Welcome to your front door for using AI in research at Indiana University. This page brings together tools, events, funding opportunities, and community connections to help researchers responsibly and creatively apply AI in their work. Whether you’re exploring AI for the first time or integrating advanced methods into your projects, you’ll find resources here to learn, collaborate, and advance research with AI across disciplines.
Submit your information to be added to the Artificial Intelligence Research Network listserv.
Nov 03
Nov 03
Nov 03
Nov 03
Nov 03
Nov 05
Nov 05
Nov 05
Nov 06
Nov 09
Nov 09
Nov 09
Nov 10
Nov 10
Nov 10
Nov 10
Nov 11
Nov 11
Nov 12
Nov 12
Nov 13
Nov 14
Nov 17
Nov 17
Nov 17
Nov 18
Nov 19
Nov 23
Nov 23
Dec 01
Dec 07
Dec 07
Dec 09
Dec 15
Dec 17
Dec 18
Dec 21
Dec 29
Jan 04
Jan 12
Jan 18
Jan 26
Feb 01
Feb 02
Feb 09
Feb 09
Feb 09
Feb 10
Feb 11
Feb 12
Feb 13
Feb 14
Feb 15
Feb 15
Feb 16
Feb 16
Feb 17
Feb 18
Feb 18
Feb 19
Feb 19
Feb 20
Feb 21
Feb 22
Feb 23
Feb 23
Feb 23
Feb 24
Feb 25
Feb 25
Feb 26
Feb 27
Feb 28
Mar 01
Mar 01
Mar 02
Mar 02
Mar 02
Mar 03
Mar 03
Mar 03
Mar 04
Mar 04
Mar 05
Mar 05
Mar 06
Mar 07
Mar 08
Mar 09
Mar 09
Mar 09
Mar 09
Mar 10
Mar 10
Mar 11
Mar 11
Mar 12
Mar 13
Mar 14
Mar 15
View all IU AI events for additional offerings throughout the year.
At IU, several generative AI tools are available to faculty, staff, and students to enhance productivity, creativity, and efficiency. The following AI tools have been reviewed and are available for enterprise-wide use.
Generate text-based responses to prompts, summarize information, assist with content creation, perform public web searches, generate images.
Ability to summarize and work with documents in OneDrive and Teams storage spaces to which you have access; integration with Microsoft 365 apps, such as Word, Outlook, and PowerPoint; meeting summaries in Teams.
Generate text and images, answer questions, summarize or draft content, assist with research and brainstorming, verify responses using Google Search ("Double-check" feature), create custom AI agents called "Gems".
Upload your own documents (for example, PDFs, Google Docs), ask questions about uploaded content, get summaries, generate study guides and audio overviews, synthesize information across sources, share notebooks with others.
Supports advanced writing, editing, coding, math, and data analysis; document summarization, web browsing, and building custom GPTs; and offers higher message limits along with faster performance in more than 50 languages.
Generate and edit multimedia content, such as images, in Adobe applications.
Chat AIU is an AI-powered tool that leverages generative AI and IU data to deliver customizable chatbot experiences for university websites. It prioritizes data privacy while delivering reliable, context-aware responses.
Research and Academic LLM Services (REALLMS) is a large-language model (LLM)-powered service provided at no fee to the Indiana University community. All the hardware is on premises in the IU Data Center.
REALLMS provides two core services:
Build your own AI tool for developers.
About Azure OpenAI at IU
(requires IU Knowledge Base login)
For a full overview of the primary generative AI tools approved for use at IU, as well as their core features, data classification approvals, and usage guidelines, see Generative AI tools at IU.
Search the directory of IU faculty and staff who have conducted AI-related scholarly works in recent years.
If you have conducted AI-related scholarly works in recent years you’re invited to participate in this brief survey and submit your information to be added to the directory.
Sport produces a continuous stream of unstructured text, image, video, and audio from fans, athletes, organizations, and media. Turning it into evidence takes more than running a general-purpose model over it. Fine-tuned transformer models, vision-language models, and retrieval and agent architectures each fail in different and often silent ways on domain language, and a label a model assigns is useful only when validated against a construct the field theorizes. This group forms around that problem: what computational methods can measure reliably in sport participation, spectatorship, media, and organizational decision making, and what they cannot. No single unit holds the expertise this requires, which is why the group exists. Sport management and kinesiology supply the constructs, the domain knowledge, and the questions. Informatics and computing supply model development, evaluation design, and the engineering behind agent systems. Business supplies analytics and consumer research, media studies platform and content analysis, and public health outcome measurement for participation and well-being. Recruiting collaborators in evaluation design and annotation reliability is the immediate priority, because those are where this work most often fails. In its first year the group will meet regularly, assemble a shared dataset and evaluation benchmark from public sport data, and produce one collaborative publication and one external proposal. Its longer aim is to make IU a center for interdisciplinary sport analytics research and training, including a student analytics challenge convening teams from several institutions and connecting them with sport organizations across Indiana. Early conversations with an industry partner in cloud computing and artificial intelligence are underway, and an internal pilot is planned for spring 2027. Funding under consideration: Tier 1 and Tier 2 support in AY2026-27; the Research Conference Grant, DIRECT, and Layered-Learning in AY2027-28; and external proposals to NSF and sport-sector funders thereafter.
Lead Facilitator: Ty Qian
Email oescue@iu.edu for more information.
This working group explores AI-enabled wearable glasses that provide contextualized, real-time communication support for autistic individuals with perception and expressive communication challenges. The glasses would detect communication needs and provide context-appropriate prompts to help users interpret others’ communication and express themselves more effectively. Bringing together expertise from Information Systems at the Kelley School of Business and autism education at the School of Education, the group will pilot-test the approach and identify when it is helpful, as well as the features and configurations needed to provide effective support without overwhelming users.
Lead Facilitator: Antino Kim
Email oescue@iu.edu for more information.
Register your interdisciplinary working group to share your goals and membership with IU Research. We'll help connect your team with campus resources, potential collaborators, and strategic funding opportunities.
Submit this form to request IU Research funding, meeting support, or event logistics for your interdisciplinary working group. We'll help connect your team with campus resources and grant opportunities.
Luddy Artificial Intelligence Center
Luddy AI Center - Core AI Faculty
Luddy AI Center - Faculty by Research Area
Luddy AI Center - Labs & Centers
Metropolitan Governance and Management Transitions Laboratory
Acceptable uses of generative AI services at IU - Generative AI has potential applications across a wide range of industries, including art, writing, and software development. However, there are also concerns about the potential misuse of these tools and any data shared with the services.
Acceptable use of AI tools with IU research data - information about the currently approved uses of generative AI tools available at Indiana University with research data.
Research Data & AI - What to Know about Using Third-Party Large Language Models (LLMs such as IU-Managed ChatGPT Edu) with Research Data at IU.
Data Classification - IU Data Management
Management of Institutional Data (DM-01) - University Policies
For general questions and feedback, contact research@iu.edu.
