My research interests lie in the realm of social networks, modern media, and politics! Currently, I am a research assistant to Dr. Hanna Morris at the University of Toronto’s School of the Environment. My work focuses on developing computational methods to obtain relevant data on social networks and podcasts, to explore the diversity in climate perception and communication in America.
I’ve been exploring different methods like web scraping, public datasets, and APIs to learn more about social networks. One area I find particularly fascinating is using real and AI-driven data to simulate social networks with graph theory—to model information bubbles, misinformation, and diversity in climate perception. Inspired by research on the structural properties of social networks, I’ve been exploring how these tools can reveal patterns in influence, polarization, and the spread of information, especially with limited access to real data.
Software Engineering Projects
Culinary Connections
Collaborators: Ayusha Thapa, Alisha Zariff
Tools: Python, HTML, Folium, Tkinter
Culinary Connections is a Python-based restaurant recommendation and social networking application. Users can customize 9+ preferences such as general location, cuisine type, takeout availability, star rating, and more to be matched with restaurants displayed on a map. Users can also connect with each other to get tailored recommendations. We simulated this aspect of the program by creating dummy users associated with each restaurant.
I processed a Yelp dataset of 150,000+ businesses and 1.2M+ attributes, and created tree data structures and graph traversal methods to model restaurant relationships and attributes.
We created this application during NewHacks 2024, an annual hackathon at the University of Toronto. Harvest Aid supports farmers in remote areas to enable efficient resource pooling during times of need— and especially during natural disasters. Just make an account, browse listings by keyword or category, and click a listing to contact the farmer and arrange a trade or purchase.
Use the + button to create a listing and share your resources. I integrated the front and back ends by learning Flask at the hackathon itself!
Developed the 1990 game Dr. Mario in MIPS assembly, and learned about assembly syntax, memory management, and hardware interaction.
We configured bitmap displays, managed memory-mapped I/O for reading keyboard input and writing pixel data, and implemented game features such as gravity, collision detection, 3 levels, and pause/game over/restart/quit functionality.
This was a very fun way to learn about memory, processors, and low-level programming!
Blackjack Simulator
Collaborators: Pooja Mangra, Jacob Liso, Matt Dahlgren, Andrei Shvorkets
Tools: Java
The aim of this simple project was learning about the SOLID design principles and clean architecture, which is why I included the UML diagram above. Game modes include Free Play Mode, Assisted Mode, and Learn Mode, along with account creation and a post-game report.
I gained valuable insights into software design, documentation, and the critical role of code reviews and clear communication. I also learned the importance of setting realistic goals and prioritizing quality over quantity when working within tight deadlines.
