Expansion of AI Programs at West Virginia University
WVU photo New educational offerings in artificial intelligence at the Statler College of Engineering and Mineral Resources are significantly enhancing research and hands-on learning across diverse disciplines.
MORGANTOWN – The West Virginia University Board of Governors has formally approved a new online Master of Science degree in Artificial Intelligence at the Benjamin M. Statler College of Engineering and Mineral Resources.
Nestled within the Lane Department of Computer Science and Electrical Engineering (LCSEE), this program presents students with a comprehensive curriculum encompassing AI, machine learning, computer science, and data science concepts.
“Our aim is to equip students with advanced knowledge in AI, machine learning, and data science, thereby preparing them for evolving careers in research, impactful industries, or further academic pursuits,” stated LCSEE Chair Anurag Srivastava. “We also strive to solidify WVU’s position as a leader in artificial intelligence by fostering interdisciplinary research, bolstering strategic alliances, and promoting workforce development in transformative technological realms.”
In addition to the new MS degree, the institution will introduce certificates and specialized concentrations for both undergraduate and graduate students, facilitating an exploration of AI advancements and applications across various engineering sectors.
Below is a detailed overview of the new academic offerings reshaping the landscape of engineering education:
Advanced Graduate Offerings
The newly sanctioned online MS degree in Artificial Intelligence, approved by the Board of Governors in June, allows students to delve deeper into the theories and applications of AI. The program’s inception was driven by LCSEE Associate Chair and Professor Donald Adjeroh, in collaboration with LCSEE Lecturer Don McLaughlin. Adjeroh underscored the rapid proliferation of AI across various industries as a primary motivator for this initiative.
“The new MS in AI degree program is a critical and timely enhancement to Statler’s online offerings,” remarked Ashish Nimbarte, IMSE Chair and Statler Online Programs Director. “The AI curriculum will cultivate an emergent generation of AI specialists while accommodating students from diverse backgrounds who seek to achieve AI proficiency through carefully structured elective courses.”
“It is evident that AI will drastically transform the future workplace,” explained Adjeroh. “However, the precise dynamics of this transformation remain uncertain. This new program imparts essential training for students across varied backgrounds, illuminating the fundamental concepts underlying AI and equipping them to tackle significant challenges within their specific domains, thereby positioning them to adeptly navigate the anticipated shifts catalyzed by the ongoing AI revolution.”
Program Highlights:
- 30 credit hours required
- Flexible options for both part-time and expedited pathways
- Graduation is possible within one to three years
- Access to unique and pertinent electives
- Reasonable tuition costs
- Fully online format, ideal for working professionals and non-traditional students
- A balanced emphasis on foundational and applied AI topics
“This initiative addresses the burgeoning demand for AI-literate professionals in fields such as digital health, cybersecurity, robotics, energy systems, and automation, aligning with WVU’s mission to propel impactful technological innovation,” noted Srivastava.
“The program was crafted with insights from industry stakeholders, national priorities, alumni, and faculty expertise, ensuring it meets prevailing market demands while preparing graduates for leadership roles in AI-driven industries.”
Enrollment for the Spring 2026 semester is now open. For more information regarding applications, please visit: WVU Catalog.
Graduate Certificate in Digital Health
The Digital Health program offers students a solid technical foundation in artificial intelligence, machine learning, and data science to confront challenges in human health and healthcare settings. Participants will learn how to assess and innovate with digital technologies to enhance healthcare delivery, outcomes, and overall system efficiency. Further details can be found at: Digital Health Program.
New Areas of Emphasis
Under the guidance of Muhammad Choudhry, LCSEE Graduate Studies Director, these new concentrations have been meticulously crafted in collaboration with faculty to align with contemporary industry demands.
These focus areas are designed to produce career-ready graduates proficient in emerging AI and engineering sectors:
- Artificial Intelligence and Computational Data Science: A structured path for LCSEE students, encompassing intensive coursework in AI, machine learning, computing theory, and data analytics.
- Cyber-Physical and Complex Systems: This area underscores the integration of computing, sensing, signal processing, and control within real-world applications such as automation and smart grids.
- Cybersecurity and Networked Systems: This concentration prepares engineers and computer scientists for challenges in wireless communication, software networking, and secure systems design.
- Microelectronics and Embedded Systems: Focused on the design and implementation of microchips and resource-efficient embedded platforms.
Students from computer science and electrical engineering can participate in these focus areas.
Innovative Undergraduate Program Additions
The Statler College is committed to providing undergraduate students with an array of pathways leading to success through newly crafted interdisciplinary offerings. Spanning themes from artificial intelligence to robotics and data science, these collaborations are designed to address the demands of swiftly evolving sectors and equip future engineers with the requisite skills.
Two newly introduced dual degree programs will bridge LCSEE and the Mechanical, Materials, and Aerospace Engineering Department:
- B.S. in Computer Engineering + Robotics Engineering
- B.S. in Computer Science + Robotics Engineering
These interdisciplinary programs necessitate completion of 152-153 credit hours, providing students with a unique opportunity to attain substantial knowledge in both computing and intelligent machine design, gearing them toward high-impact careers at the convergence of AI, automation, and advanced technologies.
New Area of Emphasis: Artificial Intelligence
Directed by Brian Powell, LCSEE Teaching Associate Professor, this undergraduate AI track encompasses targeted coursework in AI, machine learning, and data analytics to bolster hands-on experiences, thereby enhancing preparedness for roles such as AI/ML engineer, data analyst, AI product associate, automation engineer, and junior data scientist.
Eligible majors for this program include:
- Computer Science
- Electrical Engineering
- Computer Engineering
- Cybersecurity
- Robotics Engineering
Department-Led Initiatives and Resources
LCSEE is home to numerous burgeoning initiatives and AI applications in research, student-led experiential learning, and cross-disciplinary collaborations:
- In partnership with WVU Health Sciences, the AI + Digital Health Engineering Center promotes interdisciplinary research and innovation at the nexus of artificial intelligence and healthcare.
- Supported by the National Science Foundation, the NRT Digital Health program fosters a new generation of interdisciplinary leaders skilled in AI, data analytics, and healthcare innovation.
- WVU has earned the esteemed Center of Excellence in Cybersecurity from the Department of Homeland Security and the National Security Agency, owing to its exemplary faculty expertise and rigorous curriculum.
- The new IDEMIA Biometrics Lab facilitates hands-on learning in biometrics and identity technologies, complementing other facilities such as the Trilogy Cybersecurity and Morey Energy Systems labs focused on experiential learning.
Students Innovate with AI
Various student competition teams are gaining recognition with pioneering projects, such as:
- WVU’s AI-powered F1Tenth team, whose autonomous car achieved a commendable second place in the previous year’s IEEE international competition.
- For EcoCAR competitions, students are leveraging AI-driven simulations and control systems to enhance energy efficiency and optimize predictive diagnostics and driver behavior models.
- The WVU Mars Rover competition team has successfully secured two second-place finishes and one first-place victory over the past three years, employing AI for autonomous path planning and navigation challenges in simulated terrains.
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