Chemical engineers, from the practicing process engineer to the academic researcher, are being asked more and more often to manipulate, transform, and analyze complex data sets. The combination of strategies and tools associated with those tasks is commonly referred to as data science. In the May AIChE Journal Perspective article, “Data Science: Accelerating Innovation and Discovery in Chemical Engineering,” David Beck, James Carothers, Venkat Subramanian, and Jim Pfaendtner, all of the Univ. of Washington, discuss data science as it relates to chemical engineers and highlight several application areas, including computational chemistry, synthetic biology, and energy systems and management. The article closes with thoughts on how data science principles can be included in the graduate and undergraduate curricula.
Chemical engineers have access to more, and more-complex, data than ever before. “For example, the stream of information available to an engineer in a modern plant is tremendous because of the proliferation of inexpensive instrumentation and the nearly ubiquitous high bandwidth and low-latency connectivity,” the authors write. “In the area of research and discovery, a student or researcher conducting data-intensive experiments, such as high-resolution particle tracking, might...
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