AI-Thirst: Synthesizing Water Consumption Datasets in Computing

AI-Thirst: This team will synthesize facility-level water consumption data for computing facilities, with a focus on datacenters and semiconductor manufacturers, by using machine learning.

Advisors

Description

Water is centrally important to sustainability. Computing significantly contributes to global water consumption. The three primary sources of water consumption in computing are artificial intelligence (AI), datacenters, and semiconductor manufacturing. To guide water management, infrastructure development, and to understand inequities in access to water, it is necessary to develop methods for water consumption data discovery, synthesis, and analysis. However, such data, especially related to computing, is lacking. This VIP project seeks to tackle the water consumption aspects of computing by synthesizing and understanding facility-level water consumption datasets specific to different life cycle stages of computing.

website: https://y-ding.github.io/

Relevant Technologies

  • Machine Learning
  • Computer Engineering
  • Environmental Engineering

Required Qualifications

  • Basic understanding of Machine Learning

  • Programming skills in Python

Preferred Qualifications

  • Computer Engineering

  • Environmental Engineering