30 Artificial Intelligence Project Ideas in 2025 [Trending]

New Program Focuses On Artificial Intelligence

WVU photo New course offerings in artificial intelligence at the Statler College are expanding research and hands-on experiential learning possibilities across several disciplines.

MORGANTOWN –The West Virginia University Board of Governors has approved a new online MS degree in Artificial Intelligence, launching at the Benjamin M. Statler College of Engineering and Mineral Resources. Housed in the Lane Department of Computer Science and Electrical Engineering (LCSEE), the program offers students a robust curriculum in AI, machine learning, computer science and data science topics.

"Our goal is to empower students with advanced expertise in AI, machine learning and data science to prepare them for dynamic careers in research, high-impact industries or graduate studies," LCSEE chair Anurag Srivastava said. "We also aim to elevate WVU's leadership in artificial intelligence by promoting interdisciplinary research, expanding strategic partnerships and workforce development in transformative technology fields."

Along with the new MS degree, new certificates and concentrations for both undergraduates and grad students provide opportunities to explore AI developments and applications in other engineering disciplines.

Here's a closer look at all the new offerings shaping the future of engineering education:

Advanced graduate

offerings

Through a new online MS degree in Artificial Intelligence approved by the BOG in June, students will have the opportunity to continue coursework in theory and applications of AI. The program's development was spearheaded by LCSEE associate chair and professor Donald Adjeroh along with LCSEE lecturer Don McLaughlin. Adjeroh emphasized AI's rapid expansion across industries as a catalyst for the new program.

The new MS in AI degree program is a timely and significant addition to Statler's online offerings," said Ashish Nimbarte, IMSE chair and Statler Online Programs director. "The AI curriculum provided by this program will cultivate a new generation of AI experts and also benefit students from other programs with diverse backgrounds who want to become AI proficient by taking structured elective courses aligned with their career goals.

"That AI will significantly re-shape the workplace of the future is a given," explained Adjeroh. "What is not clear is exactly how. The new program provides the required training for students with diverse backgrounds to understand the foundations behind AI, and how to build on that understanding to address key challenges in their specific field — positioning them for effective response to the expected changes in the workplace prompted by the ongoing AI revolution."

Program highlights: 

— 30 credit hours

— Flexibility for both part-time and accelerated paths

— Ability to graduate in one to three years 

— Access to unique and relevant electives 

— Reasonable cost 

— Fully-online delivery for working professionals and non-traditional students

— Balanced foundational and applied AI topics 

"This initiative responds to a sharp demand for AI-proficient professionals in digital health, cybersecurity, robotics, energy systems, and emerging automation fields, aligning with WVU's mission to advance impactful technological innovation," Srivastava said. "This program was shaped through input from industry partners, national priorities, alumni, and faculty expertise, ensuring the program addresses real-world needs while positioning graduates for leadership in AI-driven sectors."

Students are eligible to enroll for the Spring 2026 semester. For additional information on how to apply, visit: http://catalog.Wvu.Edu/graduate/collegeofengineeringandmineralresources/thelanedepartmentofcomputerscienceandelectricalengineering/artificialintelligence/

Graduate Certificate

in Digital Health 

The Digital Health program provides students with a technical foundation in artificial intelligence, machine learning and data science to address challenges in human health and healthcare. Students will learn to apply, evaluate and innovate with digital technologies to improve healthcare delivery, outcomes and system efficiency. More information can be found at: http://catalog.Wvu.Edu/graduate/graduatecertificates/digital_health/

New Areas of

Emphasis

Led by LCSEE graduate studies director Muhammad Choudhry, these new concentrations were developed in coordination with faculty to align with emerging industry needs. These focus areas produce career-ready graduates who are technically proficient and immediately relevant across emerging AI and engineering landscapes:

Artificial Intelligence and Computational Data Science: This is a structured track for LCSEE students, offering focused coursework in AI, machine learning, theory of computing and data analytics to complement hands-on engineering and strengthen readiness for AI-centric roles.

Cyber-Physical and Complex Systems: Emphasizes the integration of computing, sensing, signal processing and control in real-world systems like automation, robotics, smart grids and energy systems.

Cybersecurity and Networked Systems: Prepares engineers and computer scientists in wireless communication systems and software, networking and hardware security, defensive architectures and secure systems design.

Microelectronics and Embedded Systems: Focused on design and implementation of microchips, sensing electronics, digital devices, Internet of Things and resource-efficient embedded platforms.

Computer science and electrical engineering students are eligible for these focus areas.

Innovative

undergraduate

program additions

Statler is proud to offer undergraduate students even more pathways to success through new interdisciplinary offerings. From artificial intelligence to robotics and data science, these new collaborations are designed to meet the demands of today's rapidly changing industries and equip future engineers with the skills and experience to lead.

Two new dual degree programs will straddle LCSEE and the Mechanical, Materials and Aerospace Engineering department:

B.S. In Computer Engineering + Robotics Engineering

B.S. In Computer

Science + Robotics

Engineering

These new interdisciplinary programs require 152-153 credit hours and offer students a unique opportunity to gain deep expertise in both computing and intelligent machine design — preparing them for high-impact careers at the intersection of AI, automation and advanced technology.

New area of emphasis:

Artificial Intelligence

Coordinated by LCSEE teaching associate professor and computer science undergraduate studies program director Brian Powell, this undergraduate AI track offers focused coursework in AI, machine learning and data analytics to complement hands-on learning and strengthen readiness for AI-centric roles like AI/ML engineer, data analyst, AI product associate, automation engineer and junior data scientist.

Students in the following majors are eligible:

— Computer science

— Electrical engineering

— Computer engineering

— Cybersecurity

— Robotics engineering

New department-led initiatives, resources

LCSEE is home to several growing initiatives and AI applications in research, student-led experiential learning and collaborations across disciplines:

In collaboration with WVU Health Sciences, the AI + Digital Health Engineering Center advances interdisciplinary research and innovation at the intersection of artificial intelligence and healthcare.

Supported by the National Science Foundation, the NRT Digital Health program cultivates a new generation of interdisciplinary leaders proficient in AI, data analytics and healthcare innovation.

Thanks to faculty expertise, rigorous curriculum and institutional depth in cyber defense education and research, WVU holds the prestigious Center of Excellence in Cybersecurity from the Department of Homeland Security and National Security Agency.

The new IDEMIA Biometrics Lab provides opportunities for hands-on learning in biometrics, identity and access technologies. The lab joins the Trilogy Cybersecurity and Morey Energy Systems labs on the Evansdale campus to expand experiential learning and research initiatives here at Statler. 

Students innovate with AI

Student competition teams across disciplines are earning recognition with cutting-edge projects including: 

WVU's AI-powered F1Tenth team is driving innovation with their autonomous car, which placed second in last year's Institute of Electrical and Electronics Engineers international competition. 

For EcoCAR competitions, students are utilizing AI-driven simulations and control systems to optimize energy efficiency, predictive diagnostics and driver behavior models.

Over the past three years, the WVU Mars Rover competition team has earned two second-place finishes and one first-place win. AI applications have included autonomous path planning and navigation across simulated terrain using onboard planning systems, computer vision and LiDAR-guided obstacle detection, target identification and manipulation during mission tasks.

Can Artificial Intelligence Replace Humans? An Engineering ... - Forbes

Alex Gudilko, CEO of AJProTech - IoT Product Development Studio in Los Angeles, California.

In a world dominated by economic value and increased automation, there is a growing worry about whether AI will replace humans. Yet, many believe that instead of taking jobs away, AI is transforming how we work, unlocking human potential and changing how we innovate and boost productivity. In engineering, it's crucial to identify roles susceptible to AI and automation, as well as those resilient to change. In this piece, we'll navigate the dynamic landscape and dive into the impact of artificial intelligence on engineering and related disciplines.

Robots Are On The Rise

It was expected that robots would replace low-skilled labor, particularly in monotonous and dangerous tasks on factory floors. In reality, human labor remains more cost-effective than investing in purchasing and programming robots for most facilities. In addition to robotics hardware, the cost of training is substantial: every time you make a change to the process—traditional robots must be re-trained. Only in large-scale production, such as smartphone assembly, has robotics become practical due to the high volume. A big breakthrough is on the horizon, though: The latest robotics systems with computer vision and artificial intelligence can train themselves and follow generic commands in natural language. When you can "ask" a robot to separate red "things" and green "things" in plain English, robotics automation has tremendous potential.

Algorithmic Copywriting

Copywriting became popular because people realized that persuasive content makes a big impact in grabbing the audience's attention. Whether it's on websites, press releases or various media platforms, effective text plays a vital role in conveying official information and engaging with potential customers.

Presently, the work of copywriters may be greatly facilitated by artificial intelligence. While it won't disappear entirely, AI may empower engineers with specialized knowledge to write compelling articles without hiring other people. AI cannot completely replace copywriters, as the importance of high taste and the quality of the text are crucial factors that AI may struggle to replicate. Nonetheless, the significance of particular knowledge in specific domains is also starting to emerge.

Designer: Hey AI, draw 100 concepts of a speaker with…

While graphic designers are all-in on adopting AI tech, the realm of Industrial Design clings to manual processes. However, it doesn't imply that industrial designers are barred from, or should refrain from, the power of AI. For instance, they can extract valuable insights by hiring AI to generate multiple product concepts faster. Alternatively, they can task AI to generate a substantially broader range of product sketches, enhancing the exploration of design possibilities.

At present, AI-generated product renders often fall short of perfection or don't account for manufacturing limitations. Nevertheless, continuous refinement through iterative prompts is feasible. This process might result in renders and sketches at a reasonable pace, potentially faster than starting from scratch, yet it may not revolutionize the field. While generative AI can assist less skilled designers and expedite the design process, high-end professionals rely on their processes and creativity.

10x Engineers

The hot conversation in Silicon Valley revolves around whether AI can replace large software engineering staff. Big tech companies hire tens of thousands of engineers to write generic and not always groundbreaking software. Should programmers be worried about their jobs? It depends.

Website designers are at risk: AI tools can create great-looking web pages with simple prompts. Further customization, such as changing fonts or adding buttons, is even easier than asking your programmer friend.

More advanced systems are developed by hundreds of programmers. Following the 80/20 rule, even before AI, some key members created the most value. Who is a "10x engineer?" A person who can write ten times more lines of code than an average programmer. With AI, 10x engineers can drive even more value. Shall we say 100 lines of code? This way, a team of 10 programmers, together with an AI copilot—a system that engineers can "ask" to write a piece of code—will do more than their entire organization did before.

Electronics Engineers

Electrical engineers develop physical products. Every headphone or camera developed in the U.S. Was designed by a team of engineers, each earning $150,000 or more per year. This drives the total development cost into several million dollars. Can AI design a new product for a startup? The short answer is NO.

However, it can augment and expedite development. For instance, AI could generate a diagram outlining the major components of a specific device. Engineers spend a lot of time manually selecting components and discussing them with manufacturers. An AI co-pilot may compile a list of the top 10 manufacturers, find their contact info and draft email requests for pricing and documentation. AI can also help perform calculations and solve math problems. After component selection, engineers connect all parts on the Printed Circuit Board (PCB). While it remains a mainly manual process, CAD software is incorporating more and more AI tools to expedite the development.

Mechanical Engineers

The development process unfolds as our designer crafts the initial design, and our electronics team translates it into a functional PCB. At a certain point, the design is handed over to Mechanical Engineers, who transform it into a manufacturable enclosure. Integration of electronics and mechanics is a meticulous, hands-on affair. Currently, no AI software exists to seamlessly handle the complexities of developing mechanical devices. Even sophisticated tools fall short, and the integration process remains a manual craft. The limited AI involvement may extend to highlighting potential conflicts or identifying areas where design aesthetics could be improved, but the bulk of the work is done by skilled hands.

No One Likes To Dwell On Limitations

Our world is and should be evolving, but technology is far from being able to fully replace highly skilled engineers. Key qualities such as creativity, effective communication and the ability to devise innovative solutions remain invaluable. While AI can complement and enhance certain aspects of work, it is unlikely to completely overshadow the expertise and capabilities of skilled specialists. The reliance on the human touch remains irreplaceable.

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'New Era Of Engineering'

Ansys, the esteemed simulation software company based at Southpointe, is stepping up its AI game. And so is the Sunnyvale, Calif., firm that acquired it.

The $35 billion deal with Synopsys, initially announced in January 2024, was completed in mid-July amid great expectations from both sides – as the United States strives to prevail in a likely artificial intelligence race with China.

"This is a new era of engineering. Everything is accelerating," said Anthony Matarazzo, director of AI and simulation solutions with Ansys. "This is where leveraging with simulation meets EDA (Exploratory Data Analysis). It's a new era of engineering."

Although Ansys is now part of another company, Matarazzo said "we're keeping our name for the foreseeable future" – inside Southpointe, the mixed-use park in Cecil Township.

Speed is, indeed, paramount in the evolving world of AI.

Synopsys, a 40-year-old firm located in the Silicon Valley region of the Golden State, uses software to design silicon computer chips. It said in a statement that "the transaction … (with Ansys) combines leaders in silicon design, IP (internet protocol) and simulation and analysis to enable customers to rapidly innovate AI-powered products. Synopsys is now positioned to win in an expanded $31 billion total addressable market."

Synopsys said it "remains dedicated to helping engineers innovate, reduce time-to-market and costs, and improve product quality by delivering unprecedented insights into how their products will perform in the real world."

United with Ansys, Synopsys said it "can now deliver holistic system design solutions for customers in industries spanning semiconductors, high-tech, automotive, aerospace, industrial and more."

Ansys is poised to benefit as well. The company on Aug. 12 signed an agreement with Nvidia, a leading AI company in the U.S. That provides hardware, software and platforms to speed up AI development.

This accord, according to Ansys, is "to license, sell and support Omniverse technology embedded in Ansys simulation solutions."

Ansys said it "will deliver easy access to Omniverse technologies and libraries to customers … enabling accessible, smooth workflows across diverse simulation applications.

"By leveraging Omniverse platform capabilities directly from the Ansys interface, teams are empowered to innovate faster, tackle challenges head on, and achieve research breakthroughs."

Matarazzo acknowledged that before the acquisition, Synopsys was a leader in chip design, and Ansys "had a larger reach of engineers and industries it supports." He said the companies combined should enhance the integration of AI with physical systems, including robots and self-driving cars.

Massive data centers are being built around the country. Synopsys will work toward improving energy efficiency at data centers and working with customers to scale renewable energy, such as hydrogen and nuclear.

Data centers require large volumes of energy, which could severely impact the PJM electricity grid that 13 northeastern states, including Pennsylvania, and the District of Columbia rely upon.

Matarazzo said Synopsys will work toward developing a virtual replica for these models. "We're modeling all of this between Synopsys and Ansys.

"We're the backbone of physical AI for any of these intelligence systems. Together, we provide a more comprehensive tool chain that goes across any application."

John Swanson, a University of Pittsburgh graduate, founded Ansys in 1970 at a farmhouse in Pennsylvania. He named it Swanson Analysis Systems and later switched it to Ansys, the name of its simulation software.

Swanson, who was an engineer at the Westinghouse Astronuclear Laboratory, nurtured Ansys into a company that, in 2024, would post $2.5 billion in revenue and employ nearly 7,000 in the U.S., Europe and Asia Pacific.

An accomplished engineer now residing in North Carolina, Swanson was quoted in a recent Pittsburgh Post-Gazette story that he is not enamored of AI.

"I was designing software for the engineers to develop good products," he said, adding that if he were handed an Ansys code now, he would not know how to run it.

He sold his company about 30 years ago, and said at that time that Ansys could simulate "anything that was real, that you could feel and touch. And then we got into magnetics and electrical circuits. And that you can't feel and touch.

"But then, when you're getting the chip design," Swanson said, "then it's all beyond me."

"AI is a power hog," he said, "and it's basically turning back everything we've tried to achieve."

His former company is now working with a prestigious partner, Synopsys, to boost the use and efficiency of artificial intelligence – quickly and efficiently. Thus far, Matarazzo said the acquisition has been operating well.

"I think the feedback I've seen has been very energizing, very positive. We're looking at how we can take the strengths of two very large tech companies and solve problems.

"It's like peanut butter and jelly."

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