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Friday, November 5, 2021 12:00 pm - 1:00 pm EDT (GMT -04:00)

Engineering Graduate Studies Alumni Panel

Join us on November 5 as we welcome Alumni from our graduate programs to speak about the impact their graduate degree had on their career path. This is a great event to attend if you are curious about how a graduate degree in engineering can support you!

Date: Friday, November 5
Time: 12pm-1pm EDT

Register here: https://mailchi.mp/uwaterloo.ca/enggradalumnipanel

Panelists:

As part of the Water Institute's WaterTalks lecture series, Erin Mahoney,
Commissioner of Environmental Services for York Region and Douglas Wright
Engineer-in-Residence will present: York Region’s One Water Story…
recognizing the value of water in all its forms.

Presented by: Baoshi Sun, MASc student, Systems Design Engineering 

Abstract: As one of the most essential factors of learning environment, lighting in classroom has been found to have significant impact on student performance. Moreover, brightness level and correlated color temperature (CCT) are the two key luminous properties that have been examined in many relevant studies. And researchers were increasingly focusing on the diversity of luminous requirements under different learning context.

As part of the Water Institute's WaterTalks lecture series, Amy Pruden, W. Thomas Rice Professor, University Distinguished Professor, Via Department of Civil and Environmental Engineering, Virginia Tech, USA will present: Harnessing 'Omics to Inform Strategies to Mitigate the Spread of Antimicrobial Resistance as a One Water Challenge.

Thursday, February 10, 2022 7:00 pm - 8:00 pm EST (GMT -05:00)

Critical Tech Talk 2: Discriminating Data - In Conversation with Wendy Chun

In her most recent book, Discriminating Data (2021), Wendy Chun reveals how polarization is a goal—not an error—within big data and machine learning. These methods, she argues, encode segregation, eugenics, and identity politics through their default assumptions and conditions. Correlation, which grounds big data's predictive potential, stems from twentieth-century eugenic attempts to “breed” a better future. Recommender systems foster angry clusters of sameness through homophily. Users are “trained” to become authentically predictable via a politics and technology of recognition.