SCS Teaching Faculty Candidate - Bilal Taha

— 12:00pm

Location:
In Person and Virtual - ET - Newell-Simon 4305 and Zoom

Speaker:
BILAL TAHA, Postdoctoral Fellow, Department of Electrical and Computer Engineering, and, Lecturer, Department of Computer Science, University of Toronto
https://www.comm.utoronto.ca/~btaha/

Iterative Gradient-Based Algorithms for Optimization in ML

This teaching demo focuses on Iterative Gradient-Based Algorithms for Optimization in Machine Learning (ML). The lecture will introduce students to the fundamental concepts of gradient descent and ascent, detailing their roles in optimizing ML models. Students will gain an understanding of the mathematical foundations behind iterative gradient methods, including the significance of gradients, learning rates, and the convergence process. The session will also explore different types of gradient descent approaches—Batch Gradient Descent, Stochastic Gradient Descent, and Mini-Batch Gradient Descent—and highlight how advanced variants like Momentum can address the limitations inherent in the standard methods. By the end of the lecture, students will be equipped with the knowledge to effectively explain and differentiate between these optimization techniques and their applications in machine learning. 

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Bilal Taha is currently a postdoctoral fellow in the Department of Electrical and Computer Engineering (ECE) and a lecturer in the Department of Computer Science at the University of Toronto. He earned his Ph.D. in 2023 from the ECE department at the University of Toronto. Previously, he served as a Postgraduate Researcher at the Vector Institute, a Research Intern at the ICUBE Laboratory, University of Strasbourg, and at Amazon Alexa AI. He has received several awards, including the NSERC Postdoctoral Fellowship, Innovators Under 35 by MIT Technology Review Arabia, and the DiDi Chuxing Award for Biometrics. His research interests include machine learning, wearables, and biometrics. Faculty Hosts:  Dilsun Kaynar, Reid Simmons Joint Computer Science Department and CMU Qatar

In Person and Zoom Participation. 

→ Attendance at this talk is restricted to members of the SCS community and relevant CMU stakeholders.

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