This week, Florida State University will bring together experts on artificial intelligence and machine learning to explore the role of agentic AI — a type of AI that performs tasks and adapts to change with little human intervention — across industries including medicine, finance, education and more.

The 2026 Artificial Intelligence and Machine Learning Expo, AIMLX26, is set for Friday, Feb. 27, from 8:30 a.m. to 5 p.m. and Saturday, Feb. 28, from 10 a.m. to 2 p.m. at the Challenger Learning Center of Tallahassee, 200 S. Duval Street. The two-day event is presented by the FSU Interdisciplinary Data Science Master’s Degree Program.

On Friday, industry professionals and researchers from FSU’s Department of Computer Science, the FSU School of Information, OpenAI, the Massachusetts Institute of Technology, the University of Florida and Premera Blue Cross will present on topics ranging from the engineering of AI systems to their applications.

“The theme of this year’s event is agentic AI with a focus on how intelligent, autonomous and collaborative AI systems are reshaping research, industry and society,” said Zhe He, director of the Institute for Successful Longevity at FSU and a professor in the School of Information. “The program will explore topics such as multi-agent systems, large language model–based agents, decentralized and agentic web architectures, AI for scientific discovery, and real-world deployments in domains like health care, finance and enterprise systems.”

He, who is also affiliated with the Department of Computer Science, Department of Statistics, and the Department of Behavioral Sciences and Social Medicine in the College of Medicine, will present the lecture “Developing a Multi-Agent AI System for Explaining Lab Results to Older Adults.” This work is supported by a recent grant from the National Institute on Aging’s Artificial Intelligence and Technology Collaboratories for Aging Research and aims to help older Americans better understand how to use AI and other emerging technologies to better manage and act upon their health data.

He’s presentation will include his team’s work on LabGenie, a patient-and-caregiver facing application that is designed to improve health outcomes for consumers.

“The system is designed to translate complex laboratory data into patient-friendly, actionable insights that support better engagement, shared decision making, and improved health literacy and outcomes,” He said.

This year’s keynote speaker, Sherwin Wu, is a member of technical staff at OpenAI and leads engineering for the OpenAI Platform. His keynote address on Friday, “Slowly, and Then All At Once: A survey of AI agents over the last three years and a glimpse into the next three years,” will discuss industry trends since ChatGPT’s launch in 2022 and the current and future landscape of AI capabilities.

On Saturday, the Challenger Learning Center will host the local K-12 community for additional FSU faculty lectures as well as a series of interactive activities — the first event of its kind in AIMLX series history. Activities include learning about robotics, color coding magnets, basic programming, car challenges, binary number bracelet crafts and more that allow learners of all ages to participate.

“We’re highlighting the connection between what goes on at FSU on the scientific level and day-to-day applications of AI tools,” said Gordon Erlebacher, IDS program director and a professor in the Department of Scientific Computing, who will present Saturday on the rapid evolution of AI tools and their impact on daily life. “AI tools have so many uses that students should learn about, and the community day allows participants to directly ask FSU faculty questions about AI while providing a point of contact for the future. We hope that hearing from local experts who use these tools will make AI approachable and relatable.”

For a full schedule of presentations, events, topics, presenter details and more, visit the FSU Data Science event website.

AIMLX26 is sponsored by Florida State University, the FSU College of Arts and Sciences, the FSU College of Communication and Information, the FSU School of Information, the FSU Department of Computer Science, the FSU Department of Modern Languages and Linguistics, the FSU Department of Scientific Computing, the FSU Department of Statistics, the Challenger Learning Center of Tallahassee and Ruvos.

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This week, statisticians from across the globe will gather at Florida State University for a conference examining major advancements and challenges in the field, including the impacts of big data and artificial intelligence on statistical research.

Florida State University’s Department of Statistics, in partnership with the International Indian Statistical Association, will host more than 110 scholars at the “Theory and Foundations of Statistics in the Era of Big Data Conference” April 19-21 in the FSU Student Union Ballrooms.

“There has been real transformative progress within the field of statistics recently, propelled by amazing growth in computational power as well as rapid advancement in procuring and curating massive data on diverse fields including public health, medicine and national and economic security,” said Debajyoti Sinha, the Ronald and Carolyn Hobbs endowed chair of statistics and one of the conference organizers. “There’s also been a remarkable amount of progress in developing the necessary analysis tools, how to apply them, and in computational aspects of statistics for such data.”

Despite the surge in availability of novel tools for the analysis of “big data,” the theoretical foundations, scientific rigor and logical justifications that underpin these tools are not yet mature. The event brings together statistics and data science innovators and senior leaders with emerging young researchers to identify, discuss and decipher solutions to these foundational issues and challenges faced by today’s statisticians.

The conference — supported by the American Statistical Association, Institute of Mathematical Statistics and the National Institute of Statistical Science and funded by the National Science Foundation and the National Security Agency — also includes a centenary celebration honoring the foundational and pioneering contributions of legendary statisticians Raghu Raj Bahadur and Debabrata Basu, who was also a long-time FSU faculty member.

Participants traveling from universities across the U.S. and from as far as Europe, Canada, India, Nepal and China will experience a program featuring three plenary talks and six invited sessions showcasing senior leaders in the field who have made foundational contributions to statistics, two special invited sessions for early-career researchers, a poster session for graduate students and junior faculty and a banquet talk by a statistical leader.

Plenary speakers include T. Tony Cai, president-elect of the Institute of Mathematical Statistics and the Daniel H. Silberberg Professor of Statistics and vice dean at the University of Pennsylvania’s Wharton School; Xiao-Li Meng, the Whipple V. N. Jones Professor of Statistics at Harvard University, former dean of the Harvard Graduate School of Arts and Sciences and founding editor-in-chief of the Harvard Data Science Review; and Merlise A. Clyde, Duke University professor of statistical science and former chair of Duke’s Department of Statistical Science. More than 50 notable statisticians will present their research, 16 of whom are from FSU.

“The main goal of the conference is to motivate the young students and researchers in the field to understand the problems in the field and be inspired to go on to contribute to future solutions,” Sinha said. “We want students, graduate students and researchers to be educated on issues and skills they need to have a real impact on their areas of interest. The FSU Department of Statistics is among the oldest statistics departments in the country. We have a history of taking a real lead within the statistics field and have made pioneering breakthroughs. We want to continue that legacy of leadership for the next generation of statisticians.”

The conference also features two invited sessions for early-career researchers who are emerging leaders in the field, including junior faculty members from top statistics and data science departments across the nation.

“The conference scientific committee aims to create a platform for up-and-coming statisticians to network and discuss research ideas with senior leaders and among themselves and to chart the future trajectory of contemporary statistical foundations together,” said associate professor of statistics Xin (Henry) Zhang, the conference’s NSF grant principal investigator and scientific committee co-chair. “The FSU Department of Statistics has hosted several NSF-funded conferences in recent years, and thanks to NSF support we are delighted to include more junior researchers and students at this unique and influential scientific event.”

Learn more about the “Theory and Foundations of Statistics in the Era of Big Data Conference,” and view the speaker lineup on the conference website. For more information about FSU’s Department of Statistics, visit stat.fsu.edu.

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A Florida State University researcher has been granted funding from the National Science Foundation to help reduce the amount of time it takes to conduct certain statistical analyses, slashing the interval from days to just minutes. 

Jonathan Bradley, an associate professor in the Department of Statistics, part of the College of Arts and Sciences, will use the $227,000 award to virtually eliminate the need for a computationally demanding tool often used in estimate calculations and replace it with models that merge two commonly used methodologies in the field. 

Bradley’s new methodology is applicable in problem areas across many disciplines that require fast estimates for large datasets, such as those concerning COVID-19 disease mapping, poverty monitoring and predicting wildfire spread. 

“I feel a lot of gratitude for receiving this award,” Bradley said. “The research from this grant is particularly important for my long-term research goals, so to receive this support is extremely exciting. Much of this funding will also go towards the research of the doctoral students I direct, which is beneficial for the entire statistics department.”  

Bradley’s current project details how to use conjugate models, mathematical forms that can represent prior information, to simplify steps within a Markov chain Monte Carlo computation, or MCMC, which typically takes hours or days to implement when using massive quantities of data.  

“Generally, a Bayesian method allows scientists to improve estimates using what is already known about a problem,” Bradley said. “Bayesian methods combine information from a new dataset with previous knowledge about the data in a mathematical way. Spatio-temporal data are observations that are recorded at a particular time and location, and one can use the fact that nearby observations tend to be similar to improve analyses. Both methods can be combined to produce precise statistical estimates.”  

Bradley’s theory doesn’t require MCMC at all for many Bayesian spatio-temporal models frequently used in estimating public health variables or environmental mitigation efforts. Avoiding MCMC in statistical modeling is an opportunity for statisticians and scientists working with huge swaths of observational information to produce almost immediate, precise estimates in today’s world of high-volume, high-speed data.  

“The research from this grant is particularly important for my long-term research goals, so to receive this support is extremely exciting. Much of this funding will also go towards the research of the doctoral students I direct, which is beneficial for the entire statistics department.”

— Associate Professor Jonathan Bradley

This work aims to speed results in areas for which there is demand for real-time updates and projections, such as wildfire forecasting and disease spread, among others. 

“Combining these methodologies can be extremely difficult,” Bradley said. “The information fed into spatio-temporal analyses can be complex, as the sheer amount of data from meteorology, atmospheric sciences and other fields often leads to lengthy complications within this statistical calculation. These difficulties have motivated a large community of researchers around the world to work on these issues so we can leverage prior knowledge and space-time correlations to improve real-time estimates quickly.” 

Through this NSF grant, Bradley and a team of graduate students will investigate faster computational methods in collaboration with other researchers across FSU and beyond. The team will also develop software to promote the use of Bradley’s model.  

Department of Statistics chair Eric Chicken said this new methodology is the leading edge of modern statistics, with exciting potential in government and environmental science applications. 

“Jon is a dedicated instructor and mentor to our graduate students and a valued faculty member to the day-to-day running of our department,” Chicken said. “His original and well-cited research has consistently met NSF’s high threshold for intellectual merit.”  

Bradley earned a bachelor’s degree from Rochester Institute of Technology in 2008 and earned master’s and doctoral degrees at Ohio State University in 2010 and 2013. Before joining FSU’s faculty in 2016, he worked as a postdoctoral researcher at the University of Missouri. 

Bradley has co-authored more than 40 publications in the field of statistics, and he serves as an associate editor for Biometrics and the Journal of Agricultural, Biological and Environmental Statistics.  

To learn more about Bradley’s work and the Department of Statistics, visit stat.fsu.edu. 

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A Florida State University faculty member has earned one of the most prestigious awards in statistics.

Elizabeth Slate, a distinguished research professor in the Department of Statistics in the College of Arts and Sciences, has been selected as a 2023 Institute of Mathematical Statistics Fellow alongside 26 other statisticians worldwide who have demonstrated leadership and research excellence.

“I’m thrilled to be named an IMS Fellow, as this is a distinction I’ve long admired in my field,” Slate said. “I collaborate with researchers to design studies and analyze data to address important questions in a wide variety of areas, including oral health, cancer, psychology, epidemiology and behavioral science, so to have this recognition for my research and leadership contributions is immensely gratifying.”

Each year, IMS Fellows are selected by a peer committee based on their unique or pioneering contributions to the field of statistics. Slate’s election recognizes her substantial contributions to the theory of reparameterization, a mechanism for designing effective statistical models, and for her research on oral health and the link between selenium and cancer.

Founded in 1935, IMS is an international professional and scholarly society that fosters development and dissemination of the theory and applications of statistics and probability. IMS has 4,200 active global members, and about 10 percent of the current IMS membership have earned the Fellows status.

Xufeng Niu, Department of Statistics chair and professor, said Slate is a longstanding, active leader at the departmental, national and international levels.

“Dr. Slate has had an immense impact on the Department of Statistics, on FSU and the larger academic community,” Niu said. “We are so proud of her for being named an IMS Fellow this year, as both the department and FSU benefit from her research efforts, her excellent teaching and her ability to bring together researchers from many fields of study.”

Slate earned a doctorate in statistics from Carnegie Mellon University in 1991 before joining the faculty at Cornell University from 1992 to 2000. She served as a professor at the Medical University of South Carolina for over a decade before coming to FSU in 2011. In addition to this IMS Fellowship, Slate is a Fellow of the American Statistical Association and an elected member of the International Statistics Institute. In 2022, she received the Paul Minton Award from the Southern Regional Council on Statistics.

Slate’s most recent work is in longitudinal data analysis, Bayesian modeling and recurrent events, all with applications in oral health research, disease biomarkers and other medical research areas. Her work has been published in numerous statistics and medical journals, including Cancer Epidemiology Biomarkers & Prevention and the Journal of the American Statistical Association, and she has received funding from the National Science Foundation, National Institutes of Health and Department of Defense, among other institutions.

“Because my work is in biostatistics, the cross-disciplinary engagement of this field is always exciting and naturally poses challenging statistical issues,” Slate said. “Real data can have complex structures or unexplained differences that require specialized statistical methods, so I enjoy using my expertise to strengthen the statistical rigor of my team’s findings.”

Statistics can be highly collaborative — new findings in statistical methods can lead to new insights in biology, psychology, medicine and other fields. Conversely, research in those fields often requires new approaches in statistics. Slate’s career and selection as an IMS fellow serves as a testament to the necessity of this cross-disciplinary research in STEM fields, especially when related to complex statistical modeling.

“I am grateful to so many colleagues, students, and collaborators who have inspired me over the years, as well as my mentors from many institutions — all of whom encouraged and stimulated my work,” Slate said. “I’m also thankful for the leadership of IMS for their direction in the profession and the opportunities I’ve had to meet influential colleagues from around the world.”

For more information about statistics and biostatistics research at FSU, visit stat.fsu.edu.

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Machine learning and artificial intelligence have grabbed the spotlight with their potential to change the way we interact. Florida State University presents the 2023 Machine Learning Expo (MLX23) to explore the latest applications of machine learning and AI by FSU researchers.

The expo will be held from 9 a.m. to 5 p.m. Saturday, April 22, at the Jim Moran Building in downtown Tallahassee and is presented by the FSU Interdisciplinary Data Science Master’s Degree Program (IDS).

“We invite participants of this expo to open their minds to the possibilities these new tools offer, which are sprouting all around them,” said Gordon Erlebacher, FSU IDS program director and professor of scientific computing. “There’s an opportunity for Florida to become a leader in using advanced AI tools. This expo is an efficient way for the FSU community to become familiar with the tools, their use and the ethical considerations they raise.”

AI’s groundbreaking technology focuses on building systems that learn and improve from history and experience rather than explicit programming and is profoundly impacting many segments of business and industry including research activity.

MLX23 examines the newest machine learning and AI trends through presentations by FSU faculty, researchers, staff and students that illuminate how these tools are already being applied to solve complex problems. Each presentation will be accompanied by an objective analysis to compare the problem before and after machine learning integration, and hosted panel discussions will cover AI education, usage and ethics.

“Our lives are being transformed by AI,” said Zhe He, associate professor and co-chair of the information technology master’s program in the FSU School of Information. “Almost everyone is impacted by AI to a certain degree.”

This year’s presenters include researchers who contribute to the analysis of machine learning and AI from varied research perspectives including art, linguistics, physics, computer science, civil engineering, data administration and cyber security.

Peter Stone of the University of Texas Artificial Intelligence Laboratory and Sony AI America and founder and director of the Learning Agents Research Group, part of UT Austin’s Department of Computer Science Artificial Intelligence Laboratory, will deliver a keynote address.

“Machine learning, especially the generative kind, has made much progress in both language and images,” Erlebacher said. “More people have used AI chatbot ChatGPT since it launched in November 2022 than any other app or product in history. There are so many ways to use these new technologies, and we are excited to share them with attendees.”

Concerns are commonly articulated about the potential for AI software to be abused, not least by the scholars most invested in the technology’s development. The workshop will respond to these concerns and foster discussion on the importance of responsible use.

“It’s critical that we share our experiences using AI in research, education and our daily activities,” Zhe He said. “I hope attendees will also become aware of the unintended consequences of AI in our society.”

MLX23 is sponsored by FSU’s College of Arts and Sciences, College of Communication and Information, School of Information, Department of Computer Science, Department of Scientific Computing, Department of Mathematics, Department of Statistics and Jim Moran College of Entrepreneurship.

For the full schedule of presentations, topics, details on the presenters and more, visit datascience.fsu.edu/mlx.

About the FSU Interdisciplinary Data Science Master’s Degree Program:

Students in this professional degree program study the latest in machine learning, artificial intelligence, computer science, mathematics and statistics as they prepare for wide-ranging careers, from cybersecurity to the sciences and health care, from finance and economics to the humanities and more.

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