University of California, Riverside

How this program compares

At an estimated $21.0K in total tuition, the PhD in Electrical Engineering – Intelligent Systems sits roughly 76% below the $87.2K average for AI doctoral programs in our database — placing it in the 3rd percentile on cost among the 36 we track at this level. It runs on a full-time schedule (on-campus).

Admission Snapshot

Typical admitted student: Applicants typically hold a bachelor's degree in electrical engineering or a closely related field with a strong GPA (3.5+). A master's degree in electrical engineering is preferred but not always required; applicants should demonstrate research experience, strong mathematical foundations, and clear research interests aligned with intelligent systems.

About This Program

This doctoral program focuses on advanced research in intelligent systems that can sense, reason, and act in real-time within complex environments like smart grids. Coursework concentrates on Computer Vision and Machine Learning. Most students complete it in about 5 years.

Budget planners should note $21.0K estimated total tuition (3rd percentile among AI doctoral programs, below the $87.2K average). That makes it one of the more affordable options for students weighing return on investment.

It is one of 65 AI-related programs we track in California, of which about 37% offer an online option. On price, it comes in cheaper than about 73% of the California programs in our data, where typical tuition runs near $63.3K.

Graduates frequently move into roles such as AI Research Scientist, with reported salaries around $125,000.

Design, develop, and optimize intelligent control systems and autonomous agents for real-world applications.

Career Outcomes

Graduates of University of California, Riverside's PhD in Electrical Engineering – Intelligent Systems most often target AI Research Scientist roles, where reported compensation runs around $125,000. Its focus on Computer Vision and Machine Learning maps directly to how employers in engineering ai screen for specialized skills rather than generic degrees. Federal projections for this occupational area point to roughly 7% growth this decade — verify the current figure on the BLS Occupational Outlook Handbook before you rely on it.

• 1. Research Scientist in Robotics and Autonomous Systems
• 2. Controls Engineer for Industrial Automation
• 3. Machine Learning Engineer for Embedded Systems
• 4. Academic Researcher or University Faculty Member

What You'll Learn

• Design, develop, and optimize intelligent control systems and autonomous agents for real-world applications
• Apply machine learning and artificial intelligence techniques to electrical systems and embedded platforms
• Conduct original research in signal processing, robotics, and sensor networks
• Integrate hardware and software components to create autonomous and adaptive systems

Curriculum Highlights

The research-focused curriculum includes a minimum of nine graduate courses, a preliminary exam, and a significant original thesis in a specialized area.

Top Employers

Top employers include Tesla, Boston Dynamics, Lockheed Martin, NASA, defense contractors, major technology firms like Google and Microsoft, and leading robotics and automation companies.

Admissions

Admission to University of California, Riverside's PhD in Electrical Engineering – Intelligent Systems generally expects a phd in electrical engineering. Plan for the GRE, which this program lists as required (quantitative score typically 155+). Deadlines, testing policies and funding change year to year, so confirm the current requirements on the official program page before applying.

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 3
• Resume: Required
• Transcripts: Official transcripts required
• Research proposal or statement of research interests: Often required

Frequently Asked Questions