Dr. José Antonio Bowen will visit UMBC on Thursday, January 23, to lead two in-person workshops for UMBC faculty and staff based on his book Teaching with AI, co-authored with C. Edward Watson, JHU Press, 2024.

Get more information on the workshops and register in the links below to ensure seating, workshop materials, and lunch or coffee and snacks.

Registration closes on Thursday, January 16.

• AI Literacy & Prompt Engineering, (with lunch): 12:00-1:45pm;  REGISTER HERE
• AI Assignments & Assessments (coffee & snacks): 2:00-3:15pm. - REGISTER HERE

Advancing machine learning methodology for applications in gerontology

Dr. Jaime Lynn Speiser, Wake Forest University School of Medicine

11-12pm EST Mon, Dec. 11, 2024 U. of Maryland, Baltimore & online

Prediction models aim to help medical providers, individuals, and caretakers make informed, data-driven decisions about the risk of developing poor health outcomes, such as fall injury or mobility limitation in older adults. Most models for outcomes in older adults use cross-sectional data, although leveraging repeated measurements of predictors and outcomes over time may result in higher prediction accuracy. This seminar talk will focus on a novel methodology for longitudinal, repeated measures prediction models called Binary Mixed Model(BiMM) forest. I will give an overview of longitudinal data analysis and introduce the BiMM forest method with variable selection. I will then apply a BiMM forest for predicting mobility limitation in older adults using the Health, Aging, and Body Composition dataset.

Dr. Speiser received her B.S. in mathematics at Elon University and M.S. in statistics at the Ohio State University. She completed her Ph.D. in biostatistics at the Medical University of South Carolina, where she was awarded the Distinguished Graduate Student Award at the top of her class. Dr. Speiser received the Lester R Curtin Award from the American Statistical Association and several conference travel awards. She serves on the executive committees of the American Statistical Association’s Statistical Learning and Data Science Section and Statistics and Data Science in Aging Interest Group. Dr. Speiser is currently funded by an NIH K25 award and is the Leadership Fellow for Wake Forest’s Pepper Center and Clinical and Translational Research Institute. Her paper comparing random forest variable selection methods is a top-cited paper in the journal Expert Systems with Applications with over 1000 citations.

Register here to get a Zoom link. 

Real-Life Challenges and Opportunities in AI and Health

Catherine Ordun, VP at Booz Allen Hamilton

12-1 pm Mon. Nov. 25, 2024 in ITE 406 & online

Lunch provided for those attending in-person, please RSVP with this form. Additional Q&A session 1-2pm in ITE 406.

In academic research, we often find ourselves constrained to focus on algorithms and training data to develop novel architectures and frameworks. However, in real-life applications for customers, there are significantly more challenges that we should consider. When it comes to AI and Health in the Federal Government, it goes beyond algorithms and toward understanding the limitations of data and the complexities of AI integration into different platforms and systems. In this talk, Catherine Ordun will provide an overview of insights from her work leading AI development at Booz Allen Hamilton. We will walk through different real-life vignettes to help illustrate how to evaluate varying levels of complexity in AI development, from algorithms to deployment.

Dr. Catherine Ordun received her Ph.D in Information Systems from the University of Maryland, Baltimore County, with her dissertation on Multimodal Deep Generative Models for Cross Spectral Image Analysis. She has published papers at top AI conferences including NeurIPS, ICML, AAAI, MICAII, KDD, and a variety of IEEE conferences in image processing and biometrics. She is a Vice President at Booz Allen Hamilton, leading the AI Rapid Prototyping team, having led client delivery in the firm for thirteen years across health, defense, and intelligence accounts for data science, natural language processing, computer vision, and now, multimodal/multitask systems. Before Booz Allen, she worked in the U.S. Intelligence Community. She has a B.S. in Applied Biology from Georgia Tech, a Masters in Public Health from Emory University, and an MBA from George Washington University.

Enhancing Computational Thinking Skills while Addressing ChatGPT Challenges in Introductory Programming Courses

12-1pm EST, Wednesday, Nov. 20, in ITE 459 and online

Effective practices for teaching computing majors to become proficient programmers have been a key research focus for some time. Programming is a fundamental skill that computing students must develop, yet research shows that a notable percentage of students encounter difficulties or become discouraged, sometimes deterring them from the field altogether. The rise of AI tools has introduced new challenges for educators striving to equip students with the essential skills needed for professional practice. In computing, AI and its vast potential are actively studied, yet generative AI tools like ChatGPT—which are open-source and widely accessible—present unique hurdles. These tools, while valuable, may impede students’ ability to develop core computational skills, especially when emphasis is placed on programming pedagogy. This talk will explore these challenges in depth, addressing strategies and practices to mitigate the influence of ChatGPT in early programming courses. Additionally, it will highlight ongoing efforts in IS 147 to examine the impact of these practices on student learning and skill development.

Edward Dillon is an Associate Professor in the Department of Information Systems at UMBC. His research focuses on human-centered computing with emphasis on computer science education and broadening participation in computing. Dr. Dillon has received ~$3.7 million in research funding and awards from external agencies and non-profit organizations, including the National Science Foundation, the Maryland Pre-Service Computer Science Teacher Education Program, and the Collaborative Research Experience for Undergraduates. He also conducted a Faculty in Residency at Google during the summer of 2018 to learn more about this company’s culture, practices, and to understand the expectations for candidates (e.g., aspiring CS majors) who pursue career opportunities at this company and related prominent companies in tech.

CSEE Assistant Professor Rebecca WIlliams was selected to receive a  Learning Analytics Fellowship for the 2024-25 academic year funded by the UMBC Provost’s office. The program supports faculty and staff for research on and development of effective data-informed teaching and learning practices.

Microsoft’s Copilot Studio is a conversational AI platform that lets you create agents using natural language or a graphical interface that are based on the GPT-4 series of large language models. Using Copilot Studio, you can more easily design, test, and publish agents that suit your needs for internal or external scenarios across your university, department, or role. This one-hour webinar is focused on using it for education by faculty, staff, and students: 11-12pm EST, Thursday, November 21, 2024, online. Register here.