University of Maryland

Spring 2024

VCAI Seminar Series (Spring 2024)

Thursday, February 1, 2024
Calendar 2:00 pm – 3:15 pm
Thursday, February 22, 2024
Calendar 2:00 pm – 3:15 pm
Thursday, February 29, 2024
Calendar 2:00 pm – 3:15 pm
Thursday, March 7, 2024
Calendar 2:00 pm – 3:15 pm
Thursday, March 14, 2024
Calendar 2:00 pm – 3:15 pm
Thursday, March 28, 2024
Calendar 2:00 pm – 3:15 pm
Thursday, April 4, 2024
Calendar 2:00 pm – 3:15 pm
TBD
Thursday, April 11, 2024
Calendar 2:00 pm – 3:15 pm
Thursday, April 18, 2024
Calendar 2:00 pm – 3:15 pm
Thursday, April 25, 2024
Calendar 2:00 pm – 3:15 pm
Thursday, May 2, 2024
Calendar 2:00 pm – 3:15 pm

Faculty AI Roundtables

Joint with SODA, we’re running a series of faculty AI roundtables, in which a leader will select an AI-related topic and faculty with related interests will meet to discuss that topic. If you’d like to host one, please email Emily Dacquisto. Announcements and invitations will be sent to the mailing list.

AI & K-12 Education

Thursday, February 29 from 12:15 – 1:45 pm

Host: Jing Liu

Teams and AI (Joint with OTTRS)

Friday, April 26 from 12:00 – 1:30 pm

Host: Susannah Paletz

VCAI Tutorials

The tutorials are a complement to the Seminar Series. We’ll be offering 4 tutorials this Spring 2024 (details below). These are all meant to be hands-on experiences, and will therefore be in-person only for now. Room information will be sent after you RSVP. Please share widely with your PhD students, postdocs, etc.!
Tutorial 1
Host: Faisal Hamman,  PhD student in Electrical & Computer Engineering (UMD)
Time: Wednesday, February 7 from 1:00 – 2:00 pm
Title: Inside the Black Box: Interpretability and Explainability in ML/AI
Description: With growing model complexity in ML/AI, explainability and interpretability have become increasingly crucial, especially in high-stakes applications. In this tutorial, we’ll navigate various ML models, from logistic regression and deep neural networks to foundational models, highlighting key explainability techniques. The session will delve into the ethical and regulatory considerations vital in today’s AI applications. Attendees will also engage in a hands-on demonstration, applying these concepts to real-world scenarios.
Tutorial 2
Host: Hawra Rabaan, Postdoc in College of Information Studies (UMD)
Time: Monday, March 4 from 12:00 – 1:00 pm
Title: AI Unveiled: Navigating and Detecting the Social Implications of AI
Description: In this tutorial, participants will learn about a range of societal implications and the impact of AI on different areas, including human rights and values.
We will have hands-on activities to dissect and detect AI biases in various fields, including the entertainment industry, healthcare, finance, and more. Lastly, participants will partake in discussing ways to ensure algorithmic fairness.
Tutorial 3
Host: Vaishnav Kameswaran, Postdoc for VCAI (UMD)
Time: Tuesday, April 2 from 10:00 – 11:00 am
Title: Community-based participatory approaches & AI
Description: This tutorial is designed to educate AI researchers on the fundamentals of working with communities to design, develop and deploy meaningful and impactful AI technologies. The tutorial will help participants to:
– understand the principles and benefits of community-based participatory approaches;
– identify the key characteristics of successful community-researcher partnerships; and
– recognize challenges in conducting equitable research with communities
Tutorial 4
Hosts: Sandra Sandoval, Yu Hou, and Huy Tran Manh Nghiem, PhD students in Computer Science (UMD)
Time: Wednesday, May 1, 11:00 am – 12:00 pm
Title: How to use the Open AI API to programmatically prompt ChatGPT
Description: We will describe at a high level the considerations and requirements for prompting the GPT large language models programmatically, as well as walk through some examples in Jupyter/Colab notebooks. If time permits, we may touch on other large language models as well.