Hi, my name is
Janel Gilani.
I do research and build software stuff.
I’m a software and research engineer seasoned in full-stack development and machine learning applications. I currently work at Amazon Robotics as a Software Development Engineer building systems that powers robotics systems used in fulfillment centers around the world.
About Me
Hello! My name is Janel, and I graduated from the University of Toronto with an Honours Bachelor of Science (3.96/4.0 cGPA). I completed a Computer Science Specialist and Statistics Minor with Co-op, with a dual focus in Artificial Intelligence and Web and Internet Technologies.
When it comes to team environments, I’ve seen a bit of everything: from cutting-edge research labs like Google DeepMind and Noah's Ark Lab, to large financial institutions like Royal Bank of Canada, and now global operations at Amazon Robotics. From ideation and prototyping to deployment and optimization, I’ve contributed at every stage of the software and research lifecycle!
Here is my relevant coursework:
- Software Engineering
- Data Structures & Algorithms
- Web Programming
- Machine Learning
- Computer Networks
- Operating Systems
- Databases
- Computer Vision

Where I’ve Worked
Software Development Engineer @ Amazon Robotics
September 2025 - Present
- Designing and developing software that powers the robotic systems driving Amazon’s global fulfillment centers.
Some Things I’ve Built
PetPal: Pets x Adopters
PetPal is an online platform designed to connect pets in need of adoption with potential adopters. Built using modern web technologies, PetPal offers an intuitive and user-friendly interface for users to explore various pets available for adoption across different shelters.
- React
- Django
- Heroku
- Postman
- SQLite
BudgetBites: Cheap Food at UofT
A desktop application wherein users can find budget-friendly food options on campus based on their preferences, rate restaurants, track their monthly budget, and get food suggestions from the application.
- Java
- MongoDB
- Swing
- Git
ML Student Performance Predictor
Built machine learning models to predict whether a student can correctly answer a specific diagnostic question based on the student’s previous answers to other questions and other students’ responses.
- PyTorch
- NumPy
- scikit-learn
- Matplotlib
Paper: Analysing Voter Turnout
This paper investigates the impact of socio-economic and demographic factors on voter turnout in the 2022 Toronto Municipal Election. We use Bayesian analysis to examine the relationships between a ward’s voter turnout and factors such as its education level, income, unemployment rate, population, and number of subdivisions.
- R
- Bayesian Analysis
- Regression Models
COVID-19 Sentiment Analysis
Designed and implemented an interactive survey to gather insights from over 60 participants regarding their hobbies before and during the pandemic. Utilized the pandas library to conduct lexicon analysis, transforming raw CSV data into quantifiable scores. Created comparative visualizations to analyze trends and findings.
- Python
- Tkinter
- VADER Lexicon
- pandas
- Plotly
What’s Next?
Get In Touch
Whether you have an opportunity for me or just want to connect, feel free to reach out!
Say Hello



