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Bruis Van Vlijmen

Battery Data Analytics Research @Stanford
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Eindhoven, North Brabant, Netherlands
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What are Bruis Van Vlijmen’s favorite books?
Profile Image for Bruis Van Vlijmen

Bruis Van Vlijmen

Battery Data Analytics Research @Stanford
Clay User Badge
Eindhoven, North Brabant, Netherlands
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Bruis Van Vlijmen is a professional with a diverse background in mechanical engineering and a passion for advancing the use of machine learning in the lithium-ion battery industry. With an impressive educational background, Bruis holds a Master of Science in Mechanical Engineering from Stanford University and a Bachelor's degree in Mechanical Engineering, earning the distinction of Cum Laude for their thesis with a grade of 9.0 from Delft University of Technology. Bruis has also spent time as a visiting research student at the University of California, Berkeley, focusing on fluid dynamics within mechanical engineering.

In addition to their academic achievements, Bruis has been involved in various organizations and research projects. They were a member of the Battery Data Analytics Research team at Stanford University, where they contributed to advancements in data analytics related to battery technology. Bruis also co-owned a business called JasjeDasje and worked as an advisor for Global Founders Capital. Their experience in strategy consulting and private equity internships with Roland Berger and Torqx Capital Partners demonstrates their business acumen and analytical skills.

Bruis has also gained international experience, studying at Imperial College London and participating in a summer school program at The Chinese University of Hong Kong, focusing on global enterprise management. They have also immersed themselves in Chinese language and culture through a summer school program at Beijing Language and Culture University.

With their expertise in mechanical engineering, data analytics, and business, Bruis is a well-rounded professional who is highly skilled in problem-solving and strategic thinking. Their interests lie in pushing the boundaries of machine learning within the lithium-ion battery industry, aiming to contribute to advancements in battery technology and sustainability.

This public profile is provided courtesy of Clay. All information found here is in the public domain.