Final year undergrad student at University of Toronto pursuing:
Hi there! Thank you for taking a look at my website. I am a final year undergrad student at University of Toronto pursuing Computer Science Specialist program with a focus in Artificial Intelligence and a minor in Statistics. I have gained experince in the field of software development and machine learning through internships and research experiences (please go though my the experience section of my website to take a look at my work).
I enjoy taking part in sports and have been playing Tennis since the age of 4. It has been a big part of my life since I was playing in the professional circuit until university. Now, I play for University of Toronto's Varisty Tennis team. On the academic side, I enjoy taking part in hackathons and building side projects with my friends as it is an opportunity for me to learn a new skill or build an innovative project.
I love talking to people and sharing experiences. So, if you have
something to share or just want to say hi, please feel free to reach
out to via email or LinkedIn (refer to contact section for details).
Thank you again for taking the time to learn about me :)
Enhanced the search autocomplete on
amazon.com to reduce
friction while discovering the beauty products for more than
2 million customers monthly
and help them personalize their search query.
Developed the backend of the project using AWS CDK pipeline and used Lambda function to populate the DynamoDB entries using AWS IAM and S3, and created the ML architecture using Amazon's internal tools.
4 Android apps from
scratch that implemented
TFLite models pipeline & PnP algorithm for gaze
tracking, which were used by over 200 developers in China and
Canada office for validating the ML models.
Researching and Implementing deep learning models and its pipelines to solve the problem of gaze estimation using 3D-face-based and eye-based models using OpenCV in TensorFlow in a team of 7 developers.
Developed a model to estimate the causal effects of tweets, scraped using Twitter API, on companies' output data (bonds, equity, innovations, product's portfolios, etc) using TensorFlow in a team of 3 students
Designed a machine learning model capable of performing automatic lesion boundary detection using dermoscopy images. Devised deep learning models in PyTorch (Python) using architectures like UNet, Attention Net, Pool Nets and Att-UNets and tested them on the collected dataset to find the best architecture for the project
Worked as a Software Developer Engineer for HypeDocs
to work on the
front-end and back-end of the HypeDocs.co software.
Implemented functionalities in the HypeDocs software like pop-modals, csv importer, csv download and batch writes to support the launch of Public Page feature, which is now used by 70% of users (28% after first week) Improved reliability by migrating the data of 300 customers to Google Firebase and used netlify for the launch
Taught machine learning concepts to
300+ students from
the countries of
East and West Africa
including Kenya, Ghana, Nigeria, Algeria, and Mexico under
the LearnAI in Africa initiative. "LearnAI in Africa" is an
introductory ML educational program with an aim to encourage
affordable ‘AIforGood’ employment and is executed in
collaboration with organizations like AI Commons, McGill
University, Runmila AI Institute and University of Toronto.
Led a team of 40 people from University of Toronto's Artificial Intelligence group, working towards smooth execution of the program.
I will be working as an Executive for the Sponsorship team of University of Toronto [UofT] Hacks hackathon 2022.
Led a team of 20 students
responsible for UofT AI's marketing and promotion
operations for the annual
StartAI conference with almost 2,000 participants.
Contributed to the organization of an international machine learning competition with over 100 students from teams from the top 25 universities in North America (Stanford, MIT, Carnegie Mellon, UC Berkeley, etc.) with a budget of $100,000 and partnerships with Google AI, IBM, DeepMind, AccuWeather, Vector Institute, etc.
Undertaken planning and execution of a
Machine learning project
in a team of 6 students, with the aim to create a model
capable to transferring the style of a piece of music as
Academic Research projects 2020-21
cohort of University of Toronto Machine Intelligence
Student Team [ UTMIST ].
This project was made using tensorflow libraries like librosa, CNN's and was inspired by the process of style transfer of images/paintings.
I worked as a peer leader for New College Orientation
progarms that run throughout the academic year. New
College orientation includes programs like
E-mentorship, IGNITE, SPROUT and New1X.
I was a participant of New College orientation in my first year and that it was immensely useful for me as it helped me transition smoothly to university life and also helped me make friends and get comfortable with the canadian culture. Thus, I decided to give back to the college volunteering as a Peer Leader for academic session 2020-21 and 2021-22 . As a Peer Leader, I get to organize events with 100+ participants, answer incoming student's questions about university life and academic, and be a mentor for a group of 15 incoming students .
This was the Final project for CSC207: Software Design course.
In order to complete this project, I worked in a team of
7 developers over the
period of 2 months.
This is a software which can be used to schedule and manage participants for conferences. This projects is made using Java and has a complete GUI, made using Java Swing. This project is made following the principles of software design including clean archietecture and SOLID.
Research project made in a team of
5 students for
Academic track 2020-21 cohort projects.
Made a model capable of transferring the style of a piece of music while preserving its content using tensorflow’s Librosa library, CNNs and spectrograms
This was the Final project for CSC258: Computer Organization
course where I recreated the Doodle jump game using low level
Assembly programming language.
This game includes Fancier Graphics, Dynamic on-screen notifications, Scoreboard and interactive Lethal creatures/opponents.
Using NEAT Python to learn to play Flappy Bird game. This code uses search and optimise technique called genetic algorithm, which creates a particular number of random configurations and the best of them is used to create the next generation of neural networks. As we repeat the process, we observe that the performance improves.
In recognition of my academic excellence as a U of T student, I was named a Dean's List Scholar in the Faculty of Arts & Science for the 2020-21 and 2019-20 fall /winter academic year.
Awarded to the University's most outstanding International secondary school students on admission.
Awarded to the University’s most outstanding secondary school students on admission.
Awarded by University of Waterloo, Canada for being among top 25% students in Euclid Competition.
Selected among top 0.1% of students from India in Mathematics by CBSE on the basis of CBSE board's 12th standard Mathematics exam, in which I got a perfect score of 100.
Recepient of the prestigious Best Tennis Player Award by Rajasthan's State Sports Department (Women's category).