Show Notes

• (02:06) Azin described her childhood growing up in Iran and going to a girls-only high school in Tehran designed specifically for extraordinary talents.
• (05:08) Azin went over her undergraduate experience studying Computer Science at the University of Tehran.
• (10:41) Azin shared her academic experience getting a Computer Science MS degree at the University of Toronto, supervised by Babak Taati and David Fleet.
• (14:07) Azin talked about her teaching assistant experience for a variety of CS courses at Toronto.
• (15:54) Azin briefly discussed her 2017 report titled “Barriers to Adoption of Information Technology in Healthcare,” which takes a system thinking perspective to identify barriers to the application of IT in healthcare and outline the solutions.
• (19:35) Azin unpacked her MS thesis called “Subspace Selection to Suppress Confounding Source Domain Information in AAM Transfer Learning,” which explores transfer learning in the context of facial analysis.
• (28:48) Azin discussed her work as a research assistant at the Toronto Rehabilitation Institute, working on a research project that addressed algorithmic biases in facial detection technology for older adults with dementia.
• (33:02) Azin has been an Applied Research Scientist at Georgian since 2018, a venture capital firm in Canada that focuses on investing in companies operating in the IT sectors.
• (38:20) Azin shared the details of her initial Georgian project to develop a robust and accurate injury prediction model using a hybrid instance-based transfer learning method.
• (42:12) Azin unpacked her Medium blog post discussing transfer learning in-depth (problems, approaches, and applications).
• (48:18) Azin explained how transfer learning could address the widespread “cold-start” problem in the industry.
• (49:50) Azin shared the challenges of working on a fintech platform with a team of engineers at Georgian on various areas such as supervised learning, explainability, and representation learning.
• (51:46) Azin went over her project with Tractable AI, a UK-based company that develops AI applications for accident and disaster recovery.
• (55:26) Azin shared her excitement for ML applications using data-efficient methods to enhance life quality.
• (57:46) Closing segment.

Azin’s Contact Info

• Website
• Twitter
• LinkedIn
• Google Scholar
• GitHub

Mentioned Content

Publications

• “Barriers to Adoption of Information Technology in Healthcare” (2017)
• “Subspace Selection to Suppress Confounding Source Domain Information in AAM TransferLearning” (2017)
• “A Hybrid Instance-based Transfer Learning Method” (2018)
• “Prediction of Workplace Injuries” (2019)
• “Algorithmic Bias in Clinical Populations — Evaluating and Improving Facial Analysis Technology in Older Adults with Dementia” (2019)
• “Limitations and Biases in Facial Landmark Detection” (2019)

Blog Posts

• “An Introduction to Transfer Learning” (Dec 2018)
• “Overcoming The Cold-Start Problem: How We Make Intractable Tasks Tractable” (April 2021)

People

• Yoshua Bengio (Professor of Computer Science and Operations Research at University of Montreal)
• Geoffrey Hinton (Professor of Computer Science at University of Toronto)
• Louis-Philippe Morency (Associate Professor of Computer Science at Carnegie Mellon University)

Book

• “Machine Learning: A Probabilistic Approach” (by Kevin Murphy)

Note: Azin and her collaborator are going to give a talk at ODSC Europe 2021 in June about a Georgian’s project with a portfolio company, Tractable. They have written a short blog post about it too which you can find HERE.

This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit datacast.substack.com/subscribe