iHARP AI Workshop Seminar on the Foundations of Large Language Models
2-4 pm ET Tuesday, April 14 at UMBC and online
iHARP AI Workshop Seminar
Foundations of Large Language Models
2-4 pm ET Tuesday, April 14 at UMBC and online
Dr. Josephine Namayanja and Rhoda Nankabirwa will lead a two-hour workshop seminar on The Foundations of Large Language Models from 2-4 pm ET on Tuesday, April 14, 2026 as part of the UMBC iHARP AI Workshop Series. The seminar will take place on the UMBC campus in Suite 130, at 900 Walker Avenue, and will also be available online via Webex.
Large Language Models have emerged as the foundational technology driving the current AI revolution, fundamentally changing how we interact with computers and process information. These models are being used to automate complex tasks, generate creative content, and solve problems across every discipline and industry, from healthcare and education to finance and entertainment. Understanding their core principles is no longer just for computer scientists; it is essential for anyone looking to navigate and leverage the rapidly evolving digital landscape.
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iHARP AI Workshop Seminar Foundations of Large Language Models 2-4 pm ET Tuesday, April 14 at UMBC and online Dr. Josephine Namayanja and Rhoda Nankabirwa will lead a two-hour workshop...
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UMBC AI
https://dev.my.umbc.edu/groups/umbc-ai
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UMBC AI
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seminar on foundations of LLMS
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Fri, 10 Apr 2026 16:15:40 -0400
Mon, 13 Apr 2026 12:38:27 -0400
Advancing Social Science Research: A Workshop Series on AI, LLMs, and Computational Methods
UMBC's Center for Social Science Scholarship will hold a workshop series this Spring on generative AI, LLMs, and computational social science methods. Sessions will focus on familiarizing faculty and students with deploying AI and LLM models in their research and on developing a deeper understanding of the ethical, equity, and environmental consequences of these models.
February 20 | 12-1:30pm | PUP 438
Social Network Analysis: Building Web-Based Applications for Experiential Learning
Dr. Steve McDonald, Professor of Sociology, NC State University
February 27 | 12-1:30pm | PUP 438
A City in Motion: How Everyday Routines Channel and Control Crime in Baltimore
Dr. Brian Soller, Associate Professor of Sociology (SAPH), UMBC
March 25 | 12-1:30pm | PUP 438
Geospatial Analysis
Krishna Mummadi, CS3 Graduate Assistant & GES Graduate Student
April 14 | 2-4pm | Walker Avenue, Suite 130 (Hybrid)
Foundations of Large Language Models
Dr. Josephine Namayanja, Executive Director, iHARP, UMBC
Rhoda Nankabirwa, iHARP Research Assistant and PhD Student, UMBC
April 22 | 12-1:30pm | Webex
Equity in Algorithms
Dr. Kayla Schwoerer, Assistant Professor of Public Administration, Vrije Universiteit, Amsterdam
April 29 | 12-1:30pm | Webex
Evaluating LLMs for Credible and Rigorous Social Science Research
Dr. Michael Overton, Associate Professor of Political Science and Public Administration, University of Idaho
May 1 | 12-1:30pm | PUP 438
ML Models for Causal Inference Analysis + HPC
Dr. Eric Stokan, CS3 Director and Associate Professor of Political Science, UMBC; Roy Prouty, Assistant Director for Research Computing, DoIT; Ph.D. Candidate, Computer Science, and Sai Vikas Amaraneni, iHARP Research Assistant & Ph.D. Student
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UMBC's Center for Social Science Scholarship will hold a workshop series this Spring on generative AI, LLMs, and computational social science methods. Sessions will focus on familiarizing faculty...
https://socialscience.umbc.edu/computational-social-science-series/
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UMBC AI
https://dev.my.umbc.edu/groups/umbc-ai
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UMBC AI
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seven talks scheduled for Spring 2026 Advancing Social Science Research program
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Mon, 26 Jan 2026 09:04:27 -0500
Talk: Prompt-Engineering and Fine-Tuning in R, 12/12
Prof. Eric Stokan, 12-1:30pm, Fri. Dec 12, Public Policy 438
Professor Eric Stokan, Director of UMBC's Center for Social Science Scholarship, will lead a session on best practices in prompt engineering using ChatGPT to engage in image detection in R through an API. He will demonstrate how going from zero-shot prompting with poor prompting language (e.g., lacking schema, rubric, and clear separation of user from system prompts) to multi-shot prompting (using images and human coding) improves the performance. He wii also describe the prospects of using this for research and some evaluation techniques for estimating the effectiveness of LLMs and LRMs (Large Reasoning Models designed to solve complex problems by "thinking" before they speak).
Lunch will be provided for registered attendees.
Hosted by the Center for Social Science Scholarship and cosponsored by the Division of Information Technology, the Center for Scalable Data and Computational Science, and CGC-SCIPE. CS3-sponsored events are open for full participation by all individuals regardless of race, color, religion, sex, national origin, or any other protected category under applicable federal law, state law, and the University's nondiscrimination policy.
10/1: Dr. Mariann Hawken (Director of Instructional Technology), Google Gemini: AI Tools for Research, Teaching, & Learning
10/8: Brianna Hughes (STEM Reference & Instruction Librarian), Assembling an AI Toolbox: Access-Oriented Approaches to Scholarship and Instruction
10/15: Nina-Simone Edwards, JD (Senior Institute Associate, Institute for Technology Law & Policy), Beyond the Hype: Embedding Ethics in AI Policy for Libraries and Higher Ed
10/22: Jennifer Posada (PhD student, Human-Centered Computing), Making Sense of Data with AI: Lowering Barriers, Expanding Who Participates
10/29: Manas Gaur (Asst. Professor, CSEE), and Yash Saxena (PhD student), Building Trustworthy LLM Agents for Academia through Structured, Interpretable Knowledge Retrieval and Source Attribution
11/5: Roberto Yus (Asst. Professor, CSEE), The Privacy Paradox of GenAI: What It Knows, Why It Matters, and How We Fight Back
11/12: Eric Stokan (Assoc. Professor, Political Science & Director of CS3), Advanced Opportunities with AI and Large Language Models (LLMs): Examples from the Social Sciences
The seminar series is made possible by the following sponsors: Division of Information Technology, Center for Social Science Scholarship, CSEE Department, IS Department, and the Hackerman Foundation.