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CIOs and CTOs often begin exploring the tech innovation cycle at the startup stage, evaluating young companies with promising technologies and, hopefully, more than a whiff of eventual competitive advantage.
But there’s a still-earlier phase in the cycle that plants the seeds for startups and opens the way for technology diffusion in enterprises. That’s the ideation phase, in which technologists identify problems or user needs and then develop and test initial concepts for addressing them. A recent tech day at the Rochester Institute of Technology (RIT) provided a window into this phase of the innovation cycle.
Imagine RIT, held April 26 on the university’s Rochester, N.Y., campus, is an annual innovation event that features student and faculty demos, prototypes and projects. This year’s edition included more than 400 exhibits in fields such as AI, computer science, cybersecurity and healthcare.
Here’s a sampling of developments demonstrated at the event.
A health-related exhibit featured an adjustable prosthetic arm prototype accommodating growth in children aged 5 to 7. The device extends from a child’s upper arm, provides movement around the elbow area and extends to a gripping device called a tensor.
The prosthetic device was created using selective laser sintering, a 3D printing method in which a laser heats and fuses nylon powder into a solid structure.
The ability to periodically adjust the prosthetic arm reduces the frequency of replacement. In addition, the 3D-printed limb is more cost-effective than traditional prosthetics, according to its developers. Paloma Hamilton, a fifth-year mechanical engineering major at RIT, said printing the arm costs $100, with an additional $50 expenditure for associated hardware. In contrast, just the tensor part of a traditional prosthetic arm costs $300, she added.
Hamilton, who works on a team with other students and faculty advisors, said they plan to seek a patent for the adjustable prosthetic through RIT’s Intellectual Property Management Office.
In addition to producing prosthetics such as the prototype arm, healthcare applications for 3D printing include customizing surgical implants and creating anatomical models to prepare medical personnel for complex procedures.
The arrival of a quantum computer that can break classical encryption is considered only a matter of time. The potential security threats could affect many industries, including the tech-heavy automotive sector.
Geoff Twardokus, a Ph.D. candidate in electrical and computer engineering at RIT, is researching the intersection of intelligent transportation systems and post-quantum cryptography. PQC involves the development of algorithms able to thwart attacks driven by quantum computers. Twardokus discussed his research during a demonstration of an intelligent transportation digital twin, which provides a video game-like platform for exploring secure connectivity for vehicles.
Specifically, Twardokus and fellow researchers at RIT and elsewhere are exploring how PQC can be implemented in vehicle-to-vehicle communications. V2V devices share information such as the location and direction of vehicles to improve traffic flow and avoid collisions. However, V2V communications use elliptic curve cryptography, a quantum-vulnerable algorithm. A threat actor’s ability to interfere with safety messages among vehicles could snarl traffic and cause accidents.
Twardokus said a key task in the ongoing research is developing methods and protocols for integrating quantum-resistant algorithms without introducing new security vulnerabilities or latency issues that could hinder the transmission of safety messages between vehicles. The methods and protocols would apply to the post-quantum encryption algorithms published by NIST in 2024 and other upcoming PQC standards, he said.
A recent regulatory change could boost the adoption of V2V technology — and increase the importance of incorporating PQC. Twardokus cited Federal Communications Commission regulations, finalized in November 2024, that allocate specific radio frequencies for V2V communications. Previously, automakers couldn’t legally install V2V equipment without obtaining special experimental licenses, he said. Automakers are now showing a greater willingness to move forward with broad adoption of V2V technology, even though this also increases the potential attack surface as a byproduct, he noted.
Accordingly, one aim of the research project is to ensure the safety benefits of V2V aren’t “accompanied by new, and potentially unanticipated, security risks,” Twardokus added.
The V2V project and developing a digital twin to test the updated security protocols are funded through a five-year National Science Foundation grant. The NSF has been reviewing grants for compliance with executive orders by President Trump requiring federal agencies to terminate grants and programs that the White House deems not in the national interest. Twardokus said the researchers have yet to receive any updates from the NSF regarding changes in the funding status.
Here are some other technologies presented at the Imagine RIT event:
The path from ideation to user acceptance remains a challenging aspect of innovation. Underutilized technology often stems from insufficient customer focus and a lack of tools for tracking digital adoption. RIT’s AI Foundry aims to build bridges between students’ computer science talent and users’ unmet needs, noted Christopher Collison, director of RIT’s AI Hub and Initiatives.
AI Hub, launched in 2024, specializes in AI for teaching and learning. As part of AI Hub, AI Foundry encourages students to build AI tools that provide tangible value, Collison said. The idea is to cultivate a culture where student developers work with faculty to identify specific needs and create “targeted solutions,” he noted.
He added that this approach mirrors startup-style thinking, in which teams build minimum viable products, test them with users, obtain feedback and iterate accordingly.
Collison’s team demonstrated AI TutorBot as an example of its tool-building philosophy. The generative AI learning assistant, currently a pilot project, was tested with 292 students taking an introductory chemistry course. Initial results suggested the bot doesn’t outperform instructor-led learning, but benefits students looking to access learning outside of regular classroom hours, Collison noted.
AI TutorBot uses OpenAI’s GPT-4o and employs a retrieval-augmented generation approach to access RIT educational content and programmatic instructions, such as prompt engineering directives. The RIT-specific data is not used to train the underlying LLM, Collison said. Students access the bot through a custom-built web interface, rather than the public ChatGPT interface. Tom Fuller, visiting scholar at RIT, contributed about 80% of the codebase and front-end design for the interface, with Collison providing 18% of the development work and a student co-op supporting 2%, Collison said.
The pilot tool, built using a personal development environment, is not owned by RIT. Collison said discussions this summer at the university will explore the technical and legal aspects of deploying AI TutorBot at scale.
John Moore is a writer for Informa TechTarget covering the CIO role, economic trends and the IT services industry.
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