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The NeurIPS 2026 Smart Buildings Competition, hosted on Kaggle, asks entrants to train machine-learning or reinforcement-learning HVAC control policies on simulated buildings. The policies are then tested on unseen buildings that differ in size, layout, weather, materials and HVAC systems. HVAC accounts for 40 to 60 percent of building energy use, so the goal is policies that transfer across buildings with minimal setup.
The organisers are the University of Washington, the NSF AI Institute in Dynamic Systems, Harvard, Columbia and Kajima Corporation. The $40,000 prize pool includes a $25,000 leaderboard pool, with first place at $5,750 and fourth to eighth place at $2,500 each.
A $15,000 paper track runs through OpenReview: round-one papers are due 13 November 2026 and earn $250 to $1,000, and final papers are due 15 January 2027 and earn $500 to $3,000. The NeurIPS workshop is on 13 December 2026, and winners may test their policies on three real buildings. Solutions are licensed under CC-BY 4.
0. The competition pages give conflicting entry deadlines of 3 December 2026 and 3 January 2027, so applicants should check the Kaggle page.
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Or search similar grants →According to the current listing, eligibility includes: Individuals or teams of up to five worldwide, aged 18+ (or age of majority) with a Kaggle account; sanctioned jurisdictions excluded. Confirm the full requirements in the official notice before applying.
The current listing shows $40,000 total; $25,000 leaderboard pool (1st $5,750 to $2,500 for 4th-8th) plus $15,000 paper track ($250-$3,000 awards). Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for NeurIPS 2026 Smart Buildings Competition for Transferable Reinforcement Learning HVAC Control Policies are due January 15, 2027. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
NeurIPS 2026 Smart Buildings Competition for Transferable Reinforcement Learning HVAC Control Policies is funded by University of Washington with the NSF AI Institute in Dynamic Systems, Harvard University, Columbia University and Kajima Corporation (hosted on Kaggle). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
The Center for Socially Responsible Artificial Intelligence at Penn State runs an annual internal seed funding competition for collaborative faculty research that advances socially responsible ways of using, building and deploying AI technology. Two tiers are offered: Collaboration Initiation Funding of 500 to 5,000 US dollars for forming new cross-disciplinary teams, and Pilot Project Funding of 5,000 to 25,000 US dollars for preliminary studies intended to seed larger external proposals. The centre's stated emphasis areas include AI for social good, accountability, consciousness, justice, equity, ethics, fairness, inclusivity, transparency, privacy and human agency in AI systems, which makes the call a genuine responsible-AI instrument rather than a general AI research fund. Applications for the 2027 funding cycle are due 2 November 2026, with funded projects starting in Spring 2027 and running up to two years. Recent cycles funded seven projects in Spring 2026, seven in Spring 2025 and five in Spring 2024, so the competition is small but the acceptance rate is more favourable than most external programmes. Proposals must be collaborative; the centre is explicit that it is funding team formation and interdisciplinary work rather than single-investigator continuation, which in practice means pairing computational and social-science, legal, humanities or domain expertise. The award is restricted to Penn State faculty and is therefore relevant only to that institution, but it is one of the more clearly specified university responsible-AI seed mechanisms currently published.
The Yale AI Seed Grants 2026 programme, run by the Office of the Provost AI Initiatives, funds interdisciplinary artificial intelligence work through Research Grants of up to 100,000 US dollars and Workshop Grants of up to 20,000 US dollars, plus two supplemental Yale and the World awards of 15,000 US dollars each for international relationship building. The submission deadline was Friday 6 February 2026 at 11:59pm, with notification on 1 May 2026 and a project period of 12 to 18 months starting 1 July 2026. Research proposals are organised into four categories: Foundation Models, Model Development and Robotics; AI Research Application Development to Advance Disciplines; LLM-powered Analysis, Impact, Information and Advocacy Projects; and Critical and Evaluative Approaches to AI. Workshop themes include Human Struggle in the Age of AI, Ethics and Responsibility, Interdisciplinary Applications of AI to Advance Science, AI and Human Health, and Novel Approaches to the Humanities and Arts. The defining structural requirement is mandatory interdisciplinarity: teams must include two or more faculty from different fields, led by a full-time Yale faculty or staff member eligible to serve as PI, which rules out single-investigator proposals however strong. The programme is also notable for funding critical and evaluative approaches to AI and humanities and arts themes on equal footing with technical model development, making it one of the more intellectually broad university AI funds; a philosopher, historian or legal scholar working with a computer scientist is a core intended applicant rather than an edge case. One proposal per PI is allowed, though individuals may join multiple proposals as teammates. Submission was through InfoReady with a five-page narrative for research and three pages for workshops, plus CVs, budget and timeline. The 6 February 2026 deadline has passed.
The Oberndorf AI Medical Catalyst Grant funds University of Florida medical students to carry out research applying artificial intelligence to medical problems, with each award set at 5,000 US dollars. It sits within the Oberndorf AI Medical Scholarship Program, endowed by a donation from Lou and Rosemary Oberndorf and run jointly by the UF College of Medicine Office of Research and the Intelligent Clinical Care Center, known as IC3. The programme's design reflects a specific view of what limits clinical AI training: it does not require applicants to have prior AI experience, but it does require that each project have an AI mentor who is a current IC3 member or has membership pending and who brings extensive AI experience. In other words, the money follows the mentorship rather than the credential, which makes the award genuinely accessible to clinically oriented students who have the interest but not yet the technical background. Eligible project scope spans clinical decision-making, diagnostics, research and healthcare management, and past awardees have worked on large language models over electronic health record data, predictive analytics for kidney disease, and AI image segmentation in medical imaging. The most recently published cycle closed on 5 January 2026 with submission through the University of Florida InfoReady platform. No deadline is recorded here because the next cycle's date has not been published. For UF medical students, this is the designated on-ramp into AI research; for everyone else it is a useful model of how an institution can lower the barrier to clinical AI training.
Gates committed $540.2 million over a decade to the Institute for Health Metrics and Evaluation — the largest gift in University of Washington history — while IHME's federal grant income falls from $7.3 million to a projected $4.8 million. The gift is a case study in the anchor-funder model: what it can do that federal money cannot, and the concentration risk it quietly underwrites.
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