Current graduate students

SE2023 student Vikram Subramanian won first place in the ACM undergraduate student research competition at ICSE 2020 for his work titled An empirical study of first-time open source contributors on Github, which was supervised by Prof Mei Naggapan. Great work!
 

SE students Ethan Chen, Samuel Hao, Emily Tao, William Wen, and Yifei Zhang are part of the team on Flatten.ca, which is a website to crowd-source COVID-19 symptom distribution. This data might help researchers and the public to flatten the curve. The team also includes students from UWaterloo CS and other universities.

Monday, March 9, 2020

SE Students win first at CEC

SE2020 students Jasper Chapman-Black, Céline O'Neil and Sean Purcell won first-place in the Canadian Engineering Competition Programming Challenge. The team developed an algorithm to simulate a drone reconstructing a broken 3D model, determined how to move the pieces back into place and created a visualization for it.

Monday, January 27, 2020

SE Students Win First at OEC

SE2020 students Jasper Chapman-Black, Céline O'Neil and Sean Purcell won first place in the Ontario Engineering Competition (OEC) Programming Competition. The team developed a system to control an hour-by-hour simulation of power generation in Ontario. “We combined a control system and a linear programming solver to pick the optimal combination of power sources to use, minimizing cost and CO2 emissions," says Purcell.

Thursday, September 5, 2019

SE Students Organize Citizen Hacks

This weekend in Toronto, a group of Software Engineering students will be running Citizen Hacks, a new hackathon about privacy and socially beneficial technology. The event encourages youth to tackle the challenge of privacy in technology and begin to develop a design orientation that considers technology’s broader social impacts.

SE Capstone team TagBull aims to harness the power of video game players to train artificial intelligence systems. An AI system for an autonomous vehicle, for example, might be trained to recognize pedestrians from thousands of photos of street scenes in which the pedestrians have been labelled by a person who plays video games. The gamer would earn in-game rewards for their efforts, and the dataset owner would pay TagBull and the video game company for the labelling work.

SE Capstone team TagBull aims to harness the power of video game players to train artificial intelligence systems. An AI system for an autonomous vehicle, for example, might be trained to recognize pedestrians from thousands of photos of street scenes in which the pedestrians have been labelled by a person who plays video games. The gamer would earn in-game rewards for their efforts, and the dataset owner would pay TagBull and the video game company for the labelling work.