Education
CILQ: An Evolving Modern Curriculum
The Communications, Information, Learning and Quantum Group (CILQ) is made up researchers in the Electrical and Computer Engineering Department who are working on a diverse set of challenges. Our work is at the forefront of many important emerging technologies and our curriculum is constantly evolving to give our students the skills necessary to succeed in these fields today.
Wireless
Wireless
CILQ continuously modernizes its teaching to be up to date with the developments that impact the careers of our students. A typical example is the recent revamping of the ECE 535 (Wireless Communications) and ECE 635 (Advanced Wireless Communications). These courses form the basis for the jobs many of our students get at manufacturers such as Samsung, Nokia, and Qualcomm, as well as operators like Verizon and AT&T, and many startups. Thus, ECE 535 recently moved the emphasis from the traditional “cellphones” approach to those aspects (such as multi-user scheduling, smart antennas, etc.) that are relevant for internet of things and high-speed communications with smartphones. We also present up-to-date information on the 5G standards (3GPP NR, WiFi 6), and cutting-edge research topics such as massive MIMO and mm-wave communications.
Blockchain
Blockchain
CILQ continuously modernizes its teaching to be up to date with the developments that impact the careers of our students. A typical example is the recent revamping of the ECE 535 (Wireless Communications) and ECE 635 (Advanced Wireless Communications). These courses form the basis for the jobs many of our students get at manufacturers such as Samsung, Nokia, and Qualcomm, as well as operators like Verizon and AT&T, and many startups. Thus, ECE 535 recently moved the emphasis from the traditional “cellphones” approach to those aspects (such as multi-user scheduling, smart antennas, etc.) that are relevant for internet of things and high-speed communications with smartphones. We also present up-to-date information on the 5G standards (3GPP NR, WiFi 6), and cutting-edge research topics such as massive MIMO and mm-wave communications.
Deep Learning
Deep Learning
An EE599 Special Topics class on Deep Learning was offered during the Spring 2019 semester and is similarly scheduled for Spring 2020. It is planned to convert the class to a regular course as part of the ECE department’s new MS degree in Machine Learning and Data Science. This class is intended to complement and build on our more analytical graduate level courses and utilizes a “learning by doing” educational paradigm.With only a minimal programming background and no prior knowledge of machine learning, students developed software for increasing realistic problems as the class progressed. This included classification of facial expressions using convolutional neural networks (CNNs) and language classification of speech using recurrent neural networks (RNNs). This was part of the process of learning to develop and work with large datasets. Students programmed the training of neural networks using just the standard NumPy Python library before learning and utilizing the industry-standard deep learning toolkits (Keras, TensorFlow, and PyTorch).
As the scope of the assignments increased, students moved from training on their personal computers to training in the cloud using GPUs. Amazon Educate generously supported these cloud computing assignments with $15,000 in AWS cloud computing credits provided directly to enrolled students. The class culminated with a Deep Learning Symposium in which student teams presented the results of their self-defined projects to the USC community. In addition to their presentations, students also produced final reports for their projects and YouTube videos.
Quantum Information
Quantum Information
More information coming soon!
Published on September 20th, 2017
Last updated on February 16th, 2022