includecs LupLab

Research shows that early CS education may help CS students perform better in college. In this episode, we explore this question via interviews with college students and college professors. Early CS education means that students would take CS classes as part of their K-12 curriculum and would therefore arrive in college with some prior knowledge. We talk to Matthew Butner, a lecturer at UC Davis who often teaches intro CS classes, and ask him what assumptions he makes about students and whether or not prior CS knowledge is important. We also talk with multiple CS majors, some who had prior CS experience before going to college and some who didn’t. This episode was produced by Saili Karkare and Joël Porquet-Lupine.

The 2020 COVID lockdown has fundamentally changed people’s lives. In this episode, we talk with students, faculty, and many other people about their experiences so far. The interviews were conducted during the Spring of 2020 and asked a wide range of people (UC Davis Chancellor, Computer Science department chair, CS students, family and friends) how the lockdown has altered their daily lives.

As the next presidential election is coming ahead, we talk with UC Davis Professor Matthew Bishop about election technology and its security. Professor Bishop is a cybersecurity expert who has helped election officials in California and across the country vet their electronic voting systems, and fix issues when he finds them.

We try to explore the question of whether artificial intelligence will love us or kill us first, during an interview with UC Davis Professor Zhou Yu. Professor Yu is an expert in the field of Natural Language Processing (NLP), leading UC Davis’ Team Gunrock to win first place in the 2018 Alexa Socialbot Grand Challenge. In the interview, we touch on the meaning of artificial intelligence, diversity and ethics in technology, how Professor Yu won the challenge, and what is the future of AI.

In our pilot episode, we talk about imposter syndrome, which is a common feeling among students, especially in computer science. Imposter syndrome is an adverse belief that one’s accomplishments are the product of luck or fraud rather than skill. This belief is unfortunately common for many students in Computer Science who doubt their talent because they don’t fit the typical cliché of the nerd who has been programming since age eight.