- Why Grad Studies at SFU?
- Programs Alphabetically
- Individualized Interdisciplinary Studies
- Accelerated Master's
- Tuition + Fees
- Visiting + Incoming Exchange
- Awards + Funding
- Graduate Students
- Getting Started
- Understanding Your Role
- Managing Your Program
- Completing + Graduation
- Postdoctoral Fellows
- Life + Community
- Community Guide
- Indigenous Graduate Students
- International Graduate Students
- Professional Development
- Jobs + Volunteering
- People + Research
- Highlights & Awards
- Grad Student Spotlight
- Travel Reports
- Grad Student Profiles
- Participate in Grad Student Research
- News + Events
- Faculty + Staff
- Individualized Interdisciplinary Studies in Graduate Studies
Student Profile: Weina Jin
Computing Science doctoral student in the Faculty of Applied Sciences
I am a Ph.D. student at the Medical Image Analysis Lab in Computing Science, supervised by Prof. Ghassan Hamarneh. My research is on explainable artificial intelligence (AI) for medical image analysis. I came to the AI research field from an unconventional background: I was originally trained as a doctor and also have research experience in human-computer interaction. I bring these backgrounds to my research that aims to build explainable AI techniques that are clinical user-centric.
WHY DID YOU CHOOSE TO COME TO SFU?
SFU has a world-class research faculty in computer vision and human-computer interaction. In addition, it locates in the Great Vancouver where I can enjoy the beautiful scenery and many activities with my family on the west coast.
HOW WOULD YOU DESCRIBE YOUR RESEARCH OR YOUR PROGRAM TO A FAMILY MEMBER?
My research is on developing clinical user-centric explainable AI techniques for medical imaging tasks. As AI becomes increasingly pervasive in our everyday life, such as automatically detecting faces from our smartphone camera, AI technologies also have the potential to transform healthcare by assisting doctors with their clinical tasks and improving their clinical performance. However, the mainstream of AI technologies are basically black-box models, meaning given an input, an AI will output a prediction. But we humans, even the AI developers have no idea of how and why AI makes such a prediction. My research on explainable AI aims to open the mystery box of AI, and make AI technologies more explainable to its clinical users, so that medical practitioners can better understand AI capabilities and can better collaborate with AI for clinical decision support.
WHAT ARE YOU PARTICULARLY ENJOYING ABOUT YOUR STUDIES/RESEARCH AT SFU?
I enjoy the creative research environment at SFU, where it has great support for graduate students' research on academic, financial, social, and emotional aspects.
HAVE YOU BEEN THE RECIPIENT OF ANY MAJOR OR DONOR-FUNDED AWARDS? IF SO, PLEASE TELL US WHICH ONES AND A LITTLE ABOUT HOW THE AWARDS HAVE IMPACTED YOUR STUDIES AND/OR RESEARCH.
I am the recipient of Sulzer (Bingham) Pumps Inc. Graduate Scholarship, Helmut & Hugo Eppich Family Graduate Scholarship, Andrew Wade Memorial in Visual Analytics, Borden Ladner Gervais Graduate Scholarship, and McQuarrie LLP Scholarship. I appreciate the generous funding from the donors, which greatly support me financially and enable me to focus on my research.
HOW WOULD YOU DESCRIBE YOUR PROGRAM/POSTDOC POSITION TO SOMEONE STILL SEARCHING FOR A PROGRAM OR POSTDOC POSITION?
SFU Computing Science has top-notch research in AI and computer vision. I enjoy the change of ideas with like-minded researchers who have a high standard and good taste of what good researches are.
IS THERE ANYTHING ELSE YOU'D LIKE TO SHARE?
If you want to know more about my research, my personal website keeps a record of my research projects at: weina.me
Contact : email@example.com