With Knowledge Comes Power
Reducing the impact of technology on the environment
The world has an ever-increasing appetite for information. The use of smartphones, laptops, tablets and their accompanying hardware and software have placed high demands on our energy grids, which have in turn led to an increase in CO₂ emissions. Researchers estimate that unless changes are soon implemented, the technology sector will have a carbon footprint greater than that of the global aviation industry by the year 2020.
Dr. Ziliang Zong is dedicating his career to decreasing the energy consumption of the world’s information technology. At Texas State University, Zong is developing green design principles that will reduce the environmental impact of the computer industry and generate increased awareness among his students to the research and career opportunities that exist in this important emerging field.
With funding from the National Science Foundation to support his research, Zong has become internationally recognized for his contributions to green computing. Through his knowledge, expertise and enthusiasm for teaching the next generation of computer scientists, he is helping to take the bite out of our technology-driven lifestyles.
Facts about green computing
- In 2013, U.S. data centers used enough electricity to power every household in New York City for two years.
- Annual data center power consumption is projected to grow 54 percent by 2020.
- Green computing equipment and practices could cut data center carbon emissions up to 88 percent.
Sources: NRDC and Stanford's Steyer-Taylor Center for Energy Policy & Finance
Dr. Ziliang Zong
Dr. Ziliang Zong is an assistant professor in the Department of Computer Science. In 2015, he received the Texas State University Presidential Award for Excellence in Scholarly/Creative Activities. He earned his Ph.D. in computer science from Auburn University with the Distinguished Dissertation Award. Dr. Zong’s research is focused on high performance computing, green computing and systems, and big data analytics.