AI Capstone Project with Deep Learning

IBM AI Engineering Specialization