Coffee chats: Judith Degen

Judith Degen, Assistant Professor of Linguistics, spoke with us on Thursday about her research in psycholinguistics, semantics, and pragmatics, her advice for those interested in graduate school, and the value of “taking joy in the discovery process.” 

Professor Degen’s current research investigates questions of how speakers decide what to say when, and how listeners know exactly what they mean by “reading between the lines” over the course of a conversation. She integrates computational modeling approaches with methods in psycholinguistics in order to form a more complete picture of how listeners make pragmatic inferences both correctly and quickly. She also teaches at both the graduate and undergraduate level about the theory and methods of psycholinguistics. 

Before becoming the director of the interActive Language Processing Lab at Stanford (ALPS), she was a postdoctoral researcher in Noah Goodman’s CoCoLab at Stanford. She has lived all over the world, from South America to Europe to upstate New York, and stressed to us the importance of taking opportunities to study and live abroad. 

When asked about what tips she had for surviving graduate school, Degen shared stories of her time as a graduate student at the University of Rochester, where she made lifelong friends and learned how to become comfortable with being wrong. She also talked about celebrating the small victories and how it is inadvisable to go to graduate school just for the sake of getting a doctorate. 

Towards the end of the afternoon the conversation took a turn towards questions related to how to choose a major of study, the serendipity that plays a part in that decision, and the necessity of taking advantage of the large variety of classes that Stanford has to offer. Specifically, Dr. Degen emphasized that while technical skill is extremely valuable, in order to build a more well-rounded world view, an education in the humanities is indispensable. 

Written by Pratyusha Javangula

Humans of SymSys: Beata Petkowa

"There are people who thrive in their fields of expertise, but find it challenging to think cross-contextually. I am the opposite. I was born in a multicultural and multilingual family, moreover raised in 5 different countries and exposed to 5 different educational systems. It felt thus natural for me to chose an interdisciplinary major like Symbolic Systems..."

Beata is a junior majoring in Symbolic Systems with an individually-designed concentration in the behavioral aspects of HCI and tech-related entrepreneurship.  

Introduce yourself: My name is Polish, my last name is Bulgarian, but I consider myself to be a rather culturally ambiguous blend. Majoring in SymSys with a self-designed concentration and minoring in Modern Art History under the awe-inspiring leadership of Alexander Nemerov. I am also working for the Stanford Technology Ventures Program on how to make their entrepreneurship courses and events more relatable to a wider spectrum of students.

What drew you to the SymSys major? Why did you pick SymSys as opposed to other (especially, related) majors?

Quite frankly, I am perfectly incapable of studying just one thing. There are people who thrive in their fields of expertise, but find it challenging to think cross-contextually. I am the opposite. I was born in a multicultural and multilingual family, moreover raised in 5 different countries and exposed to 5 different educational systems. It felt thus natural for me to chose an interdisciplinary major like Symbolic Systems and fulfill my interest in future technologies from multiple perspectives, but also belay my academic attempts with sufficient rigor.

What is your concentration and why did you choose it?

In order to escape higher level CS classes and get myself closer to what I felt truly passionate about, I decided to grab fate by its balls and self-design my concentration. I am currently tailoring it towards the behavioral aspects of Human Computer Interaction and combining it with the study of tech-related entrepreneurship. So if I ever earn the honor of becoming a true Palo Alto Mom, I'll use these insights to ponder less on the choice between Blue Bottle versus Soul Cycle, but more on the question of how to transform the Silicon Valley so that it addresses truly global problems.

What’s your favorite SymSys-related class that you’ve taken so far?

If forced to pick one class, I'd say Phil1 with Nadeem Hussain. It was a terrific introduction to Philosophy and I think that's been mostly thanks to Nadeem. Whether we considered arguments for the existence of God or argued about the body-mind problem, he would make the discussion extremely logical to follow and also exceptionally engaging.

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

Just do your thing. Absorb new ways of thinking and doing, but never lose track of what makes you unique. Work on communicating your truth, so that without major compromises, you can let others believe in whatever you're trying to achieve. And if you don't know what that is yet, try the opposite of freaking out. Chill. If it's not good yet, it's not the end.

What underlying questions and issues do you hope to tackle/learn more about through SymSys?

I'm looking forward to acquiring more intellectual frameworks and practical skillsets to tackle the issue of how to humanize technology without dehumanizing ourselves.

What’s the coolest (loosely) SymSys-related topic that you’re excited about right now?

I am really curious how the application of machine learning to widely accessible devices like smartphones or home assistants will unfold for us. It's already been a while since fields like vision recognition or natural language processing have been enriched by processes underlying artificial intelligence. But the the past few years were quite different in the sense that deep learning mechanisms have slipped into our everyday lives and way more personalized contexts. And it makes me wonder. Not only about how AI will keep adapting to our token bedrooms, but also how we as humans will continue to adapt to only more complex interactions with our computer counterparts.

Beata is one of many profiles featuring selected alumni, undergraduates and graduates who are involved in the Symbolic Systems community.

Coffee chats: Jeannette Bohg

Jeannette Bohg, Assistant Professor of Robotics, chatted with us on Friday about her research, her advice for aspiring academics, and what keeps her going in her work as a professor.

Professor Bohg’s current research focuses on perception for autonomous robotic manipulation and grasping. Although she just arrived at Stanford two months ago, she is already fond of the collaborative culture she sees in the computer science department, as well as in the rest of the School of Engineering. She says she has been an academic “her whole life,” so although she has considered working in industry, she prefers the excitement of figuring out how things work by implementing the underlying principles on robots rather than building a robot that works for a specific task.

For those who are considering pursuing a career in academia, Bohg described the differences in titles such as “Assistant Professor,” “Associate Professor,” and “Lecturer.” She talked about her day-to-day life as an assistant professor and how her daily work might differ compared to that of, say, a grad student.

Bohg stressed the importance of keeping an multidisciplinary perspective throughout one’s academic journey. She studied computer science as an undergrad, but she took a detour for her master’s to explore the intersection of art and technology, because she was always interested in art but did not study it previously due to financial considerations. Bohg emphasized sticking with “what you like”, even when a clear path for the future does not materialize immediately. Without an intrinsic drive to learn more about what you are studying, she said, it’s really hard to excel in any field.

Written by Marika Buccholz

Coffee chats: James Landay

Our most recent faculty coffee chat was on Tuesday, November 1st, with James Landay, a computer science professor at Stanford who specializes in human-computer interaction. As the student attendees sipped their Coupa drinks, Landay began to recount his journey: “I started by stealing video games.” 

Not literally, of course; video games served as his avenue into the world of computer science. Landay continued to enter the human-computer science niche, first studying at UC Berkeley and Carnegie Mellon before serving as faculty for UC Berkeley, University of Washington, Cornell Tech, and, finally, Stanford University. 

During the engaging coffee chat (it exceeded the scheduled end by 23 minutes), Landay described his research in the Smart Primer, a story-based tutor that grows with the student, as well as the future he envisioned of designing for behavior change with interactive environments. In between, conversation shifted from research to education to speech recognition to an objective comparison of everywhere Landay has lived: Bay Area, Seattle, New York City, and Beijing. 

To learn more about James Landay, visit his website at www.landay.org.

Written by Jenny Zhi

Humans of SymSys: Blue Sheffer

“Fight off academic intimidation of others as much as you can -- it's entirely unhelpful. Learn from the brilliant peers that surround you, and befriend those who you look up to.”

Blue is a recent graduate of the Symbolic Systems Program (B.S. ’17). He concentrated in neuroscience, completed an honors thesis on brain-machine interfaces, and was an advising fellow. Here, he shares some thoughts on SymSys, research, and gives academic advice.

What drew you to the SymSys major?

Once I found out about Symbolic Systems, I didn’t really even consider any other majors. When I came to Stanford, I knew that I wanted to study neuroscience, but I also had budding interests in computer science and philosophy. Studying SymSys would allow me to study each of these fields in depth, as well as their intersections, so it was a perfect match.

What is your concentration and why did you choose it?

I chose the Neuroscience concentration because understanding how the brain processes information is at the forefront of my academic interests. The concentration puts emphasis on technical skills which are increasingly necessary for a career as a neuroscientist.

What’s your favorite SymSys-related class that you’ve taken so far?

I have many, many "favorites", but here are two:

1) Mathematical Foundations of Computing (CS 103). Depending on what you do, the material may or may not be super applicable, but Keith's quality of instruction is so unbelievably good that you should take it regardless.
3) High-level Vision: From Neurons to Deep Neural Networks (CS 431). I took this as a kind of "capstone" course my senior spring with Kalanit Grill-Spector and Dan Yamins. It was an awesome class that analyzed and compared neuroscience/deep learning approaches to vision.

Are you involved in research? If so, tell us about a project you are working on:

Yes! I currently work at the Stanford Neuroscience and Artificial Intelligence Laboratory. My project focuses on bridging sensory representations with decision making. We've built a model capable of solving complex visual tasks that reflect typical neuroscience experiments, and we are collaborating with experimentalists to compare our model to both behavioral and neural data.

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

1) Fight off academic intimidation of others as much as you can -- it's entirely unhelpful. Learn from the brilliant peers that surround you, and befriend those who you look up to.
2) Get involved in research! Even if you don't want to go to grad school/have a career in research, it's a really fun way to deepen your knowledge of a subject and be at the forefront of development in your field.

Blue is one of many profiles featuring selected alumni, undergraduates and graduates who are involved in the Symbolic Systems community.