“I am passionate about solving challenging problems,” said Chayawan (Earth) Jaikla, PhD ‘21. “Cybercrime has been on the rise, especially in 2020 and 2021, and with this increase it has become imperative to develop machine learning models that automatically detect and assist in the elimination of cyber threats on a global scale.”
With an ever-increasing number of cyber attackers attempting to steal, expose, alter or destroy data – including compromising individuals’ personal and confidential information – Jaikla has undoubtedly found a challenging problem.
She currently works as a data and applied scientist at Microsoft on the Microsoft Cloud Security team, where she and her colleagues concentrate on discovering and investigating cyber threats.
As a graduate student, she was a member of the Stanford Project on Deepwater Depositional Systems (SPODDS) research group. Jaikla applied techniques typically found in separate disciplines to deliver her PhD dissertation, which focused on a groundbreaking understanding of ancient sedimentary systems deposited in the deep sea and the processes in which they were deposited. The application of machine learning combined with extensive fieldwork, data collection and interpretation allowed her to provide quantitative results to support her thesis.
Gaining experience through conducting interdisciplinary research played a considerable role in preparing Jaikla for this position, she said.
She now utilizes the skills she honed by being at the forefront of extensive research projects to develop and sustain machine learning models that monitor, mitigate and protect websites threatened by cyber-attacks – a significant contribution to cyber security worldwide.
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