In the halls of the University of Dayton, where innovation thrives, researchers Tarek Taha and Chris Yakopcic ’09 are creating technological marvels. Their journey — from theoretical musings to tangible patents — has shaped their careers as artificial intelligence innovators.
Their impressive output — five patents this past academic year and 32 patents since 2015 — speaks volumes. When asked about their achievements, Yakopcic, a UD research scientist, replies, “We think about the next patents more than the last ones.”
Professor Taha, head of the University of Dayton Parallel Cognitive System Laboratory, admits patenting wasn’t initially on their radar. Their first patent experience was bewildering, transitioning from precise academic papers to practical, legally intricate documents.
Yakopcic and Taha’s journey began in 2009 when Yakopcic joined the University of Dayton as a grad student. Their project on memristor-based circuits promised efficient neural networks. A memristor is like a tiny brain cell in an electronic circuit. It remembers how much electricity has passed through it, even when the power is turned off. This memory effect allows it to control the flow of electricity based on its history, making it useful for storing information in computers in a way that mimics human memory. Together, they redefined chip design, creating computer chips for artificial intelligence. These tiny components revolutionize circuit design, outperforming conventional chips.
Tarek and Yakopcic mastered the intricate dance between innovation and legal rigor. With UD’s Office of Technology Entrepreneurial Partnerships, they crafted patents that safeguarded ideas while allowing flexibility for future applications. Patents transformed their theoretical work into tangible assets, addressing real-world challenges. As Tarek puts it, “Once it’s patented, it feels nice.”
Yakopcic’s excitement about building a brain in silicon resonates. Taha emphasizes dual goals: making state-of-the-art chip designs and artificial intelligence capabilities. Their focus extends beyond computations to efficiency and deep learning. Deep learning uses layers of calculations to sift through data and learn from it, getting better and smarter over time, just like a human brain getting wiser with experience. Their patents extend beyond University walls, validating ideas and attracting collaborators. They expect their work will impact everyday devices, like battery-operated gadgets, to space technology.
What’s next? Harmonize seemingly incompatible algorithms — mathematical calculations that give computers instructions — and focus on evolving memristor technology. Their early chip designs were taught; now, they aim to create chips that learn independently. Yakopcic’s advice echoes their journey: embrace uniqueness. High-risk ideas may take longer to catch on, but they’re worthwhile. Taha encourages broad-mindedness — explore less-trodden paths with potential.
A version of this article appears in print in the Winter 2024-45 University of Dayton Magazine, Page 12. EXPLORE THE ISSUE — MORE ONLINE
This story was drafted using advanced artificial intelligence and then reviewed and edited by the researchers and University of Dayton news and communication staff to ensure accuracy, clarity and consistency with the University’s standards. After all, it only seems fair to ask AI to help write its own story.