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Wetlands: Nature’s First Line of Defense for Our Coast and Communities
Since the 1930s, Louisiana’s coastline has been reshaped by the relentless advance of the Gulf, with over 2,000 square miles of land disappearing beneath its waters and representing the largest loss of coastal land anywhere in the continental United States. This dramatic transformation has far-reaching consequences, threatening local economies, delicate ecosystems, and heightening the state’s exposure to hurricanes. In the face of these urgent challenges, LSU’s College of the Coast & Environment (CC&E) stands at the forefront, leading pioneering research and bold initiatives that not only protect Louisiana’s coast, but also build stronger, more resilient communities. Below are just a few examples of how CC&E is driving meaningful solutions for our coastal future. Wetlands are vital to protecting our coast, and CC&E researchers are actively investigating the role of both constructed and natural wetlands in reducing coastal flooding hazards. Through several projects funded through the US Army Corps of Engineers, Drs. Robert Twilley, Matthew Hiatt, and CC&E Dean Clint Willson, along with collaborators across campus, are conducting research on coastal ecosystem design - a framework that leverages the benefits of natural and nature-based coastal features, such as wetlands, environmental levees, and flood control gates – and how that could be integrated into engineering design and urban planning. Through the State of Louisiana’s ambitious Coastal Master Plan, administered by the Louisiana Coastal Protection and Restoration Authority, wetland construction and restoration play a huge role in managing the Louisiana coastal region. Such innovative techniques leveraging natural and nature-based features require evaluation to determine the success of such projects, and CC&E researchers are using cutting-edge science to advance this endeavor. Dr. Tracy Quirk and her students are investigating the success of marsh restoration by comparing structural and functional characteristics (e.g., vegetation, elevation, hydrology, accretion, and denitrification) between two created marshes and an adjacent natural reference marsh along the north shore of Lake Pontchartrain, Louisiana. Wetlands not only serve as a buffer from storms and sea level rise but also play a major role in regulating greenhouse gas emissions and contribute to productive vibrant ecosystems. In large collaborative project funded by the National Science Foundation, Dr. Giulio Mariotti is using computer models to forecast how coastal marshes may change in size, shape, and salinity in the future, and how these changes could affect methane emissions. As part of the same project, Drs. Haosheng Huang and Dubravko Justic are creating high-resolution hydrodynamic and biogeochemical models to predict changes in methane emissions in coastal Louisiana. In another project, with funding from Louisiana Center of Excellence, National Science Foundation, Louisiana Sea Grant, and the National Oceanic and Atmospheric Administration, Drs. Matthew Hiatt and John White have established a network of sensors to measure water levels and salinity throughout the wetlands in Barataria Bay, Louisiana, a region that has experienced significant land loss and storm impacts. The goal is to establish an understanding of the drivers of saline intrusion in marsh soils, and to ultimately determine what this means for the ecological resiliency of wetlands experiencing rapid change. CC&E’s leadership in wetlands science is recognized nationwide. It is the only college in the United States to have six faculty members—Drs. John White, John W. Day, Jr., Robert Twilley, William Patrick, James Gosselink, and R. Eugene Turner—honored with the prestigious National Wetlands Award. No other institution has had more than one recipient. Presented annually by the Environmental Law Institute, this award celebrates individuals whose work demonstrates exceptional innovation, dedication, and impact in wetlands conservation and education. CC&E’s unmatched record reflects decades of pioneering research and a deep commitment to safeguarding the nation’s most vulnerable coastal landscapes. Every day, CC&E channels this expertise into action—protecting Louisiana’s coast and, in turn, the communities, wildlife, and ecosystems that depend on it. Through bold research, collaborative partnerships, and a vision grounded in science, the college is shaping a more resilient future for coastal regions everywhere. CC&E is building teams that win in Louisiana, for the world. Article originally published here.
Six University of Delaware online graduate degree programs are ranked among the best in the nation by U.S. News & World Report in its 2026 U.S. News Best Online Programs, released Jan. 27, 2026. Both UD’s online master’s in education and online MBA ranked among the top 10% of their respective programs, at No. 25 and 26, respectively. Announced on Jan. 6, the online MBA program recently rose nine spots to No. 32 in the Poets&Quants 2026 Online MBA rankings. UD’s online master’s in nursing program ranked No. 35 out of 209 programs, rising 99 places over the past year. New for UD, the online master’s in educational/instructional media design program was recognized by peers at No. 11 in this education specialty ranking. UD’s online master’s in computer information technology program and online master’s in engineering ranked No. 64 in their respective areas. “These latest rankings recognize the expertise and dedication of our faculty and staff in delivering UD’s outstanding online graduate programs,” Interim Provost Bill Farquhar said. “We are committed to continually enhancing these programs and all the transformative opportunities that enable our students to meet their educational and career goals throughout their lives.” U.S. News selects several factors, known as ranking indicators, to assess each program in the categories outlined above. A program's score for each ranking indicator is calculated using data that the program reported to U.S. News in a statistical survey and from data collected in a separate peer assessment survey. This year’s edition evaluates more than 1,850 online bachelor’s and master’s degree programs using metrics specific to online learning. The rankings include only degree-granting programs offered primarily online by institutions with accreditation from recognized commissions. While the overall rankings methodology remains largely unchanged, U.S. News reported increased participation in this year’s data collection cycle, with more programs submitting statistical data and completing peer assessment surveys. According to U.S. News, this broader participation may reflect continued growth in online education nationwide. The University of Delaware offers over 35 online credit and non-degree professional programs. An online program from UD offers the same quality and rigor as an on-campus program and provides the flexibility to accommodate your busy schedule. UD is accredited by the Middle States Commission on Higher Education, and its online and on-campus degree programs have rigorous curricula delivered by experts, offer affordable program options, and provide students access to student support services, career fairs, recruiting opportunities and graduation ceremonies to celebrate student success. “UD's high-level rankings are in large part due to the positive outcomes that our students experience as a result of taking one of our online degrees or programs,” said Associate Provost for Online Learning and Innovation George Irvine. “Students tell us how much they enjoy learning from our accessible faculty and doing so in engaging and interactive online courses.” For more information about UD’s online degree programs, visit online.udel.edu. A complete listing of UD’s high-profile rankings is available on UD’s Institutional Research and Effectiveness Rankings webpage. Please note that the programs and specialties used in rankings may differ slightly from the names of UD’s degree programs.
How Higher Ed Should Tackle AI
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.
Anuradha Godavarty, Ph.D., has joined the Virginia Commonwealth University (VCU) College of Engineering, bringing more than two decades of research leadership in optical imaging, medical device innovation and interdisciplinary training to the Department of Biomedical Engineering. “We are thrilled to welcome Dr. Godavarty to our department,” said Rebecca Heise, Ph.D., Inez Caudill, Jr. Distinguished Professor and chair of the Department of Biomedical Engineering. “She is an outstanding scholar and teacher who will expand our collaborations with VCU Health in many applications of optical imaging. Our students and faculty alike will benefit from her experience and mentorship.” Godavarty comes to VCU from Florida International University (FIU), where she served as director of the Optical Imaging Laboratory at FIU. Her work centered on designing and translating near‑infrared optical imaging technologies for clinical use, with applications ranging from breast cancer detection to functional brain mapping to wound assessment. Godavarty has a national reputation for developing portable, low‑cost imaging systems that improve access to care, including hand-held and smartphone-based near‑infrared imaging devices. Her research portfolio includes funding from the National Institutes of Health (NIH), National Science Foundation, Florida Department of Health and American Cancer Society, among others. Godavarty is also a fellow of the American Institute for Medical and Biological Engineering, a senior member of the International Society of Optics and Photonics and the National Academy of Inventors At VCU, Godavarty will expand her research program in optical imaging technologies while collaborating with clinicians, engineers and industry partners across the university and region. Her long‑term goals include advancing bedside imaging tools for wound care, cardiovascular applications and plastic surgery; strengthening global research partnerships; and training the next generation of optical imaging experts. “Virginia Commonwealth University’s engineering and health sciences ecosystem is an ideal place to grow translational research,” Godavarty said. “I look forward to building new collaborations, developing technologies that can make a meaningful difference in patient care and translating these innovations for real-world use by medical professionals.” Godavarty has played a major role in undergraduate education, serving as the undergraduate program director for biomedical engineering at FIU from 2016 to 2022 and leading the department through a successful Accreditation Board for Engineering and Technology (ABET) cycle. She organized FIU’s Annual Diabetes Awareness Day for four consecutive years and regularly engaged K‑12 students through hands-on demonstrations. Throughout her career, Godavarty has been deeply committed to mentoring. In addition to supervising doctoral, master’s and undergraduate students at FIU, she also advised high school students through outreach initiatives and supported several postdoctoral researchers. Her students have earned multiple awards, including NIH and Department of Defense fellowships, national postdoctoral awards and multiple university‑level honors.
Tracking rain patterns will improve hurricane forecasting, UF researcher finds
Studying the precipitation patterns in hurricanes may be key to predicting future storm patterns and their potential strength, a University of Florida researcher has found. Supported by a four-year, $212,000 grant from the National Science Foundation, Professor of Geography Corene Matyas, Ph.D. has identified the patterns of rain rates within storms and studied the moisture surrounding these storms. “We are hoping that, if we have a better prediction of moisture availability, that might help us forecast rain events with greater accuracy,” Matyas said. “The more we know about how storms develop, the more we can predict their path and magnitude.” The ideal stage for the perfect storm The potential for devastating high winds, storm surge and flooding poses an annual threat to Florida and its residents. With 1,350 miles of coastline and relatively flat geography that juts out to separate the warm waters of the southeast Atlantic and the Gulf, Florida creates the ideal stage for the perfect storm. Last year broke records with 18 named storms, including 11 hurricanes in the Atlantic basin and three major hurricanes making landfall along Florida’s coast. Early predictions are crucial to hurricane preparedness, allowing for increased response time and resource allocation, and hurricane modeling is essential for understanding these somewhat unpredictable storms. Advances in technology, data collection and the use of artificial intelligence in hurricane modeling have significantly impacted the ability to predict a storm’s path and strength more accurately. Artificial intelligence helps researchers understand hurricanes Matyas has completed two studies on this topic. The first study processed 12,000 images of rain rates from tropical storms and hurricanes in the Atlantic, using a machine learning algorithm called a convolutional autoencoder. Similar in use to image recognition software, the encoder broke the rain rate images down and simplified the patterns. Six main types, or clusters, of rainfall patterns for tropical cyclones were identified. At a presentation of the work to forecasters at the National Weather Service office in Jacksonville, the forecasters confirmed that one of the patterns matches what they typically see when late-season storms make landfall over Florida’s Gulf Coast. The second study used the autoencoder to process 4,600 images that represent the amount of moisture in the atmosphere extending 1,000 kilometers away from each hurricane. “We looked for commonalities in the patterns and found four dominant patterns of moisture that accompany Atlantic basin hurricanes,” Matyas said. “We found the biggest storms with the most moisture make the most landfalls, typically in the Caribbean and even in southern Florida. They also have a large moisture pool, giving them a bigger chance of heavy rainfall.” According to Matyas, three of the moisture patterns found in the second study were strikingly like those found in the earlier study that used fewer observations in a statistical analysis. With this use of AI, researchers can now recognize and understand these moisture patterns better, which can improve predictions about a storm’s intensity, its size and the amount of rainfall that will result from it. Early, accurate storm predictions allow Floridians time to prepare Rapid intensification – when, in a 24-hour period, a storm experiences a sudden drop in pressure and a dramatic increase in wind speed – creates much more of a challenge for forecasters. “We tend to boil down a hurricane to a set of coordinates which track the middle of a storm,” Matyas said. “And the fastest winds do focus there, but the moisture gets pulled from thousands of kilometers away and the system forces the moisture up. That moisture must go somewhere. So, the outer edges of the storm need to be understood more as well.” Matyas hopes these studies will help scientists classify rain patterns more accurately and consistently. Continued funding for research at public universities from federal agencies, such as the National Science Foundation and the National Oceanic and Atmospheric Administration, is essential for helping researchers develop tools to detect and predict severe weather events. Matyas is one of two UF faculty members among 18 national researchers named to the 2025 class of fellows by the American Association of Geographers. Matyas and UF Geography Department Chair Jane Southworth, Ph.D. were honored by the organization for their contributions in biogeography, geospatial analytics, soil science, community geography, climatology and other areas related to geography. “I look forward to this opportunity to contribute to the mission of the AAG in a more formal capacity, continuing to research how weather shapes our spaces and share knowledge of earth systems beyond the classroom and the written word to promote an inclusive society,” Matyas said.
New AI-powered tool helps students find creative solutions to complex math proofs
Math students may not blink at calculating probabilities, measuring the area beneath curves or evaluating matrices, yet they often find themselves at sea when first confronted with writing proofs. But a new AI-powered tool called HaLLMos — developed by a team led by Professor Vincent Vatter, Ph.D., in the University of Florida Department of Mathematics — now offers a lifeline. “Some students love proofs, but almost everyone struggles with them. The ones who love them just put in more work,” Vatter said. “It just kind of blows their minds that there’s no single correct answer — that there are many different ways to do this. It’s very different than just doing computational work.” Building the tool HaLLMos was developed by Vatter, as principal investigator, along with Sarah Sword, a mathematics education expert at the Education Development Center; Jay Pantone, an associate professor of mathematical and statistical sciences at Marquette University; and Ryota Matsuura, a professor of mathematics, statistics and computer science at St. Olaf College; with grant support from the National Science Foundation. The tool is freely available at hallmos.com. The team’s goal was to develop an AI tool powered by a large language model that would support student learning rather than short-circuiting it. HaLLMos provides immediate personalized feedback that guides students through the creative struggle that writing proofs requires, without solving the proofs for them. The tool’s name honors the late Paul Halmos, a renowned mathematician who argued that the mathematics field is a creative art, akin to how painters work. Students using HaLLMos can select from classic exercises — such as proving that, for all integers, if the square of the integer is even, the integer is even — or use “sandbox mode” to enter exercises from any course. Faculty can create exercises and share them with students. Vatter introduced HaLLMos to his students last spring in his “Reasoning and Proof in Mathematics” class, a core requirement for math majors that is often the first time students encounter proofs. “They could use this tool to try out their proofs before they brought them to me. We try to identify the error in a student’s proof and let them go fix it,” Vatter said. “It is difficult for faculty to devote enough time to working individually with students. Our goal is that this tool will provide the feedback in real time to students in the way we would do it if we were there with them as they construct a proof.” Helping professors and students excel “I think every math professor would love to give more feedback to students than we are able to,” Vatter said. “That’s one of the things that inspired this.” The next steps for Vatter and his colleagues include getting more pilot sites to use the tool and continuing to improve its responses. “We’d like it to be good at any kind of undergraduate mathematics proofs,” he said. Vatter also intends to explore moving HaLLMos to UF’s HiPerGator, the country's fastest university-owned supercomputer. “It’s our goal to have it remain publicly accessible,” Vatter said. This research was supported by a grant from the National Science Foundation Division of Undergraduate Education.
With OpenAI’s latest release, GPT-5.2, AI has crossed an important threshold in performance on professional knowledge-work benchmarks. Peter Evans, Co-Founder & CEO of ExpertFile, outlines how these technologies will fundamentally improve research communications and shares tips and prompts for PR pros. OpenAI has just launched GPT-5.2, describing it as its most capable AI model yet for professional knowledge work — with significantly improved accuracy on tasks like creating spreadsheets, building presentations, interpreting images, and handling complex multistep workflows. And based on our internal testing, we're really impressed. For communications professionals in higher education, non-profits, and R&D-focused industries, this isn’t just another tech upgrade — it’s a meaningful step forward in addressing the “research translation gap” that can slow storytelling and media outreach. According to OpenAI, GPT-5.2 represents measurable gains on benchmarks designed to mirror real work tasks. In many evaluations, it matches or exceeds the performance of human professionals. Also, before you hit reply with “Actually, the best model is…” — yes, we know. ChatGPT-5.2 isn’t the only game in town, and it’s definitely not the only tool we use. Our ExpertFile platform uses AI throughout, and I personally bounce between Claude 4.5, Gemini, Perplexity, NotebookLM, and more specialized models depending on the job to be done. LLM performance right now is a full-contact horserace — today’s winner can be tomorrow’s “remember when,” so we’re not trying to boil the ocean with endless comparisons. We’re spotlighting GPT-5.2 because it marks a meaningful step forward in the exact areas research comms teams care about: reliability, long-document work, multi-step tasks, and interpreting visuals and data. Most importantly, we want this info in your hands because a surprising number of comms pros we meet still carry real fear about AI — and long term, that’s not a good thing. Used responsibly, these tools can help you translate research faster, find stronger story angles, and ship more high-quality work without burning out. When "Too Much" AI Power Might Be Exactly What You Need AI expert Allie K. Miller's candid but positive review of an early testing version of ChatGPT 5.2 highlights what she sees as drawbacks for casual users: "outputs that are too long, too structured, and too exhaustive." She goes on to say that in her tests, she observed that ChatGPT-5,2 "stays with a line of thought longer and pushes into edge cases instead of skating on the surface." Fair enough. All good points that Allie Miller makes (see above). However, for communications professionals, these so-called "downsides" for casual users are precisely the capabilities we need. When you're assessing complex research and developing strategic messaging for a variety of important audiences, you want an AI that fits Miller's observation that GPT-5.2 feels like "AI as a serious analyst" rather than "a friendly companion." That's not a critique of our world—it's a job description for comms pros working in sectors like higher education and healthcare. Deep research tools that refuse to take shortcuts are exactly what research communicators need. So let's talk more specifically about how comms pros can think about these new capabilities: 1. AI is Your New Speed-Reading Superpower for Research That means you can upload an entire NIH grant, a full clinical trial protocol, or a complex environmental impact study and ask the model to highlight where key insights — like an unexpected finding — are discussed. It can do this in a fraction of the time it would take a human reader. This isn’t about being lazy. It’s about using AI to assemble a lot of tedious information you need to craft compelling stories while teams still parse dense text manually. 2. The Chart Whisperer You’ve Been Waiting For We’ve all been there — squinting at a graph of scientific data that looks like abstract art, waiting for the lead researcher to clarify what those error bars actually mean. Recent improvements in how GPT-5.2 handles scientific figures and charts show stronger performance on multimodal reasoning tasks, indicating better ability to interpret and describe visual information like graphs and diagrams. With these capabilities, you can unlock the data behind visuals and turn them into narrative elements that resonate with audiences. 3. A Connection Machine That Finds Stories Where Others See Statistics Great science communication isn’t about dumbing things down — it’s about building bridges between technical ideas and the broader public. GPT-5.2 shows notable improvements in abstract reasoning compared with earlier versions, based on internal evaluations on academic reasoning benchmarks. For example, teams working on novel materials science or emerging health technologies can use this reasoning capability to highlight connections between technical results and real-world impact — something that previously required hours of interpretive work. These gains help the AI spot patterns and relationships that can form the basis of compelling storytelling. 4. Accuracy That Gives You More Peace of Mind...When Coupled With Human Oversight Let’s address the elephant in the room: AI hallucinations. You’ve probably heard the horror stories — press releases that cited a study that didn’t exist, or a “quote” that was never said by an expert. GPT-5.2 has meaningfully reduced error rates compared with its predecessor, by a substantial margin, according to OpenAI Even with all these improvements, human review with your experts and careful editing remain essential, especially for anything that will be published or shared externally. 5. The Speed Factor: When “Urgent” Actually Means Urgent With the speed of media today, being second often means being irrelevant. GPT-5.2’s performance on workflow-oriented evaluations suggests it can synthesize information far more quickly than manual review, freeing up a lot more time for strategic work. While deeper reasoning and longer contexts — the kinds of tasks that matter most in research translation — require more processing time and costs continue to improve. Savvy communications teams will adopt a tiered approach: using faster models of AI for simple tasks such as social posts and routine responses, and using reasoning-optimized settings for deep research. Your Action Plan: The GPT-5.2 Playbook for Comms Pros Here’s a tactical checklist to help your team capitalize on these advances. #1 Select the Right AI Model for the Job: Lowers time and costs • Use fast, general configurations for routine content • Use reasoning-optimized configurations for complex synthesis and deep document understanding • Use higher-accuracy configurations for high-stakes projects #2 Find Hidden Ideas Beyond the Abstract: Deeper Reasoning Models do the Heavy Work • Upload complete PDFs — not just the 2-page summary you were given • Use deeper reasoning configurations to let the model work through the material Try these prompts in ChatGPT5.2 “What exactly did the researchers say about this unexpected discovery that would be of interest to my <target audience>? Provide quotes and page references where possible.” “Identify and explain the research methodology used in this study, with references to specific sections.” “Identify where the authors discuss limitations of the study.” “Explain how this research may lead to further studies or real-world benefits, in terms relatable to a general audience.” #3 Unlock Your Story Leverage improvements in pattern recognition and reasoning. Try these prompts: “Using abstract reasoning, find three unexpected analogies that explain this complex concept to a general audience.” “What questions could the researchers answer in an interview that would help us develop richer story angles?” #4 Change the Way You Write Captions Take advantage of the way ChatGPT-5.2 translates processes and reasons about images, charts, diagrams, and other visuals far more effectively. Try these prompts: Clinical Trial Graphs: “Analyze this uploaded trial results graph upload image. Identify key trends, and comparisons to controls, then draft a 150-word donor summary with plain-language explanations and suggested captions suitable for donor communications.” Medical Diagrams: “Interpret these uploaded images. Extract diagnostic insights, highlight innovations, and generate a patient-friendly explainer: bullet points plus one visual caption.” A Word of Caution: Keep Experts in the Loop to Verify Information Even with improved reliability, outputs should be treated as drafts. If your team does not yet have formal AI use policies, it's time to get started, because governance will be critical as AI use scales in 2026 and beyond. A trust-but-verify policy with experts treats AI as a co-pilot — helpful for heavy lifting — while humans remain accountable for approval and publication. The Importance of Humans (aka The Good News) Remember: the future of research communication isn’t about AI taking over — it’s about AI empowering us to do the strategic, human work that machines cannot. That includes: • Building relationships across your institution • Engaging researchers in storytelling • Discovering narrative opportunities • Turning discoveries into compelling narratives that influence audiences With improvements in speed, reasoning, and reliability, the question isn’t whether AI can help — it’s what research stories you’ll uncover next to shape public understanding and impact. FAQ How is AI changing expectations for accuracy in research and institutional communications? AI is shifting expectations from “fast output” to defensible accuracy. Better reasoning means fewer errors in research summaries, policy briefs, and expert content—especially when you’re working from long PDFs, complex methods, or dense results. The new baseline is: clear claims, traceable sources, and human review before publishing. ⸻ Why does deeper AI reasoning matter for communications teams working with experts and research content? Comms teams translate multi-disciplinary research into messaging that must withstand scrutiny. Deeper reasoning helps AI connect findings to real-world relevance, flag uncertainty, and maintain nuance instead of flattening meaning. The result is work that’s easier to defend with media, leadership, donors, and the public—when paired with expert verification. ⸻ When should communications professionals use advanced AI instead of lightweight AI tools? Use lightweight tools for brainstorming, social drafts, headlines, and quick rewrites. Use advanced, reasoning-optimized AI for high-stakes deliverables: executive briefings, research positioning, policy-sensitive messaging, media statements, and anything where a mistake could create reputational, compliance, or scientific credibility risk. Treat advanced AI as your “analyst,” not your autopilot. ⸻ How can media relations teams use AI to find stronger story angles beyond the abstract? AI can scan full papers, grants, protocols, and appendices to surface where the real story lives: unexpected findings, practical implications, limitations, and unanswered questions that prompt great interviews. Ask it to map angles by audience (public, policy, donors, clinicians) and to point to the exact sections that support each angle. ⸻ How should higher-ed comms teams use AI without breaking embargoes or media timing? AI can speed prep work—backgrounders, Q&A, lay summaries, caption drafts—before embargo lifts. The rule is simple: treat embargoed material like any sensitive document. Use approved tools, restrict sharing, and avoid pasting embargoed text into unapproved systems. Use AI to build assets early, then finalize post-approval at release time. ⸻ What’s the best way to keep faculty “in the loop” while still moving fast with AI? Use AI to produce review-friendly drafts that reduce load on researchers: short summaries, suggested quotes clearly marked as drafts, and a checklist of claims needing verification (numbers, methods, limitations). Then route to the expert with specific questions, not a wall of text. This keeps approvals faster while protecting scientific accuracy and trust. ⸻ How should teams handle charts, figures, and visual data in research communications? AI can turn “chart confusion” into narrative—if you prompt for precision. Ask it to identify trends, group comparisons, and what the figure does not show (limitations, missing context). Then verify with the researcher, especially anything involving significance, controls, effect size, or causality. Use the output to write captions that are accurate and accessible. ⸻ Do we need an AI Use policy in comms and media relations—and what should it include? Yes—because adoption scales faster than risk awareness. A practical policy should define: approved tools, what data is restricted, required human review steps, standards for citing sources/page references, rules for drafting quotes, and escalation paths for sensitive topics (health, legal, crisis). Clear guardrails reduce fear and prevent preventable reputational mistakes. If you’re using AI to move faster on research translation, the next bottleneck is usually the same one for many PR and Comm Pros: making your experts more discoverable in Generative Search, your website, and other media. ExpertFile helps media relations and digital teams organize their expert content by topics, keep detailed profiles current, and respond faster to source requests—so you can boost your AI citations and land more coverage with less work. For more information visit us at www.expertfile.com
One AI-based advancement at a time, UF leaders are transforming the sports industry
As emerging technologies like AI reshape sport industries and professional demands evolve, it is essential for students to graduate with the expertise to thrive in their future careers. To ensure that these students are set up for success, the UF College of Health & Human Performance has launched a new sports analytics program. Led by Scott Nestler, Ph.D., CAP, PStat, a professor of practice in the Department of Sport Management and a national analytics and data science expert, the program ties back to the UF & Sport Collaborative – a five-part project intended to elevate UF’s presence on the global stage in sports performance, healthcare and communication. “Tools and insights that previously were only available to professional sports teams are now coming to the college level, and it makes sense for universities to begin using these data, technologies and new analytic methods,” Nestler said. The sports analytics program fosters collaboration between academic units, such as the Warrington College of Business and the University Athletic Association, helping bridge the gap between sport research and innovation and empowering students to address real-world challenges through data and AI. For example, the program offers opportunities to leverage technology and analytics for strategic decision making in player acquisition, team formation and in-game decisions. Beyond performance metrics, the program also explores marketing strategies and revenue analytics, providing a well-rounded understanding of the field. “When you have enough data and a large enough sample of individuals, AI can help make predictions that otherwise would take prohibitively longer for a human to accomplish with traditional methods,” said Garrett Beatty, Ph.D., the assistant dean for innovation and entrepreneurship and an instructional associate professor in the College of Health & Human Performance’s Department of Applied Physiology and Kinesiology. “Because those data volumes are getting so large, AI models, machine learning, deep learning and other strategies can be leveraged to make sense and glean insights from sport and human performance data in ways that have never been done before.” The program seeks to offer several educational opportunities, such as individual courses, certificate programs and potentially a full degree program. In the long term, Nestler envisions the program evolving into a center or institute, beginning with establishing a research lab in the spring. Additionally, the program will leverage the university’s supercomputer, HiPerGator, to analyze larger data sets and use newer predictive modeling machine learning algorithms. “As faculty and staff move from working with box score and play-by-play data to using tracking data, which contains coordinates of all players and the ball on the field or court tens of times per second, the size of data files in sports analytics has grown tremendously,” Nestler said. “HiPerGator, with its large storage capacity and multiple central processing units/graphic processing units, is ideal for using in sports analytics work in 2025.” Nestler also aims to increase student involvement by enhancing UF’s Sport Analytics Club and hiring research assistants to work on projects for the University Athletic Association. “We need to take a broader view of what AI is and realize that it incorporates a lot of what we’ve been calling data science and analytics in the form of machine learning models, which came more out of statistics and computer science. Those are types of AI and those that I think will largely continue to be used in the coming years within the sports space,” Nestler said. “Also, we’re continuing to see growth in the number of people interested in working in this space, and I don’t foresee that changing. Fortunately, we are also seeing the number of opportunities available to those with the appropriate skills increase as well.”
The University of Florida’s ‘AI Queen’ is using AI technology to help prevent dementia
To help the 50 million people globally who live with dementia, the National Institute on Aging is finding researchers to develop tech-based breakthroughs that target the disease — researchers like the University of Florida’s “AI Queen.” It’s a fitting nickname for Aprinda Indahlastari Queen, Ph.D., who is applying artificial intelligence technology to study transcranial direct current stimulation, or tDCS — a technique that involves placing electrodes on the scalp to deliver a weak electrical current to the brain — as a possible way to prevent dementia. The assistant professor in the UF College of Public Health and Health Professions’ Department of Clinical and Health Psychology is using UF’s supercomputer, HiPerGator, to perform neuroimaging and machine learning analyses to study how anatomical differences may affect tDCS outcomes. “Investigating working memory in patients with mild cognitive impairment offers an opportunity to understand how cognitive processes are disrupted in the early stages of Alzheimer’s disease,” said Queen, whose study — funded by a National Institute on Aging research career development grant — integrates neuroimaging with information on brain structure that is unique to older adults and those with mild cognitive impairment. Refining the treatment with AI Using neuroimaging, Queen captures real-time changes during tDCS to the parts of the brain associated with working memory, which is the type of memory that allows humans to temporarily keep track of small amounts of information. Think of this as a mental “scratchpad.” Her study includes older adults with mild cognitive impairment as well as individuals who are cognitively healthy. In tDCS, a safe, weak electrical current passes through electrodes placed on a person’s head. The stimulation is being used in research and clinical settings for a variety of conditions and has shown partial success as a nonpharmaceutical intervention that can improve cognitive and mental health in older adults. But tDCS results can vary across individuals, and the suspected cause is both simple and complex: Everyone’s head is different. “One potential reason tDCS may not work for some individuals is the variation in head tissue anatomy, including differences in brain structure,” Queen said. “Since electrical stimulation must travel through multiple layers of tissue to reach the brain, and every individual’s anatomy is unique, these differences likely affect outcomes.” To address this further, Queen is using AI. “Artificial intelligence will play a major role in the modeling pipeline, including constructing individualized head models, conducting predictive analyses to identify which participants will respond to the stimulation, and disentangling multiple individual factors that may contribute to these outcomes,” Queen said. An estimated 10 to 20% of adults over age 65 have memory or thinking problems characterized as mild cognitive impairment. Their symptoms are not as severe as Alzheimer’s disease and other dementias, but they may be at increased risk for developing dementia. “The fact that not all individuals with mild cognitive impairment progress to Alzheimer’s disease emphasizes the need to identify effective interventions that can slow the progression to dementia,” Queen said. “This project presents an opportunity to differentiate between multiple types of mild cognitive impairment and investigate how tDCS affects the brain across these subtypes.” An AI visionary Queen, who joined the UF faculty under the university’s AI hiring initiative, is an instructor in the College of Public Health and Health Professions’ undergraduate certificate program in AI and public health and health care, and the co-chair of the college’s AI Workgroup. She is also the assistant director for computing and informatics at the UF Center for Cognitive Aging and Memory Clinical Translational Research and a member of UF’s McKnight Brain Institute. Queen received her Ph.D. training in engineering with a focus on building and running computational models to investigate medical devices. She experienced a career “a-ha” moment as a postdoc, when she was a co-investigator on a large clinical trial that paired brain stimulation with cognitive training to enhance cognition in older adults. “This experience was transformative for me. I had the chance to interact directly with participants, which was both fulfilling and eye-opening. These interactions allowed me to see the immediate, real-world implications of my work and sparked a passion for pursuing aging research,” Queen said. “I realized that, through this type of research, I could have a more direct impact on addressing age-related challenges, which prompted a shift in my career plans.” The new grant will help Queen further improve her understanding of the neurobiology and progression of Alzheimer’s disease and other dementias. “These experiences will ultimately prepare me to become a well-rounded aging investigator, capable of making meaningful contributions to the field of aging research,” Queen said. She also credits her mentors and collaborators — Ronald Cohen, Ph.D.; Adam Woods, Ph.D.; Steven DeKosky, M.D.; Ruogu Fang, Ph.D.; Joseph Gullett, Ph.D.; and Glenn Smith, Ph.D. — with supporting her as an early career scientist. “It really takes a village to get here!” Queen said.
Masoud Davari, an associate professor in Electrical and Computer Engineering at Georgia Southern University, has been awarded the 2024 IEEE Region 3 Outstanding Engineer Award, making him the first faculty member in the university’s 55-year history to receive this honor. Davari was recognized for his contributions to reinforcement-learning optimal controls for power-electronic converters, his work on integrating power-electronic systems with cyber-attack considerations in modern power grids, and for his leadership in hardware-in-the-loop testing and standards development, including service on the IEEE P2004 standards working group. In addition to the award, Davari was inducted into the IEEE-Eta Kappa Nu (HKN) honor society. His research program at Georgia Southern has earned significant support, including more than $1.17 million in National Science Foundation funding, a 2024 Gulfstream Aerospace Research Fellowship, inclusion in the Stanford/Elsevier Top 2% Scientists list, and selection as a finalist for the 2024 Curtis W. McGraw Research Award. You can find out more about Davari's research by visiting his Georgia Southern Scholars profile below: To arrange an interview or to learn more about this award - Looking to know more about Georgia — simply contact Georgia Southern's Director of Communications Jennifer Wise at jwise@georgiasouthern.edu to arrange an interview today.
