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.
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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...
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seminar
talk
UMBC AI
https://my3.my.umbc.edu/groups/umbc-ai
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UMBC AI
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LRM thinking agent
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Thu, 11 Dec 2025 13:04:23 -0500
Webinar: Generative AI for Graduate Students and Post Docs, 12/5
11-12pm ET Friday, December 5, 2025, free and online
Generative AI for Graduate Students & Post Docs
See how generative AI can augment your grad school journey via interactive demonstrations, applications and sandboxing
This session provides guided, hands-on experience with tools like
Gemini, Gemini Deep Research, and
Google NotebookLM and is designed to boost your learning, writing, and critical thinking. You'll try out real prompts, experiment with workflows, and see how
Gen AI can help you
brainstorm, organize research, and
assess insights. Framed by principles of
ethical and
responsible Gen AI use, you will be ready to integrate Gen AI thoughtfully into your academic practice.
UMBC Professor John Schumacher will lead this session. Dr. Schumacher is the Director of the Public Health Research Center (PHRC) of CAHSS and a Professor in the Department of Sociology, Anthropology, and Public Health (SAPH). He is also currently serving as a University System of Maryland Generative AI Pedagogy Fellow 2025-2026.
Sponsored by UMBC's Office of Graduate Student and Postdoc Professional Development
This is part of a FDC sponsored a series of workshops facilitated by UMBC's
John Schumacher, Professor of Sociology, Anthropology and Public Health and a USM Generative AI Pedagogy Fellow for 2025-26.
On Language Models and the Dangers of an Algorithmic View From Nowhere
Dr. John Bai, University of Canterbury
2-3:00pm EST Monday, December 1, 2025, online
Large language models (LLMs) are stochastic text generators, trained using large scale, web-scrapped datasets. Uncritically accepting LLM outputs as "truthful" or "objective" risks perpetuating an algorithmic "view from nowhere", which hides the many human decisions involved in developing, training, and fine-tuning LLMs. This talk aims to demystify language modelling and support critical, de-colonial analyses of (human and artificial) knowledge systems.
Dr. John Bai works as a Senior Lecturer in the School of Psychology, Speech and Hearing at the University of Canterbury. He completed a PhD in Psychology at the University of Auckland and a Postdoc in the Department of Educational Sciences at the Carl von Ossietzky Universität Oldenburg. His research on artificial intelligence in education takes a collaborative, interdisciplinary approach to examine educators' perspectives on the possible futures of education.
This webinar is part of a series on Decentering Intercultural Competence Research and Practice, organized by the Intercultural Competence Research and Practice Working Group (the World Council on Intercultural and Global Competence) in collaboration with the UMBC Center for Intercultural Research and Practice.
Register here
]]>
On Language Models and the Dangers of an Algorithmic View From Nowhere Dr. John Bai, University of Canterbury 2-3:00pm EST Monday, December 1, 2025, online Large language models (LLMs)...
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UMBC Center for Intercultural Research and Practice.
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poster for john Bai talk
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Mon, 24 Nov 2025 15:57:58 -0500
Fri, 05 Dec 2025 15:30:03 -0500
AI After Dark: Free AI Essentials Workshop 11/19
5-7:30pm Wed. Nov. 19 in person at UMBC Training Centers
UMBC Training Centers and AFCEA Central Maryland Emerging Leaders are teaming up to provide a condensed 2-hour free version of UMBC Training Center's AI Essentials workshop, which offers a well-rounded survey of AI for relative newcomers to the field. The free course will cover:
• AI & Generative AI fundamentals
• Survey of public & open-source models
• Multi-modal systems & prompt engineering
• AI applications in data analysis & visualization
• AI tools for image & media generation
• All delivered through a blend of lectures and live demonstrations.
This workshop is designed for entry-level learners with basic internet and Microsoft Office/Google Workspace skills who are looking to transition into AI-related roles or enhance their career prospects with AI knowledge. No prior AI experience required. If you attend, you will gain:
• A clear, practical foundation in AI concepts and tools
• Hands-on exposure to generative and multi-modal systems
• Real-world insights on how AI is applied in data, media, visualization
• A powerful learning experience to boost your professional profile
Location: UMBC Training Centers, 6996 Columbia Gateway Drive Ste 100, Columbia, MD 21046
Wikipedia from the World: Grounded Articles from Any Source
Alexander Martin, JHU
4-5:15pm EST Monday, Nov. 24 in ITE229 and online
Whether tracking emerging events, analyzing economic trends, or understanding public discourse, valuable information is scattered across modalities, from professionally produced news content and curated Wikipedia articles to firsthand footage of disasters livestreamed on social media. Building systems that can effectively retrieve, reason over, and synthesize these heterogeneous information sources is essential for knowledge-intensive applications.
This talk will focus on advancing both sides of the information-seeking pipeline: retrieving relevant multimodal evidence at scale, and synthesizing that evidence into coherent, Wikipedia-style explanations grounded in verifiable evidence. For retrieval, we will focus on recent progress in large-scale
multimodal retrieval, including new dataset, efficient and scalable first-stage retrieves, and reasoning reranking. In Wikipedia-style article generation, we will cover benchmarking and evaluating multimodal article generation and a method for enabling the use of
VLMs for high-level reasoning. Together, these components outline a path toward unified systems capable of transforming large collections of multimodal evidence into verifiable, human-readable articles.
Alexander Martin is a PhD candidate at Johns Hopkins University’s Center for Language and Speech Processing (
CLSP) and Human Language Technology Center of Excellence (
HLTCOE). He is advised by Dr. Benjamin Van Durme. Alex’s research focuses on end-to-end multimodal information retrieval and reasoning. His work aims to produce Wikipedia-style articles, grounded in retrieved documents and videos, in response to information seeking queries. His research has been published in CVPR, ACL, NAACL, and EMNLP. Alex is a recipient of the NSF’s Graduate Research Fellowship.
]]>
Wikipedia from the World: Grounded Articles from Any Source Alexander Martin, JHU 4-5:15pm EST Monday, Nov. 24 in ITE229 and online Whether tracking emerging events, analyzing economic...
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UMBC AI
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UMBC
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Mon, 17 Nov 2025 08:14:06 -0500
Generative AI in Teaching II: Applied Skills and Use Cases
11:30-12:30 EST Tue., Nov. 11, Public Policy 204 and online
Building on the first session in the series of Generative AI and Teaching, this interactive session highlights applied skills and practical use cases. Participants will practice effective prompting, explore discipline-specific scenarios, and consider assignment design strategies. Examples will touch on advanced features (custom GPTs/GEMs, Canvas Mode, Deep Research Mode, agent mode) related to teaching.
Part II of an Introduction to Generative AI in Teaching Series by John Schumacher, Professor of Sociology, Anthropology and Public Health and a USM Generative AI Pedagogy Fellow for 2025-26. Whether you have already begun exploring AI for your teaching and for student learning, are an AI-skeptic, or are somewhere in between, joining Dr. Schumacher and your UMBC colleagues for these hands-on workshops will help you to deepen your understanding of how AI works, some of the ethical concerns of AI-usage, and when and how to use which GenerativeAI tools. This is a reprise of the workshop held in October and is offered in person or online.
Register here to participate in person or get the online link
]]>
Building on the first session in the series of Generative AI and Teaching, this interactive session highlights applied skills and practical use cases. Participants will practice effective...
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UMBC AI
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UMBC AI
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ai on circuit board
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Mon, 10 Nov 2025 08:16:22 -0500
Talk: Dealing with unstructured data, APIs, and API calls to LLMs 11/7
Dr. Eric Stokan, 12-1:30pm Fri. Nov. 7, Public Policy 438
In this session
Dr. Eric Stokan, director of UMBC's
Center for Social Science Scholarship, will discuss ways to process and handle unstructured data such as text and images. The session will take place in person at UMBC in
Public Policy 438 from 12-1:30pm on Friday, November 7.
Topics he will cover include:
- Using the R programming language to work with unstructured data like text and images
- Using OpenAI (makers of ChatGPT) to analyze unstructured data through an API
- Comparing LLMs to other AI techniques such as topic models and named entity recognition
- Discussing more effective ways to prompt LLMs
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.
]]>
In this session Dr. Eric Stokan, director of UMBC's Center for Social Science Scholarship, will discuss ways to process and handle unstructured data such as text and images. The session will take...
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UMBC Center for Social Science Scholarship
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talk by Dr. Eric Stokan
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Thu, 06 Nov 2025 09:42:12 -0500
Thu, 06 Nov 2025 10:16:58 -0500
Generative AI in Teaching I: Literacy and Foundations New
7-8pm EST Monday, Nov. 3, 2025, online
Generative AI in Teaching I: Literacy and Foundations
7-8pm EST Mon, Nov. 3, 2025, online
This session introduces the basics of generative AI and its implications for teaching and learning. It focuses on AI literacy by examining what these tools are, what they can and cannot do, basic prompting, ethical & responsible use, and how they may impact classroom practice. Participants will see short demos of ChatGPT, Gemini, Perplexity, and have time for Q&A. This is a reprise of the workshop held by Dr. John Schumacher, in October.
Get more information and register here.
]]>
Generative AI in Teaching I: Literacy and Foundations 7-8pm EST Mon, Nov. 3, 2025, online This session introduces the basics of generative AI and its implications for teaching and learning. It...
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UMBC AI
https://my3.my.umbc.edu/groups/umbc-ai
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UMBC AI
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generative ai in teaching
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Sat, 01 Nov 2025 14:27:18 -0400
Talk: I'm Not Teaching with Generative AI, But What Do I Still Need to Know?
12-1pm EDT Monday, October 27, online
This session highlights what faculty need to know, even if they are not adopting AI in their own teaching. Topics include basic Gen AI literacy, a critical examination of student use of AI tools, equity and access, ethical concerns, credible sources of Gen AI information, and implications for assessment and pedagogy.
The FDC is co-sponsoring a series of three workshops facilitated by John Schumacher, Professor of Sociology, Anthropology and Public Health and a USM Generative AI Pedagogy Fellow for 2025-26. Whether you have already begun exploring AI for your teaching and for student learning, are an AI-skeptic, or are somewhere in between, joining Dr. Schumacher and your UMBC colleagues for these hands-on workshops will help you to deepen your understanding of how AI works, some of the ethical concerns of AI-usage, and when and how to use which Gen AI tools. These workshops will be held online via Webex at noon on October 6, October 13, and October 27, 2025. They will repeat in November.