Coffee Chat with Charlotte Cheng '04

Charlotte Cheng majored in Symbolic Systems as an undergrad and completed her M.A. in Elementary Education at Stanford School of Education. She is currently a curriculum product manager for Wonder Workshop, where she designs curriculum and products that help teachers use educational robots in the classroom.

Eric Zelikman ‘20 wrote the following recap of the coffee chat we had with Charlotte on February 13.

We met with Charlotte Cheng and we talked about how she had gotten involved with Wonder Workshop. Using scratch-like blocks and the iPad she brought, we played with coding two models of really adorable robots. We talked about what it's like being into EdTech at Stanford; in the past, apparently nobody had heard of it, and now, a lot of niches in the field are targeted. People in the field were there for really diverse reasons, and mostly everyone was involved in a different area of the space, having been involved with organizations focused on teaching music, language learning, learning more abstractly, etc. This inspired some discussion of the value that the "jack-of-all-trades" nature of SymSys can bring to someone not working directly on the technical side, especially in a more startup environment. We discussed community outreach, and how an increasingly large company can address the needs and interests of many groups of kids. We talked about the value of user-testing and how a lot of coding-teaching tech ends up producing products targeted at boys unintentionally, because young boys and girls have very different motivations for wanting to learn to code in the first place. From that, we also discussed how useful it was to have some actual experience as a teacher, both because it helps talk with teachers and to know what won't work. We also spent some time on opportunities, highlighting how useful the d.school is, the class at Bing Nursery on child development, and a few education-focused groups on campus. At the end she suggested if anyone there was interested in interning with the company, they should reach out to her. Overall, it was a really positive experience and it was cool to see these really varied reasons for coming there to all kind of come together.

Humans of SymSys: Hang Jiang

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Hang is a first year master’s student in SymSys.

Where are you from? 

I am from Wuhan, China. Prior to Stanford, I went to Emory University located in Atlanta, GA, where I finished my BS in CS and BA in Linguistics.

What's something cool you've worked on? 

I was a summer natural language processing intern at Educational Testing Service (ETS), the organization to give standardized exams such as TOEFL and GRE. I developed a grammar error detection system based on machine and deep learning algorithms for preposition errors during my internship, which is used to assist raters in grading essays. As someone who used to be “tortured” by exams from the institute, I felt quite unreal to work there the whole time. :D 

What drew you to the SymSys MS program? 

The unique curriculum that bridges computer science and humanities really interests me. Specifically, I love the perspective that this program takes on artificial intelligence, which is more than just computation and is intrinsically interdisciplinary. 

What are some of your initial impressions of Stanford? 

A campus full of startup cultures. Definitely love the vibe here and enjoy talking to people about their plans.

What kind of research are you hoping to do here?

Natural language processing, computational linguistics, machine learning, and language learning. 

What's one piece of advice you'd like to offer to younger students?

Take fewer classes in your first quarter. I am glad that I did that and I was able to participate many activities and make new friends at Stanford. 

Humans of SymSys: Richard Kahn

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Richard is a first year master’s student in SymSys.

Where are you from? 

I grew up in Chicago and did my undergrad at Yale in Math & Philosophy. For the five years between undergrad and Stanford, I was working at Locus Analytics, an economic think tank / hedge fund / data analytics firm. Other SymSys folks have been interns there. Ask me about it!  

What's something cool you've worked on? 

My undergrad senior thesis was an argument for the Platonic existence of numbers. Not necessarily cool, but certainly out there.

What drew you to the SymSys MS program? 

It's more or less the only program of its kind that brings together all of my interests! And I figured that giving the West Coast a try made sense.

What are some of your initial impressions of Stanford? 

Besides the obvious things, it's definitely a more professional-oriented philosophy here than Yale. Professors and students alike are focused on how to make a difference in the non-academic world, which is exciting!

What kind of research are you hoping to do here?

I'd like to dip my hands into some more linguistics than I've previously done.  

What's one piece of advice you'd like to offer to younger students?

Don't ever take a course you don't want to take. If it feels bad in the first week, trust your gut. College is too short.  

Coffee Chat: Chris Potts

Chris Potts, Professor of Linguistics and Computer Science, spoke with us on Tuesday morning about his research at the intersection of semantics and pragmatics, and machine learning. We chatted about a variety of topics from the departments and faculty outside of Stanford who take a computational approach to solving problems in semantics and pragmatics to the ongoing open question of which problems to solve next.  

Professor Potts's current research investigates what insights from formal semantics and pragmatics can do to advance the state of natural language processing (NLP), and what insights from computing can do to advance the state of formal semantics and pragmatics. 

He also teaches at the undergraduate level about formal semantics and pragmatics, and at the graduate level about natural language understanding, and most recently, programming for linguists. He shared his enthusiasm for the latter class and his strong belief that anyone can be a programmer in our chat. 

Before joining the Departments of Linguistics and Computer Science and becoming the director of the Stanford Center for the Study of Language and Information, he was a graduate student at UC Santa Cruz, where his thesis focused on the logic of conventional implicatures. When asked how he decides what to delve into next, he said while it is a hard problem, he most enjoys advising his students through the completion of projects that are interesting to them.

To learn more about Chris Potts, visit his website at https://web.stanford.edu/~cgpotts/.

Written by Pratyusha Javangula

Coffee Chat: Mike Frank

Mike Frank, Associate Professor of Psychology, spoke with us on Friday about his research to do with language learning and social cognition in children, his thoughts on the ongoing debate between language as an innate faculty or one that is acquired via general-purpose learning mechanisms, and his assessment of the nature of the gap between machine learning and human cognition. 

Professor Frank's current research investigates questions of language learning in children, from a variety of perspectives ranging from word learning and its relationship to concept learning to pragmatic development and how children learn to participate in a conversation. In addition, he and his lab are collecting large datasets of children's speech in order to answer these questions. Finally, his research focuses on encouraging replication, reproducibility, and openness in the scientific community.  

He also teaches at the undergraduate level about human biology and developmental psychology, and at the graduate level about experimental methods. 

Before becoming the Principal Investigator of the Stanford Language and Cognition Lab, he was a graduate student at MIT under the tutelage of Edward Gibson. While there, he worked on a variety of problems from the development of the mental abacus in Canadian and Indian students to the native speakers of Piraha (a language with no words for numbers) to word learning as pragmatic inference. In our coffee chat, he explained that while he is glad he delved into a breadth of topics as a graduate student, he now employs a depth-first approach in order to meaningfully contribute to our understanding of the world. 

To learn more about Mike Frank, visit his website at https://web.stanford.edu/~mcfrank/.

Written by Pratyusha Javangula