Online Student Conference
The College of Information, Data and Society Online Student Conference seeks to connect
students across the college and promote student work. The conference allows students
to share their school or professional work, helps them communicate and connect and
fosters a stronger sense of community among students in the college. The Online Student Conference is organized annually by the College of IDS RSCA Advisory Committee in collaboration with student organizers.
2025 Student Conference: March 4-6, 2025
This dynamic event, taking place March 4-6, 2025, is now accepting submissions. Students (graduate and undergraduate) from both the and the Department of Applied Data Science are invited to submit research projects and professional work that highlights innovative ideas, problem-solving and collaboration. Students graduating in December 2024 may also submit and participate in the 2024 Student Conference.
View the Call for Submissions [pdf]
Why Should You Participate?
Since 2022, the College of IDS Online Student Conference has been a unique platform for students to:
- Develop Presentation Skills: Gain valuable experience presenting your work professionally.
- Connect with Peers: Engage in meaningful dialogue with students from different disciplines within the college.
- Earn Recognition: All presenters will receive prizes for their participation!
Conference presenters will prepare short, recorded video presentations of their research or professional projects. These videos will be available for attendees to view throughout the conference, fostering a rich learning and interactive environment.
Abstract submissions are due Friday, December 20, 2024.
Past Student Conferences
2024 Online Student Conference Keynotes
by Dr. Bharat Mehra (Opening Keynote)
Recorded February 2024
Description: Dr. Bharat Mehra will discuss social justice and action research intersections across
his recent work in the field of information (including library and information science)
to generate community-wide positive impacts. In the process, he provides a critical
positionality to his βvoiceβ toward strategic actions that can dismantle white entrenched
systemic hegemonies in research, teaching, service and practice.
About the Presenter: Dr. Mehra is EBSCO Endowed Chair in Social Justice and Professor in the School of Library and Information Studies at the University of Alabama. His research focuses on diversity and social justice in library and information science (LIS) and community informatics or use of information and communication technologies to empower minority and underserved populations to make meaningful changes in their everyday lives. Dr. Mehra primarily teaches courses on social justice and inclusion advocacy, diversity and inclusive leadership in information organizations, community-engaged scholarship, outreach to diverse populations, public library management, collection management and grant development for information professionals.
by Krishna Gadiraju, MSEE (Closing Keynote)
Recorded February 2024
Description: In the dynamic realm where Artificial Intelligence (AI) intersects with healthcare,
a profound transformation unfolds, unveiling unparalleled possibilities and advancements.
The fusion of advanced AI technologies with healthcare practices holds the promise
to not only reshape the landscape of medical research, diagnosis, treatment and patient
care but also to set new standards for enhanced healthcare outcomes. This talk delves
into the need for integrating Advanced AI applications in healthcare, recognizing
the escalating complexity and challenges faced by the industry. It introduces a proactive
solution rooted in graph theory to identify infectious hotspots in urban healthcare
environments, constructing a patient-specific graph that adeptly captures intricate
inter-dependencies and health dynamics for effective outbreak management. The subsequent
discussion seamlessly aligns with the critical demand for advanced AI in healthcare,
focusing on optimizing Large Language Models (LLMs). By employing graph theory and
clique-finding methods to craft a prompt-specific graph, this approach aims to refine
the capabilities of LLMs, enhancing their understanding of context, semantics and
domain-specific intricacies. This initiative directly contributes to the augmentation
of AI tools tailored for healthcare applications. Together, these initiatives underscore
the transformative potential of Advanced AI applications in healthcare. The integration
of diverse patient data and the optimization of LLMs represent a strategic response
to the multifaceted challenges faced by the healthcare industry. This talk endeavors
to showcase these pioneering initiatives, emphasizing a unified approach that provides
a tangible blueprint for the seamless integration of cutting-edge AI tools into healthcare
practices.
About the Presenter: Gadiraju received his Bachelor of Science degree in Electrical and Electronics Engineering (B. Tech EEE) from JNTU Kakinada in May 2013. He then received his Post Graduate Diploma Degree from NPTI-PSTI-Bangalore, and worked as a Jr. Electrical Engineer in Elpro International Ltd. in Pune, India. He then joined Louisiana State University to pursue his masterβs degree in Electrical Engineering in the spring semester of 2016. He received his degree of Master of Science in Electrical Engineering (MSEE) in Fall 2018. He is currently a doctoral candidate in electrical and computer engineering.
Outstanding Student Presentation Winners
- by Samantha Warriner
- by Marcus Ortiz
- by Hope Peters
- by Rebecca Joy Clower
