RSVP by November 5 to uoft.me/realtalk

You’re invited to a night of Real Talk with engineering alumni about the intersection of engineering skills and social change. Equip yourself with knowledge that can help you make decisions about when to act for social change versus when to step back, learn how to find your way when you want to contribute your engineering skills but don’t know how, and better understand how engineers can strike a balance between supporting others and empowering themselves to lead.

This night will offer:

• Tools and take-aways from working alumni that you can use as you decide on and a plan a course to contribute to social justice initiatives with engineering skills and expertise.
• Find out how engineering alumni have empowered themselves,
• The hard lessons they’ve learned about social change work, how they’ve adjusted their approaches and persevered
• The power of deep listening
•  A chance for you to plot your own steps towards empowering yourself and others in the face of overwhelming projects for systemic change, including preliminary learning.

U of T Engineering alumni, join us for this monthly series.

This special event will showcase some of the innovative and progressive research underway at U of T Engineering.

With professors from different departments sharing their expertise and research, you’ll get a taste of the diversity of our Faculty’s research.

Featured speakers:

Upcycling CO2: Achieving energy storage and addressing persistent emissions with renewable electricity, Professor David Sinton (MIE)

Supporting Student Success: Increasing Access to Inclusive Global Research Experiences, Professor Elham Marzi (ISTEP)

Pi in the Sky: Drone-delivered defibrillators for out-of-hospital cardiac arrest, Professor Timothy Chan (ISTEP)

Read the abstracts and register for this free and exclusive event.

U of T Engineering alumni, join us for this monthly series.

Artificial Intelligence (AI) is now a part of the standard physical scientist’s tool kit, and it is regularly used to discover exciting new materials and processes. But AI is famously fickle, susceptible to data set bias and imbalance, subject to information leakage during training, and reliant on humans to evaluate its performance.

Professor Jason Hattrick-Simpers (MSE) discusses best practices for the implementation of AI techniques in the field of materials science, the challenges and successes of his research, and why he believes that robots can help us learn to better trust AI.

Read the abstracts and register for this free and exclusive event.