University of Arizona Electrical, Computing, and Software Engineering

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Where electrical, computing & software engineers build what's next for Arizona and beyond. News & World Report.

Electrical and computer engineers power the technologies that define our world—and the University of Arizona’s ECE department is at the forefront. Our faculty are internationally recognized researchers tackling society’s biggest engineering challenges while helping make Arizona a leader in innovation and high-tech growth. With 50 faculty members, we’re the largest department in the College of Engineering and consistently ranked among the nation’s top ECE programs by U.S. We offer bachelor’s, master’s, and PhD degrees in electrical and computer engineering, computer science and engineering and software engineering—with flexible emphasis areas so students can focus on what inspires them most.

10/08/2026

Congratulations to all our ECSE faculty and staff who are celebrating service milestones! 🎉

The full list of employees include:

Rozanne Canizales, 45 years
Jerzy Rozenblit, 40 years
Jeffrey Rodriguez, 35 years
Tami Whelan, 35 years
Curtis Booth, 30 years
Kathleen Melde, 30 years
Bane Vasic, 25 years
Ali Akoglu, 20 years
Hao Xin, 20 years
Tosiron Adegbija, 10 years
Siyang Cao, 10 years
Ming Li, 10 years
Ravi Tandon, 10 years

Thank you for your years of service and for making ECSE what it is today. ❤️💙

Bear Down, and here’s to the milestones still to come! 🐻⬇️

09/16/2026

What's really happening inside tools like ChatGPT and Claude? Now's your chance to find out.

Join the School of Electrical, Computer, and Software Engineering for AI SPARK: Opening the Black Box on Wednesday, October 7, from 3 to 5 p.m. at the UA Campus Store, lower level. We'll go beyond the hype and dive into the real foundations of large language models – the math, the probability and the patterns that make them work.

Open to all U of A students, faculty and staff. Free food and light refreshments included! Hosted by assistant professors Huanrui Yang and Jyotikrishna Dass.

Register to attend: https://events.trellis.arizona.edu/en/f44lNu67/ai-spark-opening-the-black-box-unlocking-the-mystery-of-large-language-models-5a3UV43Gbxx/overview?publication=20260916&utm_campaign=University+of+Arizona+Electrical%2C+Computing%2C+and+Software+Engineering&utm_content=What%27s+really+happening+i&utm_medium=social&utm_source=facebook

09/10/2026

Congratulations to Xiaolong Ma, assistant professor in the School of Electrical, Computing, and Software Engineering, for winning a five-year, $500,000 National Science Foundation CAREER award to create safety protocols for generative AI models!

The NSF CAREER grant, one of the agency’s most prestigious awards, honors early-career researchers who serve as academic role models and show leadership potential.

Ma has devoted much of his research to developing privacy-preserving, safe and controllable learning methods for generative models.

“This project represents an important step toward my long-term vision of building trustworthy and controllable generative AI,” he said.

His next tool will train AI algorithms to exclude harmful content without degrading performance.

“It focuses on developing machine unlearning techniques for diffusion models, enabling AI systems to selectively forget unwanted knowledge,” said Ma.

Ma’s tool, when complete, will be available to generative AI model builders to efficiently sweep their algorithms before releasing them to the public.

“Xiaolong’s outstanding work on scalable, efficient, and trustworthy artificial intelligence addresses a critical frontier in advancing AI, helping make increasingly powerful AI systems more practical, reliable and responsible,” said Michael Wu, Thomas R. Brown Leadership Chair and head of ECSE. “As one of the school’s AI experts, his success also highlights the growing strength and breadth of ECSE’s expertise in AI.”

Learn more about Ma and his research: https://news.engineering.arizona.edu/news/nsf-career-awardee-protects-ai-users-harmful-content?publication=20260910&utm_campaign=University+of+Arizona+Electrical%2C+Computing%2C+and+Software+Engineering&utm_content=Congratulations+to+Xiaolo&utm_medium=social&utm_source=facebook

09/08/2026

The National Science Foundation has awarded $4.6 million to a University of Arizona and University of New Mexico team to build MESA – a new AI-powered platform that helps researchers find exactly the data they need, from massive scientific archives, in minutes rather than months.

"It will help researchers be more effective, make discoveries more efficiently and optimize their workflows," said David Ebert, U of A's chief AI and data science officer.

Among the researchers set to benefit is ECSE assistant professor Jingdi Chen, whose network slicing algorithms for 5G/6G cellular networks will be among MESA's first datasets.

U of A will use its $2.1 million share to build the platform's interface and cloud storage system, with collaborators Barney Maccabe and Lei Cao, hosting datasets on everything from environmental science to black holes.

Learn more about the project: https://news.arizona.edu/news/nsf-awards-46m-ai-platform-speeding-scientific-discovery?publication=20260908&utm_campaign=University+of+Arizona+Electrical%2C+Computing%2C+and+Software+Engineering&utm_content=The+National+Science+Foun&utm_medium=social&utm_source=facebook

09/02/2026

Our ECSE online Bachelor of Science in Software Engineering program was just recognized by OnlineU as one of the best online software engineering bachelor's programs for 2026, and rated #1 by students! 🎉

With a 3.99/5 overall rating and 92% of students saying it helped their careers, this ranking reflects the hard work of our students, alumni, and faculty. 👏

Learn more: https://www.onlineu.com/degrees/software-engineering

09/01/2026

A $500K National Science Foundation (NSF) grant has been awarded for the project, “GOALI: A Community-Driven Benchmarking Framework for Trustworthy Generative AI in Architecture, Engineering and Construction.”

Led by Huanrui Yang (Co-PI), assistant professor of Electrical, Computing, and Software Engineering and Liang Zhang (PI), assistant professor of Civil Engineering and Engineering Mechanics, the project will establish a community-driven framework for evaluating and validating generative AI systems before they are deployed in real-world, safety-critical engineering applications.

Generative AI is increasingly being applied to engineering design, simulation, cost estimation, contract development and regulatory compliance. While these technologies offer significant opportunities, AI-generated outputs can also contain convincing but incorrect information that may be difficult to detect. In safety-critical settings, such errors can have serious consequences for buildings, infrastructure, and public safety.

The project will also contribute to workforce development by preparing students and practicing engineers to critically evaluate AI-generated results and make informed decisions about their use in professional practice. 🧑‍💻

08/27/2026

Exciting news! 🚨

The Department of Electrical and Computer Engineering is now the School of Electrical, Computing, and Software Engineering (ECSE).

This milestone reflects over a century of growth – from our roots in 1910 to today, where we bring together three academic programs in one school: Electrical and Computer Engineering (ECE), Computer Science and Engineering (CSE), and Software Engineering (SFWE). Along with new programs in AI Engineering and Quantum Information Science and Engineering (QISE).

With 800+ students and 47 faculty members leading research in AI, cybersecurity, quantum technology, robotics, and more, ECSE is shaping the next generation of engineers and innovators.

🐻⬇️

08/26/2026

The National Science Foundation has renewed the Center for Quantum Networks (CQN) for Years 7-10, extending its mission through 2030. The University of Arizona serves as a CQN hub while the University of Maryland serves as the lead institution for this national center. ⚛️

CQN brings together computer scientists, electrical and optical engineers, physicists, materials scientists, and social scientists to build the foundations of the quantum internet – a future infrastructure connecting quantum computers, sensors, and other quantum-enabled devices across local, metropolitan, and long-distance networks. The center's researchers are developing fault-tolerant quantum repeaters and network architectures designed to work alongside, and eventually interconnect with, today's classical internet.

For this next phase, UA's team includes:

➡️ Daniel Soh (PI) and Mehmetcan Akbulut, Optical Sciences
➡️ Noel Hennessey, ENGAGED, College of Engineering
➡️ Narayanan Rengaswamy, ECSE
➡️ Xiaodong Yan, MSE & ECSE

The center will continue to support ECSE PhD student Sijie Cheng, who has been with CQN since Fall 2022. 🙌

Along with this renewal, Rengaswamy will lead CQN's Annual Winter School, working alongside Noel Hennessey, the center's Director for Education and Workforce Development.

08/18/2026

Big step forward for quantum computing. ⚛️

University of Arizona assistant professor Narayanan Rengaswamy and graduate student Zhuangzhuang Chen are helping tackle one of quantum computing’s biggest challenges: making quantum systems more reliable.

Rengaswamy is a core member of a UCLA-led team awarded $4 million by the National Science Foundation through the National Quantum Virtual Laboratory (NQVL) design competition. The project is led by Eric Hudson, professor of physics and astronomy at UCLA and principal investigator.

Rengaswamy and UC San Diego associate professor Yufei Ding co-lead the project’s quantum error correction pillar, developing methods to make quantum computers more efficient and reliable.

Chen is helping Rengaswamy develop error-correction mechanisms that can operate across multiple logical qubits simultaneously. Their approach could help reduce the physical qubits needed for a 60-logical-qubit system from the 10,000+ currently thought necessary to roughly 1,000–2,000.

“I’m very excited to be working on this transformative project that lets us think full stack from algorithms down to the physics of the hardware,” said Rengaswamy. “I believe the work we are doing will speed quantum computing’s reliability to perform quantum simulation of various physical processes faster than any current classical computer.”

By bringing together algorithms, error correction, software and hardware architecture, the team is working toward more efficient, reliable and practical quantum computing.

Read more about the project: https://ece.engineering.arizona.edu/news-events/powering-quantum-u-engineers-collaborate-4m-nsf-award?publication=20260818&utm_campaign=University+of+Arizona+Electrical+and+Computer+Engineering&utm_content=Big+step+forward+for+quan&utm_medium=social&utm_source=facebook

08/14/2026

The University of Arizona has awarded nearly $1 million to a dozen faculty research teams developing artificial intelligence tools to improve health care. Our electrical, computing, and software faculty are working on half of these teams, helping to benefit diagnosis, treatment, and patient care.

Our faculty are involved in six funded research teams:

➡️ Ali Bilgin: "Leveraging Multimodal AI to Standardize Deceased Donor Kidney Evaluation"
➡️ Ehsan Azimi: "AI-Driven Surgical Excellence: Multimodal Digital Twins in Surgical Training"
➡️ Eungjoo Lee: "AI-Driven Image Classification for Deep Vein Thrombosis Diagnosis"
➡️ Marwan Krunz: "AI-Based Prediction of Drug Response in Colorectal Cancer"
➡️ Janet Roveda: "Remote Ecosystem for Physics-Aware Intelligent Rehabilitation (REPAIR)"
➡️ Janet Roveda: "Precision Equanimity: AI-Enabled Disentanglement of Metabolic and Psychophysiological Arousal for Real-Time Stress Regulation"

“AI is transforming health care, and I am very proud to see our ECSE faculty contributing their expertise to six of the 12 projects supported through this university-wide initiative,” said Michael Wu, Head of the School of Electrical, Computing, and Software Engineering. “These projects demonstrate the breadth of our faculty’s work in AI, spanning areas such as medical imaging, surgical training, cancer treatment, rehabilitation, and personalized health. ”

🔗: https://ece.engineering.arizona.edu/news-events/ecse-faculty-members-leading-new-ai-healthcare-teams?publication=20260814&utm_campaign=University+of+Arizona+Electrical+and+Computer+Engineering&utm_content=The+University+of+Arizona&utm_medium=social&utm_source=facebook

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