Podcast Episode #4: HCI, Design, and Portfolios with Philip Guo

This article recaps our podcast episode with Philip Guo. Be sure to listen to the full podcast below or on Podbean and follow us to get notified about new episodes!

Philip Guo is an Assistant Professor of Cognitive Science at UCSD. His most recently taught classes are COGS 121: Human-Computer Interaction Portfolio Design Studio and COGS 127: Data-Driven UX/Product Design. In this podcast episode, Philip reflects on his teaching and research experiences in HCI and design thinking, and offers advice to students who are looking to build their portfolios and start side projects.

Background

Philip pursued a degree in Computer Science as an undergrad, but while his peers sought out industry positions after graduating, he was more inclined to follow a more research-centric route in academia. It was during his time in grad school when he became interested with how people interact with computers, rather than purely algorithmic work. This interest was expressed through the development of tools specifically for those doing computationally-based research, leading to the creation of Python tutor.

Philip created Python Tutor to help students visualize code by creating diagrams that they can view as their code executes. It allows programmers to “step through their code one step at a time” online, much like how a personal tutor would walk us through our code, drawing diagrams and explaining along the way. Python tutor is widely used by beginner Python classes in universities and by individuals learning on their own. Other languages are supported as well, including Java, C, and C++.

More on the differences between academia and industry, Philip talks about the trade-off between freedom and structure. With higher education, you are given more freedom to pursue your interests without necessarily needing a profitable outcome. Though of course, there is the aspect of obtaining funding for your research. It is not nearly as structured as industry where the profitable outcome is the general goal. Bigger companies have their own agendas and you are part of a team and have a specific role. Though, you also have more guidance and resources available to you. Like with all things, Philip says, deciding between academia and industry really depends on what your needs and goals are.

Side Projects & Portfolios

On the topic of starting side projects, Philip suggests finding a user that has a problem or someone who could make use of something that you create. This isn’t necessarily the same as finding a user base; it can be as simple as thinking about your friends, your parents, or just yourself. He explains that no matter how “trivial or small” you think your project may be, knowing that someone will find it useful is a great motivator to start the project.

“Just having one person use something is very magical, because it means that it actually benefits somebody, and I would just say, that’s my biggest piece of advice, just to find someone around you even if it seems very trivial or small.”

He also mentions joining an on-campus organization or lab. This can also be helpful for students who aren’t sure where to start and need a little more guidance through the process, though it may be relatively difficult under the current circumstances.

On making your own data science portfolio, Philip also suggests creating a website to showcase your work, including your class projects. The key is to have a narrative or a story showing your process and why you approached things in a certain way.

Another tip is to be curious and talk to people around you that seem to be a little bit farther down the path. Learn from what they have learned and build your network! It doesn’t need to be big.

As for his side hobbies, Philip also hosts his own podcasts where he has casual conversations with people that he finds interesting. He finds that the video is well suited for communicating information and that podcasts are a fun way to catch up with friends. It’s also a great way to learn from others and what they are interested in.

You can find Philip and his podcast at http://pgbovine.net/ or take one of his classes at UCSD!

Co-written by Zhilin Li