Xiao Lu
Info
First Name: Xiao
Last Name: Lu
Graduation Year: 2021
Country: China
Education: Shanghai International Studies University

Why MIDS?

MIDS differentiates itself to me because of its interdisciplinary approach. Unlike other data science programs dedicated solely to data techniques, The interdisciplinary aspects of MIDS would push me to think deeper on how to apply data science really into the field that I am passionate about. Besides, since data science is such a team-based endeavor, MIDS would also teach me how to enhance my teamwork through its diverse cohorts and well-rounded soft skills training.

What excites you about data science?

Data science provides solutions to problems unsolvable using traditional tools in the past. To be specific, data science is uncovering a hidden layer of consumer insights that previously could not have been easily discovered otherwise.

What research area are you most interested in?

I am particularly passionate about applying data science to consumer behavior, which is an inherently interdisciplinary field covering marketing and business, psychology and neuroscience. It exactly matches the interdisciplinary aspect of MIDS. Consumer researchers today are expected to deliver faster, cheaper, and more impactful insights than ever before. So it is imperative to transform the way we perform consumer research. I am thrilled to see the transformations that data science will introduce to consumer research efforts from ideation to communication.

What do you like to do in your free time?

I would spend time alone walking in Duke campus and appreciate the beauty of this ‘Campus in the Forest’ and the exquisiteness of its gothic architecture.

What is one interesting fact about you?

I was a baritone in an Acapella group during college. I can sing as both a solo vocalist and a backing vocalist. Sometimes I think the backup part is more interesting because it creates harmony with other back up parts (Soprano, Alto ,and Bass), which creates even more fantastic music than that by solo alone.