Repost: Announcing the 2025 AI Symposium!

Mon, 25 Aug 2025 12:37:12 -0400
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On the heels of the successful “AI, Privacy, and Ethics Symposium” of April 2024, we’re back with a new iteration! Please join us for this fall’s AI Symposium, titled “Exploring the Gadgets & Gizmos in Your AI Toolkit.” This fall’s series will highlight various topics ranging from Google Gemini and its integration into UMBC platforms, to the broader legal implications of using generative AI, and much more! This free symposium will be held virtually at noon via Webex on Wednesdays beginning October 1st through November 12th.

Below you will find the individual links for each discussion:

Wednesday, October 1st @ 12pm EST:

Dr. Mariann Hawken (Director of Instructional Technology, UMBC)

Google Gemini: AI Tools for Research, Teaching, & Learning

Wednesday, October 8th @ 12pm EST:

Brianna Hughes (STEM Reference & Instruction Librarian, UMBC)

Assembling an AI Toolbox: Access-Oriented Approaches to Scholarship and Instruction

Wednesday, October 15th @ 12pm EST:

Nina-Simone Edwards, JD (Senior Institute Associate at the Institute for Technology Law & Policy)

Beyond the Hype: Embedding Ethics in AI Policy for Libraries and Higher Ed

Wednesday, October 22nd @ 12pm EST:

Jennifer Posada, (PhD student, Human-Centered Computing, UMBC)

Making Sense of Data with AI: Lowering Barriers, Expanding Who Participates

Wednesday, October 29th @ 12pm EST:

Dr. Manas Gaur (Assistant Professor, Department of Computer Science & Electrical Engineering, UMBC)

Yash Saxena (PhD student, Computer Science, UMBC)

Building Trustworthy LLM Agents for Academia through Structured, Interpretable Knowledge Retrieval and Source Attribution

Wednesday, November 5th @ 12pm EST:

Dr. Roberto Yus (Assistant Professor, Department of Computer Science & Electrical Engineering, UMBC)

The Privacy Paradox of GenAI: What It Knows, Why It Matters, and How We Fight Back

Wednesday, November 12th @ 12pm EST:

Dr. Eric Stokan (Associate Professor, Department of Political Science & Director of CS3, UMBC)

Advanced Opportunities with AI and Large Language Models (LLMs): Examples from the Social Sciences

Our symposium was made possible thanks to the following sponsors:

UMBC’s Division of Information Technology (DoIT), The Center for Social Science Scholarship, the Department of Computer Science & Electrical Engineering, the Department of Information Systems, and The Hackerman Foundation.