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Na Zhang

PhD/Applied Mathematics and Statistics 
Technical Staff 

I received my PhD degree in Applied Mathematics and Statistics. My doctoral advisor is Professor Yuefan Deng. My PhD work focused on developing multiscale models and efficient numerical algorithms for domain-specific applications that heavily rely on high performance computing technologies. My thesis topic is “Design and Analysis of Parallel Algorithms for Multiscale Modeling of Platelets.” I got my Bachelor's degree in Physics from Nankai University, China. I also have a double Bachelor's degree in Finance.

Position Description

I am member of the technical staff working on high performance computing within VMware’s Office of the CTO. We are a group of people focusing on identifying and exploring technical areas and trends of long-term interest to VMware while also fostering and supporting innovation programs throughout VMware’s R&D organization. My job includes but is not limited to: identifying performance issues of various HPC workloads and reducing overheads; creating HPC proofs-of-concept with customers; designing HPC reference architectures; providing technical guidance and support to integrate traditional HPC middleware and VMware’s cloud platforms; and providing feedback to R&D regarding future enhancements needed for HPC customers.

Structure of a Typical Day

I usually get into the office around 9:30 and leave at 6:30. Working in OCTO, instead of on a product line, I don’t have a typical day like other software engineers, which could be to fix bugs, implement new features, code quality, etc. I have multiple tasks to work on in parallel so a typical day is to prioritize work according to what my manager or I think most important. Sometimes I need to travel - to attend internal/external conferences like the upcoming supercomputing conference (SC16). 

How Did You Find the Job?

I had two summer internships at VMware under the guidance of my current manager. Then I became a full-time employee after graduation.

Advice to Other Students

Learn as many emerging technologies as you can during graduate studies, even if it’s not your research area. 

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