Activities and Events

Trainees conduct research in one of four research tracks, guided by experienced faculty mentors, while participating in cross-track activities. Visit the Research page for information about the research tracks: software, hardware, human-computer interaction, and cognitive models.

Financial travel support enables presenting accepted research papers at relevant professional research conferences.

Brief lab rotations in other tracks provides experiences with varying lab cultures, cross-track insights, expansion of scientific vocabulary, and networking opportunities.

Trainees complete technical internships at national research labs and industrial organizations, with formal orientation provided prior to the internship experience.

Trainees visit with partner institutions in a campus interview-like experience. The itinerary may include giving a research talks, meeting with administrators and/or faculty, interacting with diverse students, sharing about the NRT experience and Ph.D. student life, and a follow-up virtual meeting to circle back on visit connections.

Until graduation, Trainees remain eligible to apply for seed funding to support project ideas in an open call issued on an annual basis.

Until graduation, Trainees have the opportunity to seek elected leadership roles on Trainee Council, as well as to engage in peer-mentoring roles during onboarding, retreats, and hackathons. 

Retreat with invited distinguished AI speakers, technical demos/tutorials on state-of-the-art topics in AI, career-advancement forums, and mentoring feedback on mid-way research reports. Example sessions include:

• Tenure-track Hiring, Lorraine Stinebiser, Office of Faculty Diversity and Recruitment
• Strategies for Coping with Growth in AI Research Literature, Roman Koshykar, GCCIS Liaison/Librarian, Wallace Library

Networking events connect Trainees with diverse postdoc and early-career near-peers in a fun and interactive format.

A new course that meets once a week with the learning experience focused on three themes:

1. Design and evaluation methods
2. Human factors basics
3. Human-centered design principles

Case studies are used to illustrate topics and survey the current state of AI research, development, and controversies.

Panels discuss advanced topics such as trends in machine learning and emerging human-sensing AI, privacy preservation, or open problems in data collection techniques. A panel on grant writing and peer review prepares Trainees to submit seed grant project proposals.

Workshops on diversity and inclusion topics that offer training with expert workshop facilitators:

• Building a Foundation for Inclusive Research, Taj Smith, Diversity Education Director
• Diversity Statements, Scott Franklin, Director, CASTLE Center for Advancing STEM Teaching, Learning and Evaluation
• Engaging with Undergraduate Researchers and LSAMP/McNair, Kate Torrey, Director of McNair Scholars and LSAMP

Workshops that offer training in communication, ethics, and teamwork with expert workshop facilitators:

• Personal and Collective Responsibility, Irina Mikhalevich, Assistant Professor and philosopher of science, cognitive science, and ethics
• Democracy, Justice, and AI, Irina Mikhalevich, Assistant Professor and philosopher of science, cognitive science, and ethics
• Collaborative Research, Scott Franklin, Director, CASTLE Center for Advancing STEM Teaching, Learning and Evaluation
• Communication with Broader Audiences: Policy and Decision-makers, Media, Public, Ammina Kothari, Director of the Harrington School of Communication and Media, University of Rhode Island
• Using Storytelling Techniques to Communicate STEM Research, Ammina Kothari, Director of the Harrington School of Communication and Media, University of Rhode Island

In AI hackathons with human sensing data, students are challenged with creating responsible and deployable AI systems in teams.

Plenary talks, research talks, and advanced PhD student talks are offered with the Center for Human-aware AI, providing opportunities to interact with speakers about human-aware AI research.

Mentored experiences with sharing and releasing datasets created in AWARE-AI research tracks or other relevant projects, with an annual newsletter that provides up-to-date information on available data resources.