Skip to main content

Cornell University

Cornell AI4S Initiative

Artificial Intelligence for Sustainability

NRT Funding & Applications

The AI4S NRT program invites students from diverse disciplines to join a dynamic community dedicated to advancing AI-driven solutions for global sustainability. We seek trainees who are passionate about interdisciplinary research and education at the intersection of AI and sustainability.

The AI4S NRT program welcomes all Cornell students and visitors to participate in its interdisciplinary training, offering opportunities to engage in courses, seminars, program events, and research collaborations focused on AI and sustainability.

The AI4S NRT program provides the following funding support options. To qualify, trainees must be enrolled in one of the 16 participating graduate fields and show strong potential in AI and sustainability research.

1. AI4S Stipend-Supported Trainees

  • Support: Stipend, tuition, and health insurance for a full calendar year (Summer, Fall, and Spring semesters) at Cornell rates.
  • Eligibility: Stipend-supported trainees must be U.S. citizens, nationals and permanent residents per NSF guidelines and work with a CAISI faculty advisor.
  • Funding Review Process: A faculty committee evaluates each submission based on academic background, research experience, and fit with program goals, with special emphasis on diversity, inclusivity, and interdisciplinary collaboration. Final decisions are typically announced one month before the semester ends.
  • Expectations: Stipend-supported trainees should complete eight credits of AI4S courses within the one-year support period. Successful applicants should have passed their graduate field’s PhD qualifying exam and completed at least 6 credits of graduate-level foundational AI courses, as well as 6 credits of sustainability-related coursework, prior to receiving NRT stipend support.
Suggested Pre-requisite Courses for Stipend-Supported Trainees

Example graduate-level foundational AI courses (e.g., machine learning, data science, or optimization):

  • CS 6241: Numerical Methods for Data Science
  • CS 6784: Advanced Topics in Machine Learning
  • ORIE 6730: Mathematics of Deep Learning
  • SYSEN 6888: Deep Learning

Example sustainability courses (e.g., environmental systems, energy systems, or agricultural sciences):

  • CHEME 6660: Analysis of Sustainable Energy Systems
  • CS/INFO 2770: Excursions in Computational Sustainability
  • AEM 4880/ANSC 6880: Global Food, Energy, and Water Nexus

2. AI4S Student Project Trainees

3. AI4S Travel Grant Trainees

  • Support: Up to $1,000 in reimbursement to support domestic U.S. conference travel expenses.
  • Funding Review Process: Applications are accepted and reviewed on a rolling basis, with decisions communicated to applicants within one month of submission. Priority is given to projects that align closely with CAISI’s research objectives. Applicants who have secured the Graduate School Conference Grant for the same conference trip will have a higher likelihood of receiving this travel grant.
  • Application instructions and online application form.

★ AI4S Flexible-Term Trainees (Pilot launched in 2025)

  • Support: Fellowship includes stipend, tuition, and health insurance at Cornell rates for one semester (Summer, Fall, or Spring), with the possibility of renewal based on progress and program needs.
  • Eligibility: In accordance with NSF guidelines, eligibility for this fellowship is limited to U.S. citizens, nationals and permanent residents. Applicants should either (a) be in the early stages of their PhD and exploring potential dissertation topics in generative AI for life cycle sustainability analytics, or (b) be experiencing short-term research funding disruptions while continuing graduate research related to AI and/or sustainability.
  • Funding Review Process: Applications are reviewed each term by a faculty committee based on alignment with AI4S goals, preparation in AI and sustainability, and feasibility of the proposed work. Consideration is also given to students facing unexpected gaps in funding to help support continuity in their academic progress.
  • Expectations: Trainees funded in Fall or Spring should enroll in the AI4S course “AI for Sustainability” (3 credits). Summer trainees will focus on immersive research training. A research report is required at the end of each funded term, with the goal of supporting future dissertation work and potential publication. Trainees are also expected to participate in weekly project meetings and AI4S events.
  • Application instructions and online application form (deadline for Summer 2025 is April 15, 2025).