ML Specialist/Software Engineer

Abhijith Balagurusamy

781-***-**** • **************@*****.*** • Lexington, MA

EDUCATION

University of Toronto

Bachelor of Engineering: Computer Engineering

Toronto, ON

Expected May 2028

SKILLS

Programming: Python Java C Linux Bash JavaScript HTML CSS NodeJS Technologies: matplotlib pandas numpy AWS CAD Git Relevant Coursework: Algorithms Data Structures Machine Learning Linear Algebra Multivariable Calculus WORK EXPERIENCE

Beth Israel Deaconess Medical Center (BIDMC)

Data Science Intern

Brookline, MA

June 2023 - August 2024

Utilized Python and Pandas to create a data pipeline for sleep EEG and cognitive task data

Created data visualizations with MatPlotLib and Seaborn of patient data

Developed Python-based Amazon Web Services Lambda functions to organize and preprocess raw EEG data UMass Lowell NERVE Robotics Center

Embedded Systems Intern

Lowell, MA

June 2022 - August 2022

Utilized C++ and ROS for precise gripper control and procedural mapping algorithms

Programmed deep-learning based Arduino circuits for autonomous path-finding systems

Created 10+ CAD designs for robot projects, grippers and circuits later used in research reports at NERVE lab The Greater Boston STEM Academy

Computer Science Instructor

Cambridge, MA

September 2022 - January 2024

Designed advanced Python and machine learning curriculum for advanced students

Courses covered Pandas, Scikit-learn, Numpy, Object-Oriented Programming, and basic data structures

Taught courses in python and machine learning to 20+ students KTByte Computer Science Academy

Computer Science Instructor

Lexington, MA

June 2020 - August 2023

Taught courses in machine learning, data structures, and algorithms to novice programmers

Taught and TA’d over 15 advanced computer science courses with 12+ students each

Coached students to advanced USACO Silver+ rankings through tutoring sessions and office hours sessions PROJECTS

DeepFake Detection Analysis

Using Python and Pytorch, compared CNNs, Autoencoders, and ResNets for Deep Fake Image Detection

Utilized matplotlib to generate ROC curves, Accuracies, Precision, and Recall for model analysis

Presented full research report and presentation at Massachusetts Science and Engineering Fair GardenX Web Application

Utilized Javascript, EJS, HTML and CSS created a social media application to share garden progress

Used PlantNet API to build functionality for identifying images of plants

Utilized MongoDB to store user data on uploaded images, collected plants and plant types

Shared application amongst local community to amass 20+ users

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