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After more than 50 years studying close relationships, University of Rochester psychologist Harry Reis has reached a deceptively simple conclusion: Happy people feel loved.
That conclusion became the jumping-off point for a new book Reis co-wrote, “How to Feel Loved: The Five Mindsets That Get You More of What Matters Most” (Harper 2026), which blends decades of research on happiness and human connection.
In it, Reis and his co-author, Sonja Lyubomirsky, a psychologist at the University of California, Riverside, outline five research-backed mindsets that strengthen connection: sharing authentically, listening to people, practicing radical curiosity, approaching others with an open heart, and recognizing human complexity.
The book was recently featured in The New York Times, which noted that the authors contend giving and receiving love function together like a seesaw: You lift a person up with the weight of your curiosity and attentiveness — and they do the same in turn.
“The other side is very important also,” Reis told The Times. “To be sharing what’s important to you, to be sharing what you’re concerned about, so it can really become a two-way street.”
Reis, who leads groundbreaking research on close relationships, is available to discuss:
• The science of feeling loved vs. being loved
• How digital distraction undermines connection
• AI companionship and its psychological limits
• Practical ways to build stronger, more resilient relationships
• The link between love, happiness, and health
Journalists writing about love and relationships can contact Reis by clicking on his profile.
What if boats, buoys, and other items designed to float could never be sunk — even when they’re cracked, punctured, or tossed by an angry sea?
If you think unsinkable metal sounds like science fiction. Think again.
A team of researchers at the University of Rochester led by professor Chunlei Guo has devised a way to make ordinary metal tubes stay afloat no matter how much damage they sustain. The team chemically etches tiny pits into the tubes that trap air, keeping the tubes from getting waterlogged or sinking. Even when these superhydrophobic tubes are submerged, dented, or punctured, the trapped air keeps them buoyant and, in a very literal sense, unsinkable.
“We tested them in some really rough environments for weeks at a time and found no degradation to their buoyancy,” says Guo, a professor of physics and optics and a senior scientist at the University of Rochester’s Laboratory for Laser Energetics. “You can poke big holes in them, and we showed that even if you severely damage the tubes with as many holes as you can punch, they still float.”
Guo and his team could usher in a new generation of marine tech, from resilient floating platforms and wave-powered generators to ships and offshore structures that can withstand damage that would sink traditional steel.
Their research highlights the University of Rochester’s knack for translating physics into practical wonder.
For reporters covering materials science, sustainable engineering, ocean tech, or innovative design, Guo is the ideal expert to explain why “unsinkable metal” might be closer to everyday use than you think.
To connect with Guo, contact Luke Auburn, director of communications for the Hajim School of Engineering and Applied Sciences, at luke.auburn@rochester.edu.
Higher learning in the age of artificial intelligence isn’t about policing AI, but rather reinventing education around the new technology, says Chris Kanan, an associate professor of computer science at the University of Rochester and an expert in artificial intelligence and deep learning.
“The cost of misusing AI is not students cheating, it’s knowledge loss,” says Kanan. “My core worry is that students can deprive themselves of knowledge while still producing ‘acceptable work.’”
Kanan, who writes about and studies artificial intelligence, is helping to shape one of the most urgent debates in academia today: how universities should respond to the disruptive force of AI.
In his latest essay on the topic, Kanan laments that many universities consider AI “a writing problem,” noting that student writing is where faculty first felt the force of artificial intelligence. But, he argues, treating student use of AI as something to be detected or banned misunderstands the technological shift at hand.
“Treating AI as ‘writing-tech’ is like treating electricity as ‘better candles,’” he writes.
“The deeper issue is not prose quality or plagiarism detection,” he continues. “The deeper issue is that AI has become a general-purpose interface to knowledge work: coding, data analysis, tutoring, research synthesis, design, simulation, persuasion, workflow automation, and (increasingly) agent-like delegation.”
That, he says, forces a change in pedagogy.
What Higher Ed Needs to Do His essay points to universities that are “doing AI right,” including hiring distinguished artificial intelligence experts in key administrative leadership roles and making AI competency a graduation requirement.
Kanan outlines structural changes he believes need to take place in institutions of higher learning.
• Rework assessment so it measures understanding in an AI-rich environment. • Teach verification habits. • Build explicit norms for attribution, privacy, and appropriate use. • Create top-down leadership so AI strategy is coherent and not fractured among departments. • Deliver AI literacy across the entire curriculum. • Offer deep AI degrees for students who will build the systems everyone else will use. For journalists covering AI’s impact on education, technology, workforce development, or institutional change, Kanan offers a research-based, forward-looking perspective grounded in both technical expertise and a deep commitment to the mission of learning.
Connect with him by clicking on his profile.
