Project ISF: Synthesizing Facility-Level Water Consumption Datasets in Computing at Scale Program DUIRI - Discovery Undergraduate Interdisciplinary Research Internship Term Spring 2025 Status Accepted Research Area Sustainable computing Description Water is centrally important to sustainability: it supports ecosystems and human society, and contributes to the growth of economic sectors, regions, and countries. Water is inextricably connected to energy, and to biodiversity. Water scarcity arises when demand exceeds supply, and includes water quantity and quality. In many cases, the impacts of water consumption are local, rather than global, and mitigating those impacts requires spatially explicit information. Computing, often overlooked in the discussion of water consumption, significantly contributes to global water usage. The three primary sources of water consumption in computing are artificial intelligence (AI), datacenters, and semiconductor chip manufacturing. In order to make decisions about water management, infrastructure development, and to understand inequities in access to water, it is necessary to develop methods for water data discovery, synthesis, and analysis. This project aims to tackle the water footprint issue in computing by focusing on synthesizing and understanding large-scale, facility-level water consumption datasets for computing. Supervisor Yi Ding Mentor Inez Hua Type of work required Students are expected to dedicate 10-15 hours per week to this project. They will participate in weekly meetings with faculty supervisor and mentor to report their progress. Key responsibilities include:
1. Leverage LLMs to develop queries to speedup the data discovery process for water withdrawal and water discharge data.
2. Write Python code and leverage LLMs to link withdrawal and discharge data.
3. Build water consumption datasets and documenting results for publication.

Websites Qualifications Undergrads in Computer Science, Computer Engineering, or Environmental Engineering at Purdue-West Lafayette, junior or senior level, with interest in AI and sustainable computing. Programming skills are required. Credit Hours 0 Weekly Hours 10 (estimated)