About Me

Who am I?

Hello, my name is Arsh! Thank you for taking the time to be here! I am currently a student in the Engineering Science program at the University of Toronto, currently on PEY with Aercoustics Engineering Ltd. I am dedicated towards developing practical applications in the fields of machine learning and software engineering.

Moreover, in addition to my exploits in engineering, I have received certifications in the real estate and finance industry, where I aspire to use available data to form productive software solutions. In fact, I currently practice real estate part-time as a salesperson at Homelife G1 Realty.

I am currently seeking summer internship opportunities for the year of 2022 in data science, machine learning and software engineering. Please reach out on the survey at the end of the page, and I would be happy to chat!


What motivates me to work every morning. Click the boxes for a link to my work (real estate website coming soon!).

Machine Learning

With a goal on making the everyday life more intuitive and easier.

Software Engineering

Self-starter passion and desire to learn new frameworks and tools of implementation everyday.

Real Estate

Focused on making the buying and selling process consumer-friendly.

Work Experiences

Here are some work experiences I have done over the last couple of years. Feel free to peruse my accomplishments within those experiences!

Aercoustics Engineering Ltd
Software Engineering Intern

  • Implemented a construction sound classification tool that reduced company labour time for sound labeling.
  • • Built automated report tools with Python & HTML/CSS to extract relevant info from notable sound events.
  • Developed testing infrastructure in SQL, Docker and Python for internal company database and codebase projects, resulting in full resolution of critical errors and 75% reduction of moderate errors.

Multimedia Lab
Machine Learning Intern

  • Created convolutional neural networks (CNNs) using Python, PyTorch & machine learning with 96% top-1 accuracy, beating state-of-the-art networks by 0.5-1.5%.
  • Implemented computer vision algorithms in a research team of 4 people with NumPy & Pandas that dynamically improve internally-developed metrics.
  • Pending final research paper submission at the CVPR 2021 conference.

U of T Machine Intelligence Student Team (UTMIST)
Project Director

  • Leading a group of 4 developers and leveraging personal background in Toronto real estate to build a user-friendly home price predictor for houses in the GTA.
  • Built a face-recognition tool on a local dataset that achieves 90% top-1 accuracy.
  • Created a recurrent visual network that mimics how humans classify images.


Different projects that I have done in collaboration with peers over the last 2 years. To learn more, hover over a project and click it!

Python algorithm that utilises house images and statistical info as user inputs to predict house prices in range of 20% of actual correct prices.
Product for HackThe6ix that uses machine learning within an app to recommend food recipes from simple fridge images. Received MLH's Best Use of Google Cloud prize.
Top 5 placement in MakeUofT 2020. Software that uses machine intelligence to detect joints and give real time feedback on how to fix your form for different types of exercises.
Hyper-efficient book stacking algorithm that received 3rd place at the UTEK 2020 Programming Competition.
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Contact Me

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