Sam Noble Museum
2401 Chautauqua Ave
Norman, OK 73072
It is with great pleasure that we invite you to the upcoming inaugural symposium, titled "Innovating for Impact: DISC Inaugural Data Science Symposium". This full-day event will be packed with learning, inspiration, and networking opportunities. The symposium will feature keynote speakers, breakout sessions, poster presentations on a variety of topics, and vendor booths.
Attendance at the symposium is FREE. However, registration is required to ensure smooth coordination. We look forward to welcoming you to this event!
Please click the accordians for more information.
| 8:30 am - 10:00 am | Event Registration /Continental Breakfast / Poster Presentations / Vendor Tables |
|---|---|
| 10:00 am - 11:00 am | Opening Remarks & Keynote Speaker |
| 11:00 am - 11:45 am | Panel Speaker Discussions (2 sessions simultaneously) |
| 11:45 am - 12:00 pm | Break |
| 12:00 pm - 1:00 pm | Lunch Provided, Poster Presentations, Vendor Tables |
| 1:00 pm - 1:45 pm | Panel Speaker Discussions (2 sessions simultaneously) |
| 1:45 pm - 2:00 pm | Break |
| 2:00 pm - 3:00 pm | Keynote Panel "The Future of AI at OU" |
| 3:00 pm - 3:30 pm | Poster Session Winners Announced |
| 3:30 pm - 4:00 pm | Networking |
Sam Noble Museum
2401 Chautauqua Ave
Norman, OK 73072
Due to an overwhelming response, we have recieved the maximum number of registrations.
Posters can be presented on any topic. Students from all Undergraduate and Graduate Colleges and Departments are invited to present.
Poster registration is separate from Event Registration, participants must register for both to present a poster.
Poster Participants are required to attend a short virtual poster information session:
Tuesday 3/4/2025 @ 9am: Click to Join Zoom
Thursday 3/13/2025 @ 3 pm: Click to Join Zoom
Prizes will be announced at 3:00 pm
1st place - $2000 scholarship
2nd place - $1000 scholarship
3rd place - $500 scholarship.
Guidelines for Posters
Design Guidelines:
Venue Information
Posters will be displayed in the Pleistocene Plaza. Easels will be provided.
Please have someone from the presentation team available beginning at 8:15 am and available throughout the day during breaks. Presenters do not have to be available during speaker sessions.
Presentation
Poster Presenters must be at their station during the evaluation times (8:30 am – 10 am and 12 pm – 1 pm) to interact with guests and present their posters to the judges.
Each presentation will be evaluated between 8:30 am – 10 am or 12 pm – 1 pm.
Presentations should be no longer than 5 minutes in length, including Q&As.
Grading Rubric: Poster Competition - Evaluation Rubric.pdf
Session | Speaker Name | Talk Title | Abstract |
|---|---|---|---|
| Opening Remarks | David Ebert | n/a | n/a |
| Keynote Speaker 10 am - 11 am | Polo Chau | "Human-Centered AI: Safe, Interpretable, Trustworthy Analytics" | Tremendous growth in artificial intelligence (AI) research has shown that AI is vulnerable to adversarial attacks, and its predictions can be difficult to understand, evaluate, and ultimately act upon.
Our Safe AI research addresses AI vulnerabilities and develops countermeasures to fortify AI deployment in safety-critical settings. ShapeShifter, the world's first targeted physical attack, fools the Faster R-CNN object detector. LLM Self Defense presents a straightforward, practical method for detecting harmful outputs through self-examination. Our safety landscape visualization reveals the novel "safety basin" phenomenon observed universally in LLMs, shedding light on the critical role of system prompts in protecting LLMs from misuse.
Our complementary interpretable AI research creates a suite of interactive visualizations that amplify people's ability to understand complex models and vulnerabilities. WizMap allows scalable on-device exploration of large AI embeddings, while LLM Attributor introduces a new way to quickly attribute an LLM's text generation to specific training data points, aiding in the inspection of model behaviors. Summit, NeuroCartography, and Bluff offer scalable summaries and visualizations of deep learning model features, interactions, and potential attack vectors.
Our trustworthy AI research empowers users to steer models in alignment with human knowledge and values. GAM Changer empowers domain users to edit ML models to reflect human knowledge. Our suite of AI Explainers (Transformer Explainer, Diffusion Explainer, CNN Explainer, GAN Lab) offer accessible tools for both students and experts to learn about AI models. |
| Keynote Panel 2 pm - 3pm | David Ebert | "The Future of AI at OU" | n/a |
| Nishanth Rodrigues | |||
| Amy McGovern | |||
| Hunter Heyck |
David Ebert, PhD
Associate Vice President for Research and Partnerships
Director, Data Institute for Societal Challenges (DISC)
Gallogly Chair in Engineering
Professor, ECE and Computer Science
BIO
Amy McGovern
Lloyd G. and Joyce Austin Presidential Professor, School of Meteorology and School of Computer Science
Director, NSF AI2ES
University of Oklahoma
Hunter Heyck
Professor, History of Science, Technology, and Medicine
Director, Center for Creativity and Authenticity in AI Cultural Production
University of Oklahoma
Session | Speaker Name | Talk Title | Abstract |
|---|---|---|---|
Morning Auditorium | Bob Palmer | The Advanced Radar Research Center (ARRC) at the University of Oklahoma – Bridging the Gap Between Engineering and Science | The Advanced Radar Research Center (ARRC) at the University of Oklahoma is leading the development of next-generation weather radar technology through the fully digital phased array radar system, Horus. This presentation provides an overview of ARRC’s history, capabilities, and its role in advancing weather and defense radar systems. Horus represents a paradigm shift in radar meteorology, leveraging cutting-edge digital beamforming, high-resolution polarimetric observations, and rapid scanning capabilities. Designed for scalability and real-time operation, Horus has already demonstrated high-quality weather measurements, including 3D hail core observations and multiple simultaneous transmit/receive beam applications. This technology promises to revolutionize atmospheric sensing, enabling more precise and rapid weather forecasting while supporting multi-mission capabilities, including aviation and defense applications. The future of weather radar observations is now being shaped by fully digital phased array technology, offering unprecedented flexibility and performance. |
Morning Auditorium | Chenghao Wang | A Comprehensive Historical Hourly Weather Database for U.S. Urban Energy System Modeling | Reliable and continuous meteorological data are crucial for modeling urban energy systems and their components under various weather and climate conditions. However, existing long-term datasets often suffer from spatial and temporal gaps and inconsistencies. We developed CHUWD-H v1.0, a 23-year gap-free and quality-controlled hourly weather dataset covering 550 locations across all urban areas in the contiguous United States. It synthesizes hourly weather observations from stations with outputs from a physics-based solar radiation model and reanalysis data through a multi-step gap filling approach. Designed primarily for urban energy system modeling, it can also support historical urban meteorological and climate studies. |
Morning Auditorium | Carrie Schroeder | Leveraging Small Data for Big Impacts | One of the challenges of our era of “big data,” especially with respect to language data, is the resource gap. Dominant, well-resourced languages such as English benefit from more extensive tool development, and much more data-driven research can be conducted on the language and documents – contemporary or historical – in those languages. Low-resourced languages, on the other hand, do not have large digital corpora and NLP tools. The ability to study, translate, analyze low-resourced languages and their historical documents is diminished compared to the well-resourced. And the research, tools, etc., built for well-resourced languages exacerbate that gap. This paper will use the example of one of the ancient languages (Coptic) to explore how a small team can move a language out of the low-resource status and have a comparatively big research impact despite working with a small dataset. |
Morning Plaza | Hank Jenkins- Smith & Joseph Ripberger | Data Analytics for Public Policy Research | This talk explores how OU’s Institute for Public Policy Research and Analysis (IPPRA) leverages data to inform public policy. We use survey research data (national, state, and subgroup samples), social media data (public sentiment and trends), and administrative data (HR, cost, and performance metrics). To enhance accessibility and impact, we develop web apps and interactive dashboards that allow users to visualize and apply our findings. By integrating diverse data sources with practical tools, IPPRA advances both academic research and real-world policy solutions. |
Morning Plaza | David Bard & William Beasley | Coming Soon | Coming Soon |
Morning Plaza | Yutian Thompson | Evaluating Data Quality in Child Maltreatment Administrative Records: Insights from the National Children's Alliance Database | This study evaluates the quality of child maltreatment administrative data from the National Children’s Alliance database (NCAtrak), which includes records from 393 Children’s Advocacy Centers (CACs) across 45 U.S. states, covering over 1.2 million child maltreatment cases. Findings indicate moderate to good overall data quality, with significant variations across CACs. Geographic location was associated with these variations. The results highlight the need for further investigation into underlying factors affecting data quality, which is essential for developing solutions to improve data integrity within child welfare systems. |
Afternoon Classroom | Erin Maher | Data Science for Social Science: The Promise and Potential for Solving Social Problems | Dr. Maher will provide examples of the application of data science in the social sciences to address social problems in concrete ways. She will discuss new advances, as well as cautions and concerns. She will highlight the promise of transdisciplinary teams employing data science techniques in innovative and ethical ways for the betterment of society. |
Afternoon Classroom | Chongle Pan | Enhancing Shared Decision-Making for Lung Cancer Screening with a Trustworthy AI Chatbot | Lung cancer screening (LCS) uptake remains low, highlighting the need for interventions that enhance accessibility, patient education, and shared decision-making. We developed an AI-driven chatbot integrating smoking cessation support with LCS consultations. A pilot study (N=29) demonstrated its effectiveness in assessing smoking-related risks and improving cessation readiness. Additionally, we are collaborating with clinical experts to standardize LCS eligibility assessment. Future work includes expert evaluations and model optimization to enhance chatbot accuracy, engagement, and its potential to reduce health disparities. |
Afternoon Auditorium | Angela Person & Christopher Black | From Data to Design: Enhancing Museum Experiences with Biosensors | Traditional museum evaluation methods often fail to capture real-time emotional and physiological visitor responses. This study integrates biosensor technology, visitor studies, and architectural analysis to assess engagement in emotionally charged exhibits. Using Empatica E4 wristbands, researchers mapped electrodermal activity (EDA) across museum spaces, revealing heightened arousal in specific exhibits. Findings suggest strategic exhibition design adjustments can be made to enhance visitor experience. This research highlights the potential of biosensory data in museum studies, offering a scalable methodology for improving engagement in heritage spaces. Results are forthcoming in the International Handbook of Heritage and Affect (Routledge). |
Afternoon Auditorium | Qinggong Tang | A Pre-Transplantation Donor Liver Evaluation System (LIVES) | Liver transplantation for severe hepatic diseases faces a critical shortage of donor livers globally. Utilizing marginal donor livers could alleviate this issue, yet current biopsy-based assessments are limited in evaluating their viability comprehensively. We propose employing polarization-sensitive optical coherence tomography (PS-OCT) to noninvasively scan multiple regions of donor livers, providing detailed microstructural and tissue property evaluations. Our approach integrates texture feature extraction and machine learning to correlate PS-OCT findings with pathological assessments, demonstrating its potential to enhance pre-transplantation viability evaluations for liver. PS-OCT can serve as a promising tool for transplant clinics, offering precise, noninvasive insights into liver tissue quality across the entire donor liver. |
Robert D. Palmer
Executive Director, Advanced Radar Research Center (ARRC)
Associate Vice President for Research & Partnerships
Interim Director, National Weather Center
Professor & Tommy C. Craighead Chair, School of Meteorology
University of Oklahoma
Caroline T. Schroeder
Professor, Women's and Gender Studies
Core Faculty, Data Scholarship Program in the Dodge Family College of Arts & Sciences
Affiliate Faculty, History and Religious Studies Departments
Faculty Fellow, Data Institute for Societal Challenges
Hank Jenkins-Smith
George Lynn Cross Research Professor, Public Policy
Director, OU Institute for Public Policy Research and Analysis
Joe Ripberger
Associate Professor, Political Science
Deputy Director, OU Institute for Public Policy and Analysis
Qinggong Tang
Associate Professor of Stephenson School of Biomedical Engineering
Endowed Stephenson Professor
Associate Member – Stephenson Cancer Center
Erin Maher
Professor, Department of Sociology
Senior Associate Director, Data Institute for Societal Challenges (DISC)
Adjunct Associate Professor, Department of Pediatrics and College of Medicine, OU Health Sciences Center
Affiliate Faculty, Department of Women’s and Gender Studies
Angela Person
Associate Dean for Research and External Engagement, Gibbs College of Architecture
Associate Professor, Architecture
Christopher Black
Interim Department Chair, Department of Health and Exercise Science
Associate Professor
University of Oklahoma
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