Nine U of T Engineering master’s students are among 66 recipients from across Ontario to receive Vector Scholarships in Artificial Intelligence (VSAI) by the Vector Institute.
The Vector Institute supports Ontario’s growing artificial intelligence (AI) ecosystem through a number of initiatives, including scholarships to increase the number of graduates from AI-related master’s programs. The VSAI are worth $17,500 and Vector scholars are invited to various networking and professional development events at the Institute throughout the year.
U of T Engineering Vector scholars are:
- Matthew Crowson (MIE)
- Ke Dong (UTIAS)
- Daniel Dworakowski (MIE)
- Salma Emara (ECE)
- Yan Fu (ECE)
- Adam Hall (UTIAS)
- Sepehr Samavi (UTIAS)
- Xiaodan (Serina) Tan (ECE)
- Jeremy Wong (UTIAS)
Vector scholar Yan Fu (MASc candidate) is working with her supervisor, Professor Ashish Khisti (ECE), to make AI-based computer algorithms — such as deep learning and neural networks — more robust and safe from attackers.
“We know that one way to improve the robustness of machine learning models is to apply what’s called a current inversion regularizer method — but limitations in memory make it difficult to apply this method to large machine learning models,” says Fu.
This leaves current machine learning models vulnerable to hacking, including dataset tampering that can produce incorrect results. Fu is focusing on designing new techniques to prevent these attacks that could be scaled up to large machine learning models.
“The Vector Scholarship in Artificial Intelligence will enable me to focus on really interesting AI research challenges,” says Fu.
The inaugural cohort of Vector scholars was celebrated at a lunch hosted by the Canadian Club on Dec. 13 where Ed Clark, Chair of the Vector Institute, delivered a speech on the progress and potential of Canada’s AI strategy.