Engineers in academia or in industry with an interest in power grid modernization can learn the latest about sensor technologies and innovative use cases of various sensor data in a new book. 

Smart Grid Sensors: Principles and Applications (Cambridge University Press), published in April 2022 by professor of Electrical and Computer Engineering Hamed Mohsenian-Rad, covers smart grid sensors, a component of electrical power grids that use real-time monitoring to lower costs, save energy, integrate renewable energy resources, and improve reliability, security and resiliency. The book’s contents enhance knowledge in the area of Energy, Environment and Sustainability, one of 12 key research themes at the Marlan and Rosemary Bourns College of Engineering. 

Currently, there is a lot of international interest in modernizing the electric power infrastructure, including the Biden administration’s “Building a Better Grid” initiative to catalyze the nationwide development of new and upgraded high-capacity electric transmission lines.

A big part of this is understanding how to obtain and analyze a wide range and a large volume of data from traditional and state-of-the-art smart grid sensors, the crux of Mohsenian-Rad’s book. This includes the analysis of abnormalities and incipient failures, i.e., problems that are in their early stages but can lead to potential catastrophic failures in the future. 

The book addresses data-driven and intelligent methods for using sensor measurements and topics such as smart meters, synchronized phasor measurements, synchronized waveform measurements, situational awareness, probing and working with off-domain measurements.

Ultimately, Mohsenian-Rad says, the book is a gateway to understanding the broader subject of smart grid development and the field of big data in power systems.  

The book provides examples, exercise questions, and sample data sets, with emphasis on real-world smart grid problems and engineering scenarios, as well as step-by-step explanations for data-driven and mathematical methods used to employ measurements from various sensor technologies in important applications. Many of the examples in this book are inspired by the author’s research activities, and several terabytes of sensor measurements that he has been working on over the past decade.

The online version of the book is publicly available to UC Riverside faculty and students here. Others can access the book at Cambridge University Press here.

Mohsenian-Rad is Bourns Family Faculty Fellow, associate director of the Winston Chung Global Energy Center and director of the Smart Grid Research Lab. In 2020, he was named as Fellow of the Institute of Electrical and Electronics Engineers (IEEE), an honor that is conferred by the IEEE Board of Directors upon a person with an extraordinary record of accomplishments. Mohsenian-Rad has received several awards in research and teaching, including the CAREER Award from the National Science Foundation (NSF), the Distinguished Teaching Award from the Marlan and Rosemary Bourns College of Engineering, and Best Paper Awards from multiple IEEE conferences.

The new major complements a robotics master’s degree unveiled in 2021

Five programs at the University of California, Riverside’s (UCR) Marlan and Rosemary Bourns College of Engineering (BCOE) moved up in rank in the 2023 U.S. News & World Report Best Engineering Graduate Schools Rankings. Designed to help prospective students identify universities for furthering their education beyond a Bachelor’s degree, the Best Graduate Schools rankings evaluate programs in a variety of disciplines, including business, education, engineering, law, medicine, and nursing.

“This rise in rankings mirrors the tremendous growth our engineering college has had in recent years,” said Christopher S. Lynch, Dean of the Marlan and Rosemary Bourns College of Engineering. “The high-quality research expertise of our faculty and students, the launch of new national research centers, and the support from government agencies and industry partners make BCOE an excellent place to earn a graduate degree.” 

Among both public and private universities, Chemical and Environmental Engineering moved up four spots to No. 48, Electrical and Computer Engineering moved up three spots to No. 63, Mechanical Engineering moved up two spots to No. 75, Materials Science and Engineering moved up two spots to No. 66, and Computer Science and Engineering and Computer Engineering moved up one spot to No. 50.

Among public universities, all seven BCOE programs, including the above plus Bioengineering, were placed among the top 50 public programs in their respective categories. Furthermore, within these, four are within the top 40 public programs: Chemical and Environmental Engineering, Computer Engineering, Computer Science and Engineering, and Electrical and Computer Engineering.

“Through graduate research and education programs, BCOE continues to meet the demand for engineers who can contribute to the technological advancements important to building a more efficient and safer world,” said Charles Wyman, Associate Dean of Research and Graduate Education at BCOE. “Our master’s and doctoral students are provided with mentorship and resources to hone their skills and become the problem-solvers needed to face tomorrow’s challenges.”

In 2021, the college continued to expand its graduate education offerings to meet the growing need for expertise in such fields as artificial intelligence and sustainability. The college established a new Robotics Master’s degree program, the first of its kind in the UC system, to offer interdisciplinary courses from the departments of Computer Science and Engineering, Electrical and Computer Engineering, and Mechanical Engineering.

In addition, the department of Chemical and Environmental Engineering added a new Master’s degree concentration in Air Quality Engineering that focuses on air pollution causes, impacts, and controls. Students in the program benefit from access to the College of Engineering Center for Environmental Research and Technology (CE-CERT), a cutting edge research center, as well as BCOE’s long-standing partnership with the California Air Resources Board (CARB), which opened its new state-of-the-art Southern California headquarters near the UCR campus this past fall.

Students interested in learning more about the college’s graduate programs and how to apply can visit https://graduate.engr.ucr.edu/. The deadline to apply for fall 2022 enrollment for all programs except Computer Science is June 1, 2022 for international students and August 1, 2022 for domestic students.

For more information about BCOE’s rankings, visit https://www.engr.ucr.edu/about/facts-rankings.  

Two UC Riverside experts explain how carbon capture and utilization technologies work, and what needs to improve for them to deliver on their promise

Assistant professor of electrical and computer engineering Basak Guler at the Marlan and Rosemary Bourns College of Engineering (BCOE) at the University of California Riverside (UCR) has been awarded a $540,000 National Science Foundation (NSF) CAREER Award to develop efficient, secure and trustworthy machine learning applications. NSF CAREER awards are awarded to assistant professors to fund research that is expected to form a firm foundation for a lifetime of leadership in integrating research and education. 

In short, machine learning is a subfield of artificial intelligence, which uses data and algorithms to imitate human behavior. Collaborative machine learning allows multiple data owners to jointly train machine learning models, to increase the volume and diversity of data.

While collaborative machine learning opens exciting possibilities, it can get tricky when used for privacy-sensitive data in the real world: things like healthcare records, financial transactions, or location data.

With this NSF grant, Guler aims to solve this problem by developing novel machine learning techniques that simultaneously protect the privacy of sensitive data. Typically, this has been limited by several major barriers, including the communication bottleneck – when there is not enough capacity to accommodate the current volume of traffic – security, and trustworthiness. 

Guler’s goal is to enable privacy-aware machine learning applications that feature three main characteristics: 1) accessible by users with limited bandwidth and computing power; 2) secure against adversaries; and 3) fair in its decisions towards all communities in society. 

Finally, to help facilitate a diverse machine learning workforce, Guler will develop mentorship opportunities for undergraduate students, new undergraduate and graduate courses and machine learning workshops for K-12 students and teachers.  

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