Celebrating Diverse Ideas in Responsible AI

Join us for the RAISE Winter Exposition, a welcoming event celebrating diverse ideas and research in responsible AI. We invite submissions of original or cited work that align with RAISE’s mission to foster trustworthy, sustainable, and equitable AI solutions.

Whether you’re sharing your research or joining as an attendee, this is your chance to connect, collaborate, and make a difference. Everyone is welcome! Please reserve your spot by Jan. 31, 2025. 

RSVP as Attendee

Event Schedule

Feb. 28th:

  • 9 am- 10 am: Keynote by Dr. Ece Kamar, VP and Lab Director of AI Frontiers at Microsoft Research.

    Keynote Title: AI Agents as the Next Frontier in AI

  • 10 am – 12 pm: Poster talks / Unconference

  • 12 pm – 1 pm: Lunch

  • 1pm – 3 pm: Networking

Keynote Speaker: Dr. Ece Kamar

Eligibility & Submission Guidelines

Important Dates

Open to all RAISE affiliates, including high school students, university students, graduate students (MS or PhD), and faculty members.

You’re invited to showcase original research, ongoing projects, published work, or relevant papers at the poster session (with proper attribution).

 

 The results of the abstract submissions are in!

For any questions, please reach out to Kirandeep Kaur at kaur13@cs.washington.edu or Yaxin Luo at yaxinluo@uw.edu.

Call for abstracts opens:              Jan. 06, 2025

_____________________________________

Abstract submission closes:        Jan. 18, 2025

_____________________________________

Notice of acceptance:                   Jan. 24, 2025

_____________________________________

RSVP for participation closes:     Jan. 31, 2025

_____________________________________

Posters / Presentations Selected

Name Position Title of the project
Jiayi Yuan Researcher/ Visitor InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma
Jiaqi He Student A Framework for Measuring and Benchmarking Fairness of Generative Crowd-Flow Models
Navreet Kaur Student Persona-based Evaluation of LLMs for substance-use Information
Kentaro Hoffman Postdoc Bayesian Optimal Experimental Design of Streaming Data Incorporating Machine Learning Generated Synthetic Data
Julia Kharchenko Student How Well Do LLMs Represent Values Across Cultures? Empirical Analysis of LLM Responses Based on Hofstede Cultural Dimensions
Himanshu Jaikumar Naidu Student iOSPointMapper: Enabling Equitable Navigation of the Pedestrian Environment with AI and Mobile Devices
Anna-Maria Gueorguieva Student Large Language Models’ Perception of Stigmatized Groups in Social Contexts differ from Human Attitudes
Harshita Chopra Student Feedback-aware Monte Carlo Tree Search for Efficient Information Seeking in Goal-oriented Conversations
Nicholas Clark Student Can We Trust LLMs? Understanding Epistemic Challenges Through Mediator Incoherence
Jonathan Jiang Student Promoting diversity and inclusion of research study participants through developing linguistically and culturally tailored virtual study assistants using generative artificial intelligence (AI)
Eddie Hock Student Embracing Multiplicity in Uncertain Times: Doing Social Science with Rashomon Sets
Tim Hua Independent researcher Hierarchical Monitoring and Talk-Back for AI Control
Ryan Lagasse Student Targeted LLM Steering: Mitigating Side Effects with Selective Feature Control
Pawan Gupta and Aditya Gupta Professional / High School Student A Philosphical Map of AI Alignment
Preetam Dammu Student Dynamic-KGQA: A Scalable Framework for Generating Adaptive Question Answering Datasets
Kirandeep Kaur & Manya Chadha Student Responsible Adaptation of LLMs for Robust Recommendations
Muhammad Aurangzeb Ahmad Faculty AI Surrogates for End-of-Life Decision-Making