Scroll through social media long enough and a pattern emerges. Pause on a post questioning climate change or taking a hard line on a political issue, and the platform is quick to respond—serving up more of the same viewpoints, delivered with growing confidence and certainty.

That feedback loop is the architecture of an echo chamber: a space where familiar ideas are amplified, dissenting voices fade, and beliefs can harden rather than evolve.

But new research from the Ģ����ý has found that echo chambers might not be a fact of online life. Published in IEEE Transactions on Affective Computing, argues that they are partly a design choice—one that could be softened with a surprisingly modest change: introducing more randomness into what people see.

The interdisciplinary team of researchers, led by Professor from the , created experiments to identify belief rigidity and assess whether introducing more randomness into a social network could help reduce it. The researchers studied how 163 participants reacted to statements about topics like climate change after using simulated social media channels, some with feeds modeled on more traditional social media outlets and others with more randomness.

Importantly, “randomness” in this context doesn’t mean replacing relevant content with nonsense. Rather, it means loosening the usual “show me more of what I already agree with” logic that drives many algorithms today. In the researchers’ model, users were periodically exposed to opinions and connections they did not explicitly choose, alongside those they did.

A tweak to the algorithm, a crack in the echo chambers

“Across a series of experiments, we find that what people see online does influence their beliefs, often pulling them closer to the views they are repeatedly exposed to,” says , a computer science PhD student and first author of the paper. “But when algorithms incorporate more randomization, this feedback loop weakens. Users are exposed to a broader range of perspectives and become more open to differing views.”

The authors—who also include Professor from the , , the Martin Brewer Anderson Professor of , PhD student , and ’16, ’22 (PhD)—say that the recommendation systems social media platforms use can drive people into echo chambers that make divisive content more attractive. As an antidote, the researchers recommend simple design changes that do not eliminate personalization but that do introduce more variety while still allowing users control over their feeds.

The findings arrive at a moment when governments and platforms alike are grappling with misinformation, declining institutional trust, and polarized responses to elections and public health guidance. Proma recommends social media users keep the results in mind when reflecting on their own social media consumer habits.

“If your feed feels too comfortable, that might be by design,” says Proma. “Seek out voices that challenge you. The most dangerous feeds are not the ones that upset us, but the ones that convince us we are always right.”

The research was partially funded through the .

When Walter McDonald ’27 found himself stranded after his car broke down this summer and his favorite local mechanic was not answering his phone, the Ģ����ý student turned his frustration into a business idea. The third-year and double major knew his mechanic did great work but because he was a small business owner, he was often too tied up fixing cars to coordinate logistics with customers.

“I realized that this is a problem a lot of businesses around the country face,” says McDonald. “We are in an automated age and there are easy solutions, but a lot of business owners don’t know about them because there’s a technological gap.”

After getting his car fixed, McDonald teamed up with his roommate Stephen Lim ’27 (majoring in and ) to create a simple-to-use system that allows small business owners to set up their own virtual receptionist powered by artificial intelligence.

Building the technical foundation

McDonald gained crucial experience in voice systems and natural language processing over the summer working for , a position he secured through the summer internship program at the URochester-based New York State Center of Excellence in Data Science and Artificial Intelligence. He was tasked with building AI voice systems that could take vocal instructions from customers, map them to back-end systems, and determine what insurance policies best matched the customers’ needs. He used many of the same concepts he learned at Soleo for OrbitPhone.

After a few months of development, in late November.

Answering every call

OrbitPhone provides a human-like assistant that can answer calls and book appointments, syncing to a client’s digital calendar and providing quick summaries of each transaction. The product promises an easy setup that takes less than two minutes, and if a client already has a website the system can scrape it for information to make the process even faster.

While products offering AI receptionists for large companies already exist, McDonald says OrbitPhone is intended to fill a gap in price point and ease of use for the small business market.

Ariel Herrera-Molina, who owns Guava Spa in Homer, New York, was among the first to sign up for OrbitPhone. She and her employees are all estheticians who are often too busy with clients to answer phone calls. She said a mentor had advised her to explore using AI to help her business, and she was excited when Ģ����ý students reached out with a potential solution.

“I run a spa and I’m the one doing the work, so I am in services all day long—I’m checking clients in and out, I’m doing the marketing, I’m doing everything,” says Herrera-Molina. “It’s literally impossible for me to be there answering the phone. I know that sometimes people are intimidated when they just get a voicemail, and sometimes they hang up before actually leaving a voicemail. I was hoping to find something to help capture any leads that I was missing.”

Expanding access to AI tools

McDonald and Lim hope their product can help level the playing field for small, local businesses trying to compete with larger corporations.

“We want to augment what people can do and democratize the technology,” says McDonald. “It’s not fair that larger companies are able to capture every single customer call and get all this valuable data while smaller businesses don’t get the same opportunities.”

Since OrbitPhone launched, McDonald and Lim have been working to incorporate feedback from their customers to enhance the product. They plan to add features such as more voice customization and outbound calling to help clients follow up on leads.

Lim says starting a company like this is a dream come true, fusing his interests in both software programming and business. He says Ģ����ý’s open curriculum��gives him the flexibility to pursue both paths, and he is glad to have found in McDonald a collaborative friend and business partner with whom he can work toward a shared goal.

“It’s a whole learning process as we’re building this and figuring things out ourselves,” says Lim. “I love getting first-hand, practical experience building a product. How can you not get excited to build something like this? It’s what I came to school for.”

In the quest for energy independence, researchers have studied solar thermoelectric generators (STEGs) as a promising source of solar electricity generation. Unlike the photovoltaics currently used in most solar panels, STEGs can harness all kinds of thermal energy in addition to sunlight. The simple devices have hot and cold sides with semiconductor materials in between, and the difference in temperature between the sides generates electricity through a physical phenomenon known as the Seebeck effect.

But current STEGs have major efficiency limitations preventing them from being more widely adopted as a practical form of energy production. Right now, most solar thermoelectric generators convert less than 1 percent of sunlight into electricity, compared to roughly 20 percent for residential solar panel systems.

That gap in efficiency was dramatically reduced through new techniques developed by researchers at the ’s . In published in Light: Science and Applications, the team described their unique spectral engineering and thermal management methods to create a STEG device that generates 15 times more power than previous devices.

“For decades, the research community has been focusing on improving the semiconductor materials used in STEGs and has made modest gains in overall efficiency,” says , a professor of optics and of and a senior scientist at Rochester’s . “In this study, we don’t even touch the semiconductor materials—instead, we focused on the hot and the cold sides of the device instead. By combining better solar energy absorption and heat trapping at the hot side with better heat dissipation at the cold side, we made an astonishing improvement in efficiency.”

The new, high-efficiency STEGs were engineered with three strategies. First, on the hot side of the STEG, the researchers used a special black metal technology developed in Guo’s lab to transform regular tungsten to selectively absorb light�� at the solar wavelengths. Using powerful femtosecond laser pulses to etch metal surfaces with nanoscale structures, they enhanced the material’s energy absorption from sunlight, while also reducing heat dissipation at other wavelengths.

Second, the researchers “covered the black metal with a piece of plastic to make a mini greenhouse, just like on a farm,” says Guo. “You can minimize the convection and conduction to trap more heat, increasing the temperature on the hot side.”

Lastly, on the cold side of the STEG, they once again used femtosecond laser pulses, but this time on regular aluminum, to create a heat sink with tiny structures that improved the heat dissipation through both radiation and convection. That process doubles the cooling performance of a typical aluminum heat dissipator.

In the study, Guo and his research team provided a simple demonstration of how their STEGS can be used to power LEDs much more effectively than the current methods. Guo says the technology could also be used to power wireless sensors for the Internet of Things, fuel wearable devices, or serve as off-grid renewable energy systems in rural areas.

The National Science Foundation, FuzeHub, and the supported the research.

The artificial intelligence systems that guide drones and self-driving cars rely on neural networks—trainable computing systems inspired by the human brain. But the digital computers they run on were initially designed for general-purpose computing tasks ranging from word processing to scientific calculations and have ultra-high reliability at the expense of high-power consumption.

To explore novel computer systems that are energy efficient particularly for machine learning, engineers at the are developing new analog hardware, with the possible application toward more efficient drones. Rochester engineers are attempting to do so by abandoning conventional state-of-the-art neural networks developed on digital hardware for computer vision. Instead, they’re turning to predictive coding networks, which are based on neuroscience theories that the brain has a mental model of the environment and constantly updates it based on feedback from the eyes.

“Research by neuroscientists has shown that the workhorse of developing neural networks—this mechanism called back propagation—is biologically implausible and our brains’ perception systems don’t work that way,” says , a professor of , of , and of at Rochester. “To solve the problem, we asked how our brains do it. The prevailing theory is predictive coding, which involves a hierarchical process of prediction and correction—think paraphrasing what you heard, telling it to the speaker, and using their feedback to refine your understanding.”

Huang notes that the URochester has a rich history in computer vision research and that the late computer science professor Dana Ballard was an author on .

The Rochester-led team includes Huang and electrical and computer engineering professors and , their students, as well as two research groups from Rice University and UCLA. The team will receive up to $7.2 million from the Defense Advanced Research Projects Agency (DARPA) over the next 54 months to develop biologically inspired predictive coding networks for digital image recognition built on analog circuits. While the initial prototype will look at classifying static images, if they can get the analog system to approach the performance of existing digital approaches, they believe it can be translated to more complex perception tasks needed by self-driving cars and autonomous drones.

And while the approach is novel, the system will not use any experimental devices but will instead be manufactured using existing technologies like the complementary metal oxide semiconductor (CMOS).

An interdisciplinary hub at the Ģ����ý has been renamed to reflect its deep expertise encompassing two rapidly growing fields of research. The new moniker for the (GIDS-AI)—previously the Goergen Institute for Data Science—is intended to communicate the University’s leadership in both AI and data science.

“AI has historically been a subdiscipline of computer science, but has been playing a central role in broader, interdisciplinary initiatives in data science, which emerged as a new discipline over the past decade,” says , the Robin and Tim Wentworth Director of the Goergen Institute for Data Science and Artificial Intelligence. “GIDS-AI serves as an important facilitator that creates opportunities for Rochester faculty and students to engage in collaborative work where the disciplines overlap.”

The University has been a leader in AI research and education for more than 50 years, dating back to the founding of the in 1974. Since then, Rochester’s computer science faculty have made major contributions to the field of AI, including with seminal texts in computer vision and natural language processing. Cetin says GIDS-AI’s close relationship with the department is critical to staying on the cutting edge of AI research.

Celebrating its 10th anniversary this year, GIDS-AI has grown to include more than 100 across the University. The institute currently offers a , , and in data science. This fall, the Institute will launch a new online professional master’s program in healthcare AI and data science in partnership with the .

Cetin says the institute is planning to offer other learning opportunities in data science and AI in partnership with other units. As an example, this fall, the Department of Computer Science and GIDS-AI plan to pilot an “AI for All” class to empower students not only to use AI in ways beneficial to their education and beyond, but also to help them navigate doing so in a safe and ethical fashion. The course, which would not have prerequisites or require previous experience with AI, would also provide intuitive perspectives on how AI works and show students how they can stay up to date with rapidly developing advances throughout their careers.

Cetin, who has served as director since 2020, was reappointed to lead GIDS-AI for another five-year term.

In addition to its academic offerings, GIDS-AI houses the��Center of Excellence in Data Science��(CoE). Funded by Empire State Development’s Division of Science, Technology, and Innovation (NYSTAR), the CoE aims to help drive regional economic development through supporting basic research, training, and technology development in data science and AI.

Where should the Rochester Fire Department (RFD) locate fire stations over the next 10 years to minimize response times to emergencies? Where should it deploy the most fire trucks? How do seasonal shifts impact the nature and volume of emergencies that firefighters need to respond to?

These are questions that a team of students from the Ģ����ý’s explored over the course of a semester for their by the RFD.

“We were looking for someone from the outside to come in and provide a different set of ideas, experiences, and viewpoints to help us enhance our emergency response services,” says Daniel Curran, a captain for planning and research who is responsible for technology-based projects at the RFD. “We felt the students would have an unbiased perspective and look at the situation and tell us, ‘This is where the data leads us,’ and come to their own conclusions.”

Over the course of the semester, the students used artificial intelligence and other data analytics tools to make sense of more than 1.6 million points of data collected by RFD from 2006 to 2024. They also incorporated external census data related to population, income, property, and housing to enrich their analysis.

“This was an amazing opportunity to contribute something meaningful,” says Brynn (Ye In) Lee ’24 (MS). “The RFD has 15 fire stations, they’re supporting about 500 personnel, and they have around 50,000 annual dispatches, so that’s a huge impact that we can have on the community.”

The students developed interactive maps that allow the RFD to analyze how long it takes the firefighters to reach an incident, while providing information about the distribution of incidents across the city and the ability to sort by incident type. They also created models to predict the monthly incident density over the next 10 years for all 15 fire stations.

In their analysis, the students found that the RFD is already effective at responding to incidents in a timely fashion. However, the students offered recommendations for small improvements that could further decrease response times. Their suggestions include reallocating specific types of trucks from one station to another and introducing programs similar to those in other cities that can address non-life-threatening calls with fewer resources.

According to the students, a critical aspect to their project’s success was going on “ride-alongs” with the RFD, which gave them an appreciation for the firefighters’ day-to-day responsibilities. They said witnessing the types of incidents the firefighters respond to, learning about their shifts, and seeing the equipment in person was enlightening.

“I used to think the fire department only deals with fire-related emergencies, but they deal with so many medical emergencies and spend a lot of time early in the morning patrolling their area to look for fire hazards,” says Homayra Tabassum ’24 (MS). “Getting to see that in person helped us be much more insightful when we were thinking about resource allocation.”

The students said their weekly meetings with the RFD sponsors and collaborating with RFD’s internal data analysts were important learning opportunities as well.

“Dealing with real-world data is not always clean or exactly the way you want it, so the captain and the senior data analysts were extremely helpful,” says team member Medhini Sridharr ’24 (MS). “They helped us choose the most important variables based on their domain knowledge, which was crucial because we had more than 300 variables to consider. They helped us drill down to what’s important.”

Overall, the students said they loved the chance to do a hands-on project with real-world implications, witness the firefighters at work first-hand, and deliver a product that will serve the RFD and local community for years to come.

The project team included data science master’s students Eugene Ayonga ’24, Lee, Sridharr, Tabassum, as well as student Nour Assili ’26.

Can artificial intelligence-powered tools help enrich child development and learning?

That question is the crux of a series of research projects led by , an assistant professor of at the Ģ����ý and the Biggar Family Fellow in Data Science at the . From tools to help parents of deaf and hard-of-hearing (DHH) children learn American Sign Language (ASL) to interactive games that demystify machine learning, Bai aims to help children benefit from AI and understand how it is impacting them.

Bai, an expert in human-computer interaction, believes that, despite all the concern and angst about AI, the technology has tremendous potential for good. She believes children are especially primed to benefit.

“Over the years, I’ve seen how kids get interested whenever we present technology like a conversational agent,” says Bai. “I feel like it would be a missed opportunity if we don’t prepare the next generation to know more about AI so they can feel empowered in using the technology and are informed about the ethical issues surrounding it.”

Minimizing language deprivation in deaf and hard-of-hearing children

During one of Bai’s earliest experiences at the University, she met a key collaborator who led her to a new avenue of research. At a new faculty orientation breakfast, she happened to sit next to , a Deaf researcher and assistant professor at the ’s . The two bonded over a shared interest in childhood development and learning.

Hall explained some of the unique challenges children who are deaf and hard-of-hearing face in cognitive and social development. More than 90 percent of DHH children are born to hearing parents, and often the very first deaf person that parents meet is their own baby. In early human development, there’s a neurocritical period of language acquisition—approximately the first five years of a child’s life—in which children need to acquire a first language foundation. Having parents who do not know a signed language, and the limits of technology such as the cochlear implant and hearing aids, increases the risk of DHH children experiencing negative developmental outcomes associated with language deprivation.

“I learned a lot from Dr. Hall about this concept of language deprivation and became fascinated with the idea of how technology could play a role to make life easier,” says Bai. “I wanted to explore how to help facilitate this very intimate bonding from day one between parents and their kids.”

Bai and Hall began collaborating on a project called the to help parents learn ASL in a natural setting. The system uses a camera and microphone to observe the parent and child interacting, and then uses a projector to present videos of relevant signs retrieved via artificial intelligence from multiple ASL libraries.

In addition to a tabletop version, Bai has been developing versions for tablets, smart watches, and smart glasses, together with her team of undergraduate and graduate students with backgrounds in computer science, data science, and neuroscience. She has also collaborated with student fellows from the and other researchers from the Deaf community such as Athena Willis, a scholar in the ��from the University’s .

Rochester, reportedly home to the country’s largest population of DHH people per capita, is a for researching assistive technologies for the Deaf community. Hall says Bai’s willingness to learn from and collaborate with the Deaf community has helped improve the effectiveness of the tool.

“Often we’ve seen hearing people, hearing researchers become involved in Deaf-related things, they learn something interesting about Deaf people and want to run with it for their own work. Even with the best of intentions, that can go awry very quickly if they are not collaborating with Deaf people and the community at all or in the right way,” says Hall. “My experience with Dr. Bai, though, she really started with a good foundation and kept collaborating with me in a very positive way, so it’s been a great partnership from the very beginning.”

Demystifying machine learning

As AI provides more recommendations to kids about the books they read, shows they watch, or toys they buy, Bai wants to provide learning opportunities so kids can use the technology and understand how it works to make it less of a “black box.” She earned a prestigious�� from the National Science Foundation to develop technologies that help K–12 students demystify machine learning, an integral aspect of current approaches to AI.

Partnering with researchers from the Department of Computer Science, including Albert Arendt Hopeman Professor , and from the —including Frederica Warner Professor , Associate Professor , and Associate Professor —her team developed visualization tools that help K–12 students and their teachers use machine learning to make sense of data and pursue scientific discovery, even if they do not have programming skills.

Bai has been piloting the web-based tool her team developed, , with K–12 teachers to see how she can help the next generation make sense of big data. She says working with teachers has been crucial because they are on the frontlines of helping children make sense of AI.

“Teachers play such a critical role in integrating AI education in the STEM classroom, but it’s so new for them both technologically and pedagogically,” says Bai. “We want to empower teachers with easy-to-use tools so they can create more authentic learning activities that integrate data into their classroom, whether they’re teaching hard sciences or social sciences.”

To help K–12 students understand how AI is affecting them, Bai and her students also developed an augmented reality game. The game uses bee-pollinating flowers as an analogy for AI-powered recommendation systems, illustrating how the preference selection process works. Called , the game shows how choosing to pollinate certain types of flowers can reduce the overall biodiversity of the flowers in the environment.

“BeeTrap explains the mechanism that makes recommendations more or less relevant and diverse to a person,” says Bai. “The goal is to help children realize the value of information and how things are being selectively recommended to people based on previous choices they made and other personal information.”

Bai says this is especially important for marginalized groups, who can be impacted by inherent biases in AI systems related to race, ethnicity, gender, and other factors. Bai has introduced the BeeTrap game to students in various summer camps including the Upward Bound pre-college program by the David T. Kearns Center at the University, and the Freedom Scholars Learning Center in the city of Rochester.

The team is also creating more tangible representations of AI. Her group created , a 3D-printed optical device that shows how AI might suggest different food choices based on your preference for sweet or salty snacks or fatty or healthy options.

Ultimately, Bai thinks it will take a multifaceted approach to help students harness the power of AI, but she is excited to develop tools that can help them get there.

“There is a lot more work to be done to improve the learning experiences and make AI accessible and relatable for students,” says Bai. “We’re happy to play a role in helping to make that happen.”

With millions of self-driving cars projected to be on the road in 2025 and autonomous drones generating billions in annual sales, safety and reliability are important considerations for consumers, manufacturers, and regulators. But solutions for protecting autonomous machine hardware and software from malfunctions, attacks, and other failures also increase costs. Those costs arise from performance features, energy consumption, weight, and the use of semiconductor chips.

Researchers from the , Georgia Tech, and the Shenzen Institute of Artificial Intelligence and Robotics for Society say that the existing tradeoff between overhead and protecting machines against vulnerabilities is due to a “one-size-fits-all” approach to protection. In a , the authors propose a new approach that adapts to varying levels of vulnerabilities within an autonomous machine system to make them more reliable and control costs.

, an associate professor in Rochester’s , says one example of a current “one-size-fits-all” approach is Tesla’s use of two Full Self-Driving Chips (FSD Chips) in each vehicle—a redundancy that provides protection in case the first chip fails but doubles the cost of chips for the car. By contrast, Zhu says he and his students have taken a more comprehensive approach to protect against both hardware and software vulnerabilities and more wisely allocate protection.

“The basic idea is that you apply different protection strategies to different parts of the system,” says Zhu. “You can refine the approach based on the inherent characteristics of the software and hardware. We need to develop different protection strategies for the front end versus the back end of the software stack.”

For example, Zhu says the front end of an autonomous vehicle’s software stack is focused on sensing the environment through devices such as cameras and light detection and ranging (LiDAR), while the back end processes that information, plans the route, and sends commands to the actuator.

“You don’t have to spend a lot of the protection budget on the front end because it’s inherently fault tolerant,” says Zhu. “Meanwhile, the back end has few inherent protection strategies, but it’s critical to secure because it directly interfaces with the mechanical components of the vehicle.”

Zhu says examples of low-cost protection measures on the front end include software-based solutions such as filtering out anomalies in the data. For more heavy-duty protection schemes on the back end, he recommends things like checkpointing to periodically save the state of the entire machine or selectively making duplicates of critical modules on a chip.

Next Zhu says the team hopes to overcome vulnerabilities in the most recent autonomous machine software stacks, which are more heavily based on neural network artificial intelligence, often from end to end.

“Some of the most recent examples are one single, giant neural network deep learning model that takes sensing inputs, does a bunch of computation that nobody fully understands, and generates commands to the actuator,” says Zhu. “The advantage is that it greatly improves the average performance, but when it fails, you can’t pinpoint the failure to a particular module. It makes the common case better but the worst case worse, which we want to mitigate.”

The research was supported in part by the Semiconductor Research Corporation.

Design a rocket.

Master artificial intelligence.

Scat with a Grammy winner.

These are just some of the building blocks of several new academic programs at the Ģ����ý. The latest degree offerings add to the for undergraduate and graduate students. Some were developed to meet the workforce needs of growing industries. Others double down on areas of historic distinction for the University. A few of the programs are brand new, while the rest debuted in the past few years. But all of them have a distinctly Rochester spin to them.

Here’s a look at some of the newest programs being offered in the 2024–25 academic year.

2024: A space odyssey
Minor in Aerospace Engineering

Want to learn how to design and develop aircraft and spacecraft—or repair them? Students in the new take courses that can open doors to mechanical design and manufacturing jobs in the aerospace.

The minor is open to all Rochester undergraduate students but particularly compatible with engineering and physics majors. The courses offered include Introduction to Aerodynamics, Aeorspace Structures, and Advanced Dynamics. Mechanical engineering majors must take four aerospace courses, while others take three aerospace courses and one mechanical engineering course.

“Our students have been enthusiastically asking about aerospace courses, careers, and credentials, and that’s why we built this new minor,” says Douglas Kelley, the director of undergraduate studies and a professor in the . “The industry is booming, with SpaceX single-handedly putting satellites into orbit more quickly than what the whole world could do 20 years ago, and with other companies not far behind.”

Kelley adds that the minor incorporates the study of aerospace optics, a longtime strength at the University (ICYMI dozens of Rochester faculty and alumni contributed to the successful launch of NASA’s James Webb Space Telescope a few years ago).

While the new minor represents a small step for undergrads, a giant leap may be coming soon for graduate students in the form of a master’s degree in aerospace engineering, which could be ready by fall 2025.

Lights, camera … sound
BA in Audio Arts and Technology

Ever wonder how sound is designed, recorded, and broadcast for video games or live sporting events? It’s as much art as it is science, so it only makes sense that a degree program would combine the two.

At Rochester, the lets students combine creative and expressive abilities with technical skills to embark on productive careers in sound and audio fields such as music recording and media production, sound design for media and games, live event support, and broadcasting. The program offers flexibility in combining studies in numerous disciplines.

“It’s for the student who has a deep connection to developing new sonic textures and wants to push the boundaries in audio,” says Stephen Roessner, an assistant professor in the Department of . “From music to podcasting, film to gaming, students can dip their ears into creative trends in audio production.”

Croon with a Grammy winner
BM in Jazz Performance—Jazz Voice

Speaking of cool sounds, you can harmonize with an award-winning artist at the world-renowned , one of the nation’s—and the world’s—.

Eastman offers a new , a track within the jazz studies and contemporary media program, that’s designed and led by Grammy Award–winning vocalist . She’s part of säje, an all-female vocal group whose single, “In The Wee Small Hours of the Morning,” won the 2024 Grammy Award for best arrangement, instrument, and vocals.

“This degree is particularly appealing because it combines the inimitable legacy of the Eastman School of Music with an eye to the future of the jazz genre,” Gazarek says. “It will serve any student who wants to learn about the jazz vocal genre/contemporary vocal performance, in a safe and supportive environment, where the pitfalls of traditional music academia are constantly investigated, and shifted to better serve our base.”

All that jazz is fitting, especially since the acclaimed is held downtown near the Eastman School’s front steps each summer.

Simon says, learn AI from home
Online MS in Business Analytics and Applied AI

The has in integrating generative artificial intelligence into business education. The school now offers an .

In the program, B-school students learn how generative AI is transforming business and then master sophisticated approaches to AI-powered analytics, distinguishing them from other candidates in the competitive job market by positioning them as data-driven, applied AI experts.

The 14-month program is fully online, with both synchronous and asynchronous courses offered. So while the AI revolution might not necessarily be televised, it will be Zoomed.

Genomics unlocks master’s program
MS in Data Science—Genomics Track

It’s not just the business world harnessing artificial intelligence. Another area leveraging AI is genomics—the interdisciplinary field of molecular biology that studies how organisms’ genes work. According to the , it’s a rapidly growing discipline, with a rising demand in the workforce for professionals who can make sense of the massive amounts of data produced by genomic sequencing.

Last year, the University’s launched a to provide students with a strong understanding of the theoretical and applied aspects of both data science and genomics.

There’s a lot of data mining and machine learning during this 19-month program, which is supplemented with workshops and seminars offered by University groups, including the (housed nearby at the Medical Center) and the��.

But wait, there’s more: Rochester’s Genomic Intensive Data Science Research, Education and Mentorship (GIDS-REM) program, partly funded by the National Institutes of Health, awards fellowships that provide full-tuition scholarships and guaranteed internships.

Engineering meets medicine
MS in Diagnostic Imaging

At Rochester, science, technology, and health care converge. The city, which was once dubbed “the image capital of the world,” is the birthplace of the Eastman Kodak Company, a pioneer in photography and imaging technologies. Today, the region’s robust health care sector is anchored by UR Medicine, our area’s premier health service organization.

The program at Rochester builds on these historic and current strengths. It’s rare that engineering students and medical residents work and learn alongside each other. At Rochester, that’s easily done when your engineering school and academic medical center are a mere five-minute walk from each other.

This master’s program aligns imaging fundamentals from engineering with radiological applications observed in immersive clinical environments. It even incorporates emerging artificial intelligence techniques to help prepare the next generation of medical imaging professionals.

Teach the children well
MS in Teaching with Initial Certification��

You don’t necessarily need your master’s degree in hand before you can begin working as an educator in New York State. The offers two teacher residency programs that can jumpstart your teaching career.

The , a partnership with the Rochester City School District and nearby Nazareth University, gives future educators a full year of hands-on classroom experience, mentorship, and employment. Fellows are hired by the school district under a three-year contract, paid a salary with benefits, and provided $15,000 toward college tuition.

During their first year, accepted teacher candidates work side by side with an experienced��co-teaching mentor in the school district while simultaneously completing a master’s degree that leads to initial New York State teacher certification. They spend the following two years after graduation leading classrooms in the city as certified full-time teachers.

Similarly, the�� is a paid teacher residency program designed to prepare future teachers for a career in one of several participating Monroe County school districts. The Warner School has three other programs with similar benefits: the , the , and the .

Three disciplines > one
BA in Politics, Philosophy, and Economics

The British are coming! The interdisciplinary study of��politics, philosophy, and economics (PPE) began at legendary Oxford University in 1920—and has made significant inroads at American universities over the years, with about 50 institutions now offering the program of study. The interdisciplinary nature of PPE allows students to apply the tools of ethical, microeconomic, and quantitative analysis to an array of fundamental social, political, and economic problems.

The at Rochester began in 2022 and is jointly housed in the University’s Department of Philosophy and its top-ranked Department of Political Science (the latter is the birthplace of the world-renowned “Rochester School” of political science, or the scientific and quantitative study of politics). Today, around 50 undergraduate students list PPE as their major.

“The PPE major is wonderful because it gives students a much more powerful and diverse toolkit for changing the world than any of the three disciplines alone,” says Rosa Terlazzo, an associate professor of and one of the PPE program coordinators. “A PPE student knows enough about each of the disciplines to be taken seriously, but they have infinitely more tools for effectively identifying problems and creating designing solutions.”

Breaking barriers for incarcerated people
BA in Multidisciplinary Studies

For nearly a decade, the University’s����(REJI) has provided higher education opportunities for incarcerated and formerly incarcerated people in the Greater Rochester area. Last year, REJI launched a bachelor’s degree at Attica Correctional Facility, becoming the first R1 (or high-research activity) university in New York—and only the seventh in the country—to offer such a program.

The degree program at Attica is in multidisciplinary studies, which builds��on a general studies associate degree program offered through REJI by nearby Genesee Community College.��There are currently 100 students at Attica, Groveland, and Wyoming correctional facilities pursuing associate degrees, with nine pursuing bachelor’s degrees at Attica. The first bachelor’s degree cohort is on pace to graduate in spring 2026.

“I’m immensely proud of the vital work REJI has been doing to decarcerate our campus, our city, and our state,” says Joshua Dubler, an associate professor of����and the director of REJI. “As the premier university and number one employer in a city that has the highest incarceration rate in the state, it is essential that the URochester be a transformative force to help end mass incarceration. The launch of the BA program at Attica is a singular achievement that cements the University’s place as a nationally recognized player in the higher-ed-in-prison sector.”