August 26, 2021
-
3
minute read

Kye Kim: An Interdisciplinary Track from Stanford to RI

People

By the light of the crackling Zoom hearth flames, over tea-mug emojis, we sat down with our talented Frontend Engineering Lead Kye Kim this week.

"I love studying human communication and how it’s related to the bigger patterns in society. Human-computer interaction makes up a big portion of the communication that humans have on a daily basis.”

Chatting with Kye over a video conference felt like an apt metaphor: throughout our discussion, the biggest theme that emerged was Kye’s fascination with both humans and computers, and especially for finding the best way to connect them. 

Kye was born in Suwon, Korea, and came to the United States in 2014 for her B.S. and M.S. in Computer Science at Stanford University, specializing in Human-Computer Interaction. After completing her M.S., Kye joined Knowhere where she developed a content management platform for newsrooms to use AI for journalism, and we were thrilled to welcome Kye on the Robust Intelligence team in January 2021.

What past life/hobby/school/work experiences do you think impacted your journey to software engineering?

Kye mentioned that before college, she always saw herself as the kind of person who gravitates towards work related to language or visual arts. She pictured herself studying psychology or film production. We were curious: what made her dive into software engineering so fully?

“I enjoy jumping into something that I don’t feel confident about or see myself doing—coming to the States and getting involved in computer science was definitely an example of that.”

While at Stanford, Kye developed her software engineering skills as a part of multiple interdisciplinary project teams. Her work involved understanding the unique backgrounds and workflows of professionals in industries ranging from journalism to retail, and cardiovascular medicine. These projects gave Kye a sense of what she has come to enjoy in her career: small focused teams that develop a strong understanding of the human need they are trying to serve. For example, as part of the VascTrac cardiovascular research team at the Stanford School of Medicine, Kye shadowed clinical study coordinators to design a software platform that replaced their paper workflows.

With Stanford teammates for a computational journalism project

“I found myself enjoying building things from end to end, starting with ‘for whom’ and ‘for what’, then iterating towards a solution based on user feedback” Kye said. Despite pursuing computer science as her major and profession, Kye never lost her early interests in video storytelling and social psychology and leverages her interdisciplinary background as she leads the frontend engineering team for RI. 

“At the end of the day, no matter how complex the testing results our models provide,  it’s humans who digest the information and take actions. And it’s always a tricky and fun question to ask - how does our interface spur corrective action taking in the mind of our users?”

What do you find the most satisfying or interesting about working at Robust Intelligence?

“I want to develop machine learning as a beneficial tool for humans.”

Currently, Kye is most excited about the transition from REST API to GRPC. We didn’t know what these acronyms meant, so we asked for an explanation, and Kye gave us a beautiful one: “The simplest way to put it is that there is a protocol on specifying data that different services communicate to each other. There is a backend that receives and responds, and then the frontend takes requests from the user and processes it to the backend. These [REST API and GRPC] are just two different types of communication, and we are transitioning between the types.”

Before the last flames in the Zoom hearth virtually crackled away, Kye offered a last nugget of wisdom. “I was initially very intimidated by the fact that this company is AI and ML oriented, and had the impression that it would be very dry and not a place that I would belong to. Now, I realize how interdisciplinary everyone and everything is here – so, I want people to know that they can develop a whole range of software engineering skills here.”

August 26, 2021
-
3
minute read

Kye Kim: An Interdisciplinary Track from Stanford to RI

People

By the light of the crackling Zoom hearth flames, over tea-mug emojis, we sat down with our talented Frontend Engineering Lead Kye Kim this week.

"I love studying human communication and how it’s related to the bigger patterns in society. Human-computer interaction makes up a big portion of the communication that humans have on a daily basis.”

Chatting with Kye over a video conference felt like an apt metaphor: throughout our discussion, the biggest theme that emerged was Kye’s fascination with both humans and computers, and especially for finding the best way to connect them. 

Kye was born in Suwon, Korea, and came to the United States in 2014 for her B.S. and M.S. in Computer Science at Stanford University, specializing in Human-Computer Interaction. After completing her M.S., Kye joined Knowhere where she developed a content management platform for newsrooms to use AI for journalism, and we were thrilled to welcome Kye on the Robust Intelligence team in January 2021.

What past life/hobby/school/work experiences do you think impacted your journey to software engineering?

Kye mentioned that before college, she always saw herself as the kind of person who gravitates towards work related to language or visual arts. She pictured herself studying psychology or film production. We were curious: what made her dive into software engineering so fully?

“I enjoy jumping into something that I don’t feel confident about or see myself doing—coming to the States and getting involved in computer science was definitely an example of that.”

While at Stanford, Kye developed her software engineering skills as a part of multiple interdisciplinary project teams. Her work involved understanding the unique backgrounds and workflows of professionals in industries ranging from journalism to retail, and cardiovascular medicine. These projects gave Kye a sense of what she has come to enjoy in her career: small focused teams that develop a strong understanding of the human need they are trying to serve. For example, as part of the VascTrac cardiovascular research team at the Stanford School of Medicine, Kye shadowed clinical study coordinators to design a software platform that replaced their paper workflows.

With Stanford teammates for a computational journalism project

“I found myself enjoying building things from end to end, starting with ‘for whom’ and ‘for what’, then iterating towards a solution based on user feedback” Kye said. Despite pursuing computer science as her major and profession, Kye never lost her early interests in video storytelling and social psychology and leverages her interdisciplinary background as she leads the frontend engineering team for RI. 

“At the end of the day, no matter how complex the testing results our models provide,  it’s humans who digest the information and take actions. And it’s always a tricky and fun question to ask - how does our interface spur corrective action taking in the mind of our users?”

What do you find the most satisfying or interesting about working at Robust Intelligence?

“I want to develop machine learning as a beneficial tool for humans.”

Currently, Kye is most excited about the transition from REST API to GRPC. We didn’t know what these acronyms meant, so we asked for an explanation, and Kye gave us a beautiful one: “The simplest way to put it is that there is a protocol on specifying data that different services communicate to each other. There is a backend that receives and responds, and then the frontend takes requests from the user and processes it to the backend. These [REST API and GRPC] are just two different types of communication, and we are transitioning between the types.”

Before the last flames in the Zoom hearth virtually crackled away, Kye offered a last nugget of wisdom. “I was initially very intimidated by the fact that this company is AI and ML oriented, and had the impression that it would be very dry and not a place that I would belong to. Now, I realize how interdisciplinary everyone and everything is here – so, I want people to know that they can develop a whole range of software engineering skills here.”

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