Important Dates

• Submission deadline: February 16, 2026 at 11:59 PM (any time zone on Earth)
• Acceptance notification: February 19, February 20, 2026
• Submit by sending mail to: presentations@chameleoncloud.org

Submission Instructions

Email your final submissions to presentations@chameleoncloud.org before the deadline.

Presentation proposals should be submitted as PDF documents, 2 pages in length, and include:

• Presentation title
• Author/Presenter name(s) and affiliation(s)
• Chameleon project ID(s) under which work was carried out
• Contact email
• If your presentation gets accepted, would you be interested in submitting a full paper? (Please put a statement, e.g., "Interested in full paper submission")

We are particularly interested in presentations that address AI and ML research on cloud testbeds. While we expect you to explain enough about your research or education projects to make the platform requirements clear, we also want you to save the important results for sharing at high ranking research conferences - your submissions here should focus on infrastructure requirements (hardware, configuration, etc.), experimental apparatus, challenges, and lessons learned.

Your proposal should address the following:

1. Project Overview. Briefly describe your research project or educational activity. What problem are you addressing? What is your approach?

2. Infrastructure Requirements & Usage. What specific Chameleon capabilities did you leverage? This might include:

• Hardware configurations (GPU types, accelerators, bare metal access)
• Networking and storage requirements
• Software stack control and customization
• Reproducibility features
• Heterogeneous resources and their management

3. Challenges & Insights. What worked well and what didn't? Where did you encounter bottlenecks or limitations -- whether in hardware availability, configuration complexity, software maturity, or experimental workflow? What was particularly valuable (and we should do more of) and features or capabilities are missing? How did Chameleon's capabilities compare to other public clouds and/or commercial cloud platforms for your specific needs?

4. Services, Tools & Workflow Support. What services or tools (beyond raw infrastructure) were critical to your work? This might include orchestration platforms, experiment management systems, data pipelines, reproducibility frameworks, or user interfaces. Where did existing tooling fall short? What gaps exist between infrastructure capabilities and researcher-friendly workflows?

We especially encourage submissions that:

• Provide detailed, specific insights about infrastructure requirements for AI/ML workloads
• Discuss challenges unique to AI research and education
• Represent diverse AI/ML domains (robustness/safety, sustainability, systems optimization, federated learning, education, etc.)
• Offer concrete recommendations for testbed evolution

Review & Selection

Submissions will be reviewed and ranked by a program committee to be announced soon. Selection will be based on the depth of infrastructure insights, relevance to the AI/ML research community, potential to inform testbed development, and contribution to productive discussion.

Travel Support

For the top 10 selected abstracts, we will reimburse travel expenses of up to $1,500 for one presenting author per abstract. Submitting a presentation proposal serves as your travel support application. Reimbursement covers transportation, lodging, and meals for attendance at the User Meeting.

What to Expect After Acceptance

Accepted presenters will be expected to:

• Attend the User Meeting in person
• Deliver a ~15-minute presentation on the morning or afternoon of April 15th
• Participate in a panel discussion following the presentation sessions
• Contribute insights to a post-meeting community report documenting infrastructure requirements, challenges, and recommendations for advancing AI research testbeds

This report will be published and shared with the research community to guide future development of Chameleon and similar cyberinfrastructure.

Teaching AI in the Real World: A Community Conversation

Symposium Chair Fraida Fund Research Assistant Professor • New York University

The AI Education Mini-Symposium will bring together educators teaching AI and machine learning to explore infrastructure needs that go beyond standard classroom resources. Instructors will share their experiences teaching AI/ML courses, followed by a panel discussion on current teaching challenges and unmet infrastructure needs.

We're particularly interested in understanding what educators need to effectively teach AI concepts that existing platforms (Google Colab, institutional HPC, commercial clouds) cannot easily support. The symposium will bring perspectives from diverse educational contexts to capture the full spectrum of teaching needs in AI education.

Applying AI to Accelerate Computational Reproducibility and Replicability

Symposium Chair Tanu Malik Associate Professor • SC'21 Reproducibility Chair • University of Missouri

Reproducibility and replicability (R&R) are cornerstones of scientific research, enabling validation, trust, and enhancing community knowledge. In computer science, conferences have played a central role in advancing R&R through formal Artifact Description (AD) and Artifact Evaluation (AE) processes. Despite significant community effort, reproducing CS artifacts remains challenging due to complex dependency chains, evolving software stacks, specialized hardware requirements, and the use of sophisticated experimental platforms and testbeds.

This session will explore how AI can strengthen R&R in CS research, with particular focus on the infrastructure demands of conference AE/AD processes. Beyond code analysis or automated testing, we are interested in exploring how AI can function as an adaptive infrastructure layer: intelligently reconstructing experimental environments, automatically resolving dependency conflicts, and navigating platform-specific quirks. The session will convene researchers and practitioners to identify concrete opportunities, challenges, and best practices, culminating in a working paper on AI-assisted reproducibility infrastructure for CS conferences.

Conference Location

NSF NCAR's Mesa Lab
1850 Table Mesa Dr, Boulder, CO 80305

Getting to the Mesa Lab

The Mesa Lab is on the side of a mountain and is not easily accessible by walking or biking. There are no public buses that go directly to the Mesa Lab. If you don't have a vehicle, plan to arrive via rideshare.

The parking lot is large and open to the public. It is a 5-10 minute walk from the lot up to the main entrance. See the Things to Know About the Mesa Lab page for cafeteria and other visitor info.

Getting to Boulder

Denver International Airport (DIA) is 45 miles from NCAR. Options for getting to Boulder:

• RTD Denver AB Bus (westbound) - the least expensive option, leaves the airport every half hour and stops throughout Boulder. Use RTD's Trip Planner for routes throughout the Boulder region.
• Lyft / Uber - commonly used but expensive (~$80 each way). Rideshare is widely available in Boulder.

Staying in Boulder

• Fairfield by Marriott Inn & Suites Boulder (10 minute drive to Mesa Lab)
  5397 South Boulder Road, Boulder, CO 80303
  Discounted rate: $125/night (incl. taxes & fees)  $139 regular
  Last day to reserve: March 25
• The Residence Inn Boulder (14 minute drive to Mesa Lab)
  3030 Center Green Drive, Boulder, CO 80301
  Discounted rate: $122/night (incl. taxes & fees)  $143 regular
  Last day to reserve: March 17

Getting Around and Enjoying Boulder

• Boulder Visitor Information - restaurants, alternative hotels, and things to do
• HOP Bus - gets to popular attractions, arrives every 7-15 minutes (City of Boulder transit info)
• B-Cycle - non-profit bike share with 41 stations. Use promo code UCAR30 for a free monthly pass (deselect auto-renewal when signing up)
• Lime - e-scooters in East Boulder, must be ridden on multi-use paths and bike lanes
• Boulder Open Space & Mountain Parks - hiking

Weather and Altitude

Boulder weather changes fast - dress in layers. Afternoon thunderstorms are common even on warm days, and temperatures drop quickly at night, especially at elevation. Keep a sweater and rain gear handy when hiking.

Boulder sits at 5,430 feet (1,655 m) above sea level. Stay hydrated, wear sunscreen and sunglasses, and drink plenty of water in the days before arrival - especially if coming from a lower elevation. Some visitors experience headaches, dizziness, or fatigue until they acclimatize.

Dress code at the Mesa Lab: Casual.