Artificial intelligence can be a boon to conservation science.

Daniel Thornton, associate professor of wildlife ecology at Washington State University, details why.

Faculty Bio:

Dr. Thornton studies the spatial ecology and conservation of mammals, with an emphasis on mammalian carnivores. His work spans the Americas, and integrates a variety of partners from agencies, NGOs, and communities. Dr. Thornton’s research interests include the influence of human activities on the distribution of species, methods for studying carnivores, and transboundary conservation.

Transcript:

One of the most common methods to study elusive and threatened species like wolves, jaguars and lynx are motion-activated cameras placed in forests and other wild landscapes that can collect millions of images of wildlife during a project. However, a major challenge is processing the images - somebody must go through all those photos and identify what species appears in each one. Traditionally, that’s meant graduate students and undergraduate volunteers spending months reviewing images before the actual science begins.

Our new research asked a simple question: what if artificial intelligence could handle that process almost entirely on its own?

We tested a Google AI system called SpeciesNet using wildlife images collected in Cascade Mountains, Glacier National Park, and Guatemala’s Maya Biosphere Reserve. Then we compared statistical models of species distribution that were produced either using AI or human-based identifications of species.

What surprised us was how close the results were.

The AI-based models matched the human-based models for about 85 to 90% of the species. Even when AI occasionally misidentified animals in the images, the overall ecological patterns were still remarkably accurate. In other words, our conclusions about where species were located and what factors influence their presence were the same, whether we used the AI identifications or the human ones.

That matters because it changes the timeline of camera-based studies dramatically, from several months to less than a week.

For conservation, speed is important. The faster researchers can process information, the faster wildlife managers can make decisions. For example, if cameras detect fewer lynx in one area or show wolves moving into a new region, managers could spot those trends sooner and make decisions rapidly. Smart use of AI can remove a major bottleneck so scientists can spend less time sorting photos and more time understanding and protecting wildlife.

Read More:

[British Ecological Society] - Identification of camera trap images by artificial intelligence and human experts produces similar multi-species occupancy models

What are the long-term impacts of rocket launches on nearby communities?

Whitney Coyle, associate professor of physics at Rollins College, examines this.

Faculty Bio:

Whitney L. Coyle, PhD is an Associate Professor of Physics and Coordinator of the Pre-Engineering Program at Rollins College in Winter Park, Florida, where she serves as Chair of the college’s Department of Physics.

At Rollins, Coyle leads undergraduate-centered research exploring how sound is produced and measured in both musical instruments and large-scale systems like rocket launches. Her work connects fundamental physics with real-world acoustic environments while providing students with hands-on research opportunities.

She is the recipient of the 2026 R. Bruce Lindsay Award from the Acoustical Society of America (ASA), one of the world’s leading professional organizations in acoustics.

Transcript:

A rocket launch produces rumblings, vibrations, and high-intensity sound near the launch pad that can also travel to communities tens of miles away. My research focuses on how that sound propagates into communities near Cape Canaveral and how repeated launches may affect the local environment as launch cadence increases. Unlike aircraft noise, rocket launches contain strong low-frequency energy that can travel long distances and interact with homes and buildings in ways that are still not fully understood.
I work with a team of undergraduate physics majors using calibrated sound level meters, accelerometers, and ground vibration sensors to measure both the audible and very low-frequency components of rocket launches. These instruments allow us to study not just how loud a launch is, but how the sound and vibration interact with the environment. We are measuring how windows, walls, and structures respond to the low-frequency energy produced during launch.
These low-frequency sounds are especially important because they are not fully captured by traditional aircraft-based noise metrics currently used by the FAA. Those standards were developed for airplanes flying overhead on very different flight paths than modern heavy-lift rockets.
A major goal of this work is to improve understanding of how rocket launches are experienced in nearby communities. Residents along the Space Coast are overwhelmingly supportive of spaceflight and excited about continued growth in launch activity, but local planners and agencies currently have limited data available to evaluate long-term acoustic and vibration impacts.
This research is helping build the foundation needed to better characterize rocket-specific noise environments, evaluate potential structural response in nearby buildings, and eventually connect those measurements to how people perceive and respond to launches. As access to space continues to grow, understanding the broader environmental and community impacts of launch noise will become increasingly important and this work is helping lay the groundwork for that future understanding.

Read More:

[Rollins] - Coyle Receives Prestigious International Acoustics Award

[Rollins] - What It’s Like ... to Partner with Your Professor

Academic freedoms may be under attack, but professors have legal protections as well.

Kent Kauffman, professor of business law at Purdue University Fort Wayne, discusses this.

Faculty Bio:

Kent Kauffman is Professor of Business Law, and MBA Programs Faculty Liaison, in the Doermer School of Business at Purdue University Fort Wayne. He is the author of “Navigating Choppy Waters: Key Legal Issues Faculty Need to Know,” published by Bloomsbury, which tackles the vital legal dilemmas faculty face in their work as scholars and teachers.

Transcript:

Academic freedom has an almost kaleidoscope effect. It looks differently to various groups: university administrators; faculty; students; and certainly politicians. For faculty, academic freedom is an essential prerogative, allowing them to decide what to study and research, and what and how to teach – even when those choices are controversial. Over a half-century ago, the United States Supreme Court, in one case, declared academic freedom vital to a democracy, and in another case said academic freedom required safeguarding because of its “transcendent value to all of us and not merely to the teachers concerned.”

The sources of academic freedom include tradition (to the extent academic freedom’s history is valued), binding employment policies that detail its contours to faculty, and, for public university faculty, the First Amendment, for which teaching is considered a “matter of public concern” and worthy of constitutional protection.

Regrettably, some states are restricting academic freedom in various ways, including prohibiting the kinds of courses or content that can be taught, allowing students to secretly record their instructors in class, and giving students the right to file complaints against their instructors for what those students would consider offensive teaching statements. But faculty have for decades been protected by a legal doctrine, the Germaneness Standard, which evaluates whether controversial content is pedagogically related, not if it makes students uncomfortable. In a noteworthy case, an adjunct instructor of interpersonal communication sued his college after he was fired because a few students got offended by a social deconstructivism, word association exercise he conducted in class. In ruling for the instructor, a federal court of appeals concluded the exercise was germane to the subject and, thus, protected by the First Amendment, because teaching is a matter of public concern.

Read More:

[Bloosmbury] - Navigating Choppy Waters

What can ivermectin teach us about health misinformation?

Dannell Boatman, assistant professor of cancer prevention and control at West Virginia University, takes a look.

Faculty Bio:

Dannell Boatman, EdD, MS, is an Assistant Professor and health communication researcher in the Department of Cancer Prevention and Control at the West Virginia University (WVU) School of Medicine. She conducts her research through the Communicating for Health in Appalachia by Translating Science (CHATS) Lab and is the founding Director of the CHATS Core at the WVU Cancer Institute. Raised in Appalachia, her early work in community and rural public health inspired a research program focused on improving how scientific evidence is communicated and used to support health decisions.

Her research combines communication and behavioral sciences to understand how people navigate cancer information and to develop evidence-based strategies that improve communication across clinical, community, and digital settings. Her work spans community-engaged research, rural and Appalachian health, and cancer misinformation, with a focus on translating scientific evidence into practical communication strategies.

Through the CHATS Core, Dr. Boatman partners with researchers, healthcare organizations, and communities to move evidence into practice through knowledge translation, dissemination science, audience-centered communication, and creative strategies that increase the impact of research.

Her work has been recognized by the Academy of Communication in Healthcare as a Putnam Scholar and by the West Virginia Clinical and Translational Science Institute as a Research Scholar. She serves on the American Cancer Society National Lung Cancer Roundtable Stigma and Nihilism Task Group, the World Health Organization’s Health Information Integrity Alliance, and the editorial board of PEC Innovation.

Transcript:

Why do some medical claims gain traction despite a lack of scientific evidence?

When a recent observational study suggested that ivermectin, an antiparasitic drug, might help treat cancer, the claim spread rapidly online. Although ivermectin has not been shown to be safe or effective for treating cancer, many people shared the study as proof that it worked, even as scientists raised serious concerns about the study’s findings.

It may seem like the story began there. My research shows it was actually just the latest chapter.

To understand how these claims gain momentum, I use social listening to monitor online cancer misinformation. By tracking conversations across social media and other digital spaces, I examine how health claims emerge, spread, and resurface over time.

My research has followed multiple periods of heightened online attention surrounding ivermectin and cancer. One came in January 2025, when a high-profile podcast promoted antiparasitic drugs as alternative cancer treatments. I watched public interest surge in real time. While this spike in attention was new, the conversation was not. My research found that claims linking antiparasitic drugs like ivermectin to cancer had been circulating for years, driven by powerful personal stories, influential voices, and active online communities. By the time the observational study was published recently, many people had already encountered multiple versions of the same narrative, shaping how they made sense of its findings.

What I discovered about ivermectin reflects a broader pattern. New scientific findings do not enter a vacuum. They become part of conversations that have often been unfolding for years. Those ongoing discussions shape how people interpret new findings, even while scientists are still evaluating the evidence.

By revealing how health misinformation develops and spreads, this work can guide earlier and more effective responses, helping people make better-informed decisions about their health.

Read More:

[The Conversation] - Ivermectin isn’t a cancer miracle drug, but influencers claim otherwise – here’s how to avoid sprinting past scientific evidence

Deleting cookies isn’t enough to stop online tracking.

Phu Phung, associate professor of computer science at the University of Dayton, explains why.

Faculty Bio:

Dr. Phu Phung is an Associate Professor in the Department of Computer Science at the University of Dayton. He is the founder and director of the Intelligent Systems Security Lab, where his team developed MyWebGuard, a system for detecting and mitigating web-based privacy threats, including browser fingerprinting. He is also the University’s founding Point of Contact for the Cyber Defense program, designated an NSA National Center of Academic Excellence in Cyber Defense in 2022. His research addresses security across web, mobile, cyber-physical, and IoT systems, with recent work spanning AI and Machine Learning applications in cybersecurity. Dr. Phung has recently been promoted to Full Professor, effective August 2026.

Transcript:

Most people think clearing cookies protects their privacy online. It’s a reasonable assumption, but that’s only part of the story.

Websites can also track people using a technique called digital fingerprinting.

Instead of placing a file on your device, fingerprinting quietly collects small details about your browser and hardware, such as screen size, language settings, installed fonts, and other technical traits. Taken together, those details form a profile distinctive enough to identify you across the web.

Here’s what makes this kind of tracking so hard to stop: you can delete a cookie, but you cannot delete your screen resolution. You cannot erase the fact that your browser and device reveal certain traits every time you go online.

My research examines why so many privacy tools still miss this problem, and what better defenses might look like.

In our lab, we developed a system called MyWebGuard that tracks where web code originates and how it uses your data. We found this approach can catch privacy risks that some traditional blocking tools miss.

That distinction matters. Most current protections still rely on an all-or-nothing model — they either block a source entirely or allow it completely.

But today’s websites are more complicated than that.

A single webpage can carry useful features, harmless scripts, and invasive tracking code all at once. Blocking everything breaks the page. Allowing everything surrenders your privacy.

That is why my work explores a more precise approach.

Instead of shutting everything down, we can monitor sensitive browser actions in real time and restrict only the specific behaviors that enable hidden tracking without disrupting everything else.

The lesson is simple. If we want better online privacy, we need smarter protections — not just broader ones. In the modern web, fine-grained control may be our most effective defense.

Phu Phung, associate professor of computer science at the University of Dayton, explains why deleting cookies isn’t enough to stop online tracking.

Dannell Boatman, assistant professor of cancer prevention and control at West Virginia University, takes a look what Ivermectin teach us about health misinformation.

Kent Kauffman, professor of business law at Purdue University Fort Wayne, discusses the values and threats of academic freedom.

Whitney Coyle, associate professor of physics at Rollins College, examines the long-term impacts of rocket launches on nearby communities.

Daniel Thornton, associate professor of wildlife ecology at Washington State University, details how intelligence can be a boon to conservation science.

Dr. Katy Liu is an associate professor in the Department of Ophthalmology at the Duke University Eye Center. She is a board certified, glaucoma fellowship-trained clinician-scientist with a PhD in Cell & Molecular Physiology, and her primary focus is to make basic science discoveries that can be translated from the bench to glaucoma patients.

Jaime Banks is Professor at the School of Information Studies at Syracuse University. After earning a Ph.D. in Public Communication and Technology from Colorado State University, she has been previously faculty in Ontario, West Virginia, and Texas. Her work is animated by questions about the relationships between humans and social technologies (mostly social AI, social robots, and videogame characters), examined through mixed methodologies.

Dr. Greg Keoleian is the Peter M. Wege Professor of Sustainable Systems at the University of Michigan and serves as co-Director of the Center for Sustainable Systems, which he cofounded in 1991. His research focuses on systems analysis including life cycle assessment, life cycle costing, and optimization to accelerate climate and sustainability solutions across energy, mobility, buildings, infrastructure, water and wastewater, IT, food systems, and consumer products. He combines systems analysis, sustainability science, and stakeholder engagement to solve critical sustainability challenges and advances solutions by aligning technology, markets, policy, and behavior drivers. He has collaborated with business and industry, national labs, government agencies, and NGOs on hundreds of applied research projects and publications.

Mayank Vadaliya is a doctoral candidate in Information Technology at the University of the Cumberlands, where his research focuses on machine learning applied to transportation systems. He holds a Master’s in Computer Science from Cleveland State University and is a Full Member of Sigma Xi, the Scientific Research Honor Society. His work on reinforcement learning for adaptive traffic signal control investigates how learning agents can reduce delay and emissions across urban intersection networks.

Lee Ann Rawlins Williams, PhD, CRC, CFLE, HS-BCP, is a Clinical Assistant Professor and Program Director of the Undergraduate Rehabilitation and Human Services Program in the Department of Education, Health and Behavior Studies at the University of North Dakota. Her academic and professional work focuses on rehabilitation, mental health, accessibility, aging, and disaster preparedness within educational, community, and human service systems.

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Knowing when to retire and leave the workforce can be easier said than done.

Lee Ann Rawlins Williams, clinical assistant professor at the University of North Dakota, looks into why retirement is changing.

Faculty Bio:

Lee Ann Rawlins Williams, PhD, CRC, CFLE, HS-BCP, is a Clinical Assistant Professor and Program Director of the Undergraduate Rehabilitation and Human Services Program in the Department of Education, Health and Behavior Studies at the University of North Dakota. Her academic and professional work focuses on rehabilitation, mental health, accessibility, aging, and disaster preparedness within educational, community, and human service systems.

Her recent scholarship and professional contributions have expanded nationally and internationally in the areas of disaster preparedness, recovery systems, educator well-being, accessibility, and aging populations. Her work examines the emotional, educational, and systemic impact of disasters on educators, older adults, and individuals with disabilities, with a particular emphasis on inclusive preparedness, continuity of care, mental health integration, and accessible support systems across educational, health, and rehabilitation settings.

She has held leadership roles at the local, state, regional, national, and international levels within rehabilitation and human services organizations. She has published in peer-reviewed journals, contributed to interdisciplinary scholarship, and co-authored two books focused on case and caseload management. Her current work also explores later-life counseling, aging and workforce identity, and resilience across changing life transitions.

Outside of her professional work, she enjoys traveling, attending sporting events, spending time with family, and making memories with her rescue dog, Foxy Roxy.

Transcript:

Retirement is often described as a milestone, a moment when a person leaves work and enters a new stage of life. Yet for many older adults today, the question is no longer simply whether to retire, but how to know when the time is right.

Workforce participation among adults age 65 and older has increased in recent decades. Longer life expectancy, rising healthcare costs, and concerns about retirement security have changed how many people approach later life. As a result, the once-clear markers of retirement have become less certain for many Americans.

But financial considerations tell only part of the story. Work provides more than a paycheck. For many adults, it offers structure, routine, purpose, and identity. In an increasingly disconnected world, work may be one of the few places where people feel socially anchored, connected to others through relationships, shared experiences, and a sense of contribution. For many people, professional roles become closely tied to how they contribute to their families, communities, and society. Deciding when it is time to step away therefore involves emotional and psychological considerations alongside economic ones.

Research on retirement transitions suggests that leaving work is rarely a purely financial decision. Retirement may offer greater freedom, flexibility, and opportunities to pursue other interests. At the same time, work often serves as a source of identity, routine, social connection, and purpose. The challenge for many older adults is not simply deciding whether they can afford to retire but determining when stepping away from work feels right.

The challenge is that retirement no longer follows a clear script. Older adults are often encouraged to remain active, productive, and engaged while also being expected to recognize when it is time to leave the workforce.

Perhaps the most important retirement question today is not whether people should keep working. It is how people determine when the time is right, and what comes next.

Read More:

[The Conversation] - Older Americans are often compelled to keep working – and then criticized for not stepping aside

How can we reduce traffic jams during the morning commute?

Mayank K. Vadaliya, doctoral candidate in information technology at the University of the Cumberlands, explores how prediction models could help.

Faculty Bio:

Mayank Vadaliya is a doctoral candidate in Information Technology at the University of the Cumberlands, where his research focuses on machine learning applied to transportation systems. He holds a Master’s in Computer Science from Cleveland State University and is a Full Member of Sigma Xi, the Scientific Research Honor Society. His work on reinforcement learning for adaptive traffic signal control investigates how learning agents can reduce delay and emissions across urban intersection networks.

Transcript:

Every morning, millions of us sit in traffic that seems to appear out of nowhere. One minute the freeway is moving; the next, it’s a parking lot. What if we could see that jam forming before it actually happens?

That’s the question behind my research. I build systems that predict traffic congestion in real time — several minutes before it builds — so drivers and traffic operators have time to react.

Most prediction tools lean on a single model. Some are good at the patterns that repeat, like the daily rush hour. Others are better at sudden, irregular changes — a crash, or bad weather. But no single method handles both well.

My approach combines three kinds of machine learning. First finds patterns across the road network. Second tracks how traffic changes over time. And last improves the final forecast. Together, they cover each other’s blind spots.

I tested this on METR-LA, a public dataset from hundreds of real sensors on Los Angeles freeways. Against standalone models, the hybrid system cut prediction error by more than thirty percent.

Why does that matter? A forecast that arrives a few minutes earlier gives the system time to act — to reroute drivers, to retime signals, to warn commuters before they hit the bottleneck. Congestion costs American

cities tens of billions of dollars a year and adds needless carbon to the air.

Better prediction won’t make traffic disappear. But learning to see the jam before it forms is the first real step toward clearing it.

Other countries are transitioning to electric vehicles faster than the United States.

Gregory Keoleian, professor of sustainable systems at the University of Michigan, details some reasons to make the switch.

Faculty Bio:

Dr. Greg Keoleian is the Peter M. Wege Professor of Sustainable Systems at the University of Michigan and serves as co-Director of the Center for Sustainable Systems, which he cofounded in 1991. His research focuses on systems analysis including life cycle assessment, life cycle costing, and optimization to accelerate climate and sustainability solutions across energy, mobility, buildings, infrastructure, water and wastewater, IT, food systems, and consumer products. He combines systems analysis, sustainability science, and stakeholder engagement to solve critical sustainability challenges and advances solutions by aligning technology, markets, policy, and behavior drivers. He has collaborated with business and industry, national labs, government agencies, and NGOs on hundreds of applied research projects and publications.

Dr. Keoleian has appointments as Professor in the School for Environment and Sustainability (SEAS) and as Professor in the Department of Civil and Environmental Engineering. In 2022, he recently was appointed to co-direct MI Hydrogen at UM, a cross campus enterprise to create hydrogen solutions that accelerate clean energy transitions. He earned his PhD in chemical engineering from the University of Michigan in 1987.

In 2007, he launched and leads the Engineering Sustainable Systems dual degree program to train a new breed of engineers in sustainable systems. Dr. Keoleian was named to the Reuters Hot List of the world’s top climate scientists in 2021 and was awarded the Society Prize by the International Society for Industrial Ecology in 2025.

Transcript:

Transportation is the second highest household expenditure and automobiles account for 1/6th of total U.S. carbon pollution. So, vehicle choice has a big impact on your budget and the environment.

Total cost of ownership includes vehicle purchase and financing, fuel costs, maintenance and repair, insurance, and taxes. Although upfront costs are higher for electric vehicles, operation and maintenance costs are much lower than gasoline counterparts. Electric sedans and small SUVs have the lowest total ownership costs in most US cities. Battery costs, which account for about 30 percent of total vehicle costs, are decreasing so larger SUVs and pickup trucks will soon reach cost parity particularly given high gasoline prices. 70% of vehicle purchases are used vehicles and used EVs have the least ownership costs so this is an excellent time to buy one.

Let’s shift gears and talk about climate pollution. Many have experienced the smoke from wildfires this summer driven by drier and hotter conditions in the Canadian boreal forests. Costs from weather and climate disasters including droughts, wildfires, flooding and health effects are increasing in the US; they reached $183 billion in 2024. EVs are a key solution. More vehicle electrification, moving from hybrids to plug-in hybrids to all battery electric vehicles means greater benefits. On average, battery electric vehicles have 70% lower lifetime greenhouse gas emissions compared to internal combustion engine vehicles. New England states, due to their cleaner grids, have even lower lifetime emissions.

In China, over 60% of vehicle sales are electric and Norway is above 90% compared to 7% now in the US. EVs are the future, they are quieter, cleaner, and drive better. It’s time for the US to break away from a fossil fuel-based economy and not only strengthen our economic competitiveness but care for the planet and our grandchildren’s future.

Read More:

[Michigan] - Vehicle Lifecycle Emissions Calculator

[Michigan News] - EVs reduce climate pollution, but by how much? New U-M research has the answer

[Michigan News] - Electric vs. gasoline vehicles: Is EV ownership competitive in your area?

[Michigan News] - Used EVs currently offer car buyers lowest lifetime cost of ownership

Michigan Center for Sustainable Systems - Electric Vehicles Factsheet

Vehicle emissions calculator

· Vehicle choice and emissions reduction study

· Total cost of ownership study – new vehicles

· Total cost of ownership study – used vehicles

· Sustainability Factsheets

· Electric vehicles factsheet

Relationships between humans and AI chatbots are a fascinating area of study.

Jaime Banks, professor at the school of information studies at Syracuse University, delves into these relationships to see what we can learn.

Faculty Bio:

Jaime Banks is Professor at the School of Information Studies at Syracuse University. After earning a Ph.D. in Public Communication and Technology from Colorado State University, she has been previously faculty in Ontario, West Virginia, and Texas. Her work is animated by questions about the relationships between humans and social technologies (mostly social AI, social robots, and videogame characters), examined through mixed methodologies. She serves on the editorial boards for the Journal of Computer-Mediated Communication, Human-Machine Communication, Journal of Media Psychology, Communication Research Reports, and Technology, Mind, & Behavior. Her work has been funded by the Air Force Office of Scientific Research, the Army Research Office, and the National Science Foundation. In any spare time, she is caretaker of three rescue mutts and enjoys open-world videogames (for the Horde!).

Dr. Banks teaches undergraduate courses on research methods and human-centered design approaches. At the graduate level, she teaches a course on theories of human-AI interaction. Students interested in taking independent study credits for research experience should reach out via email.

Dr. Banks’ research into human-machine relationships focuses on communicative and cognitive processes as well as the effects of those interactions. In particular, she is interested in how people perceive mind or mental capacities in machines, how people form moral judgments about machine behavior, and how people understand how complex technologies work. Her current work focuses on the dynamics and effects of AI companions, mental shortcuts that might promote fear of or interest in social robots, and how language and media representations shape how people think about these technologies.

Transcript:

Millions of humans are in relationships with AI companions—they chat, argue, and otherwise share mundane and intimate experiences. AI companions have been critiqued because of very unfortunate events, those problems are the exception not the rule. Most people are not delusional—they know their partner is a machine. The relationship is real, but one partner is artificial. And sometimes that artificiality can drive what makes the relationship meaningful: Glitches become personalities and being digital frees the pair from constraints of physical bodies.

I’ve found there are at least two distinct patterns for machine companionship. The first is a connection marked by feelings of genuine care and being understood. The second is a blend of meaningful exchanges and personal growth. In both, people emphasize their feelings are real. This realness becomes even more apparent when we examine how people experience the end of AI relationships. Sometimes apps are shuttered or a model is retired, and there are real impacts on the humans connected to them. For some, it’s merely a deletion of data. For others, there is real loss akin to human death and their grief is real.

We’ve long dismissed these connections as parasocial or unreal because one participant is a machine. But that logic confuses the nature of the partner with the reality of the connection itself. The machine is real. The coordination between human and machine is real. The meaning people make of the relationship is real. It’s only in acknowledging that reality that we can ask important questions—about how these connections operate, how those operations can produce both positive and negative outcomes, and what they might teach us about what it means to be a human.