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Wednesday, October 12, 2022 10:00 am - 11:00 am EDT (GMT -04:00)

Seminar: Advances in quantum dot lasers and integration with Si photonic integrated circuits

You are invited by the IEEE Electronics Packaging Society (EPS) Student chapter at University of Waterloo to attend a seminar:

Title: Advances in quantum dot lasers and integration with Si photonic integrated circuits

Speaker: Yating Wan, Assistant Professor, King Abdullah University of Science and Technology

There's growing awareness of the lack of diversity in science and the presence of barriers to inclusion. What factors lead to disparities in representation? Why should we be motivated to effect change? What can we do to change things? Will our actions really make a difference? 

The University of Waterloo along with the IEEE KW Section invites you to a seminar: “Surviving and thriving in today's workplace: A few tips to manage professional development & career security” by Bala Prasanna.

Date: December 1, 2022

Time: 6:00pm to 7:00pm

Location: online (see full details below)

Abstract:

Workplace habits and expectations have changed significantly in the last several years. Surviving and thriving depends on your ability to grasp the broader picture and hone some essential skills.

Wednesday, March 15, 2023 9:30 am - 4:30 pm EDT (GMT -04:00)

Electrical and Computer Engineering Capstone Design Symposium

Alumni, students, employers, industry partners, media, and members of the general public are invited to join us in Engineering 7 for the Electrical and Computer Engineering Capstone Design event

Name: Huixin Jin

Date: Thursday 23rd of March  2023

Time: 4:00pm to 5:00pm (EST)

Location: E5-4047

SupervisorSlim Boumaiza

Attending faculty member: Prof. Raafat Mansour

Title: Millimeter-wave 39 GHz 4x4 Phased Antenna Array with Embedded Near-field Probing Antenna for Performance Enhancement

Abstract:

Name: Sheikh Nooruddin

Date: Wednesday, March 22nd 2023

Time: 10AM - 11AM

Location: online

Supervisor(s): Fakhri Karray, Ali Elkamel, Mark Crowley

Title: On the Design of Efficient Deep Learning Methods for Human Activity Recognition in Resource Constrained Devices

Abstract: