Smith School Presents AI Research At Lightning Speed

The information about AI capabilities always seems to be changing at lightning speed. That’s why the Robert H. Smith School of Business hosted the AI Lightning Talks, a fast and focused way to share recent areas of AI research from Smith faculty and PhD students. 

The event was held in Frank Auditorium Thursday evening, Oct. 23, 2025. During the month of October, schools throughout the University of Maryland have been holding AI-focused events. Director for the Center for AI in Business, Balaji Padmanabhan, said Smith held a similar event in 2024 for faculty to share insights, but this event was an expanded version open to all. 

The event featured 15 presenters who only had seven minutes to share their recent area of study. “The challenge for the presenters is that it is not a lot of time, but it’s just to give a flavor of what they are working on,” Padmanabhan said. “Some are completed papers; some are still works in progress.”

During his welcome to the audience, Padmanabhan said that though it’s a lot of information in a short period of time, if everyone walks away with at least one new piece of information, it’s a successful event.

Areas of discussion ranged from Associate Professor Margrét Bjarnadóttir’s research, which explored the use of AI to complement human physicians by better utilizing the information they document in their notes. Dean’s Professor of Entrepreneurship and Academic Director of the Dingman Center, Brent Goldfarb, spoke about using AI to speed up venture development. Rachit Kamdar, a PhD student, spoke about how LLMs can be used to better understand the interview process.

Jingyuan Cai, a first-year PhD student, spoke about how visual design is not just a decoration, but it drives different user responses. She ended her presentation with a note to say if you want more likes on your Instagram posts, use visuals with a variety of colors. Padmanabhan ended the session with insight from a recent conference where he participated in a panel discussing whether generative AI has the ability to forecast, which he noted would be a potentially fruitful direction for further research.

The full list of topics and speakers is included below. 

Topics and presenters featured:

1. Paging Dr. GPT – Margrét Bjarnadóttir
2. Machines that Need Us – Ali Faraji-Rad
3. Feeling Advantage from AI – Michael Trusov
4. From prompt-response to response-prompt – Ming-Hui Huang
5. Deepfakes for Calibrated Decision-Making – Yizhi Liu
6. (How) Can LLMs Enhance Privacy Research – Charlie Cheng
7. Generative AI—From Democratization to Average Trap to Model Collapse –  Roland Rust
8. Skill Building and Recruiting with StratpathAI – Deep Dalsaniya and Aromal Nair and working with Nicole M. Coomber
9. CommunityTwin to Improve Community Resilience – Louiqa Raschid
10. Using AI to speed up venture development – Brent Goldfarb and Marta Villamor Martin
11. LLMs and Personality Mismatch Effects in Interview Assessments – Rachit Kamdar
12. Prediction Markets in the age of Generative AI – Ritesh Das
13. Discover Hidden Visual Complexity – Jingyuan Cai
14. Knowledge-Driven AutoML via Large Models in Marketing Analytics – Lin Lei
15. Can Generative AI Forecast? – Balaji Padmanabhan