Coffee Chat with Jure Leskovec

Jure Leskovec, Associate Professor of Computer Science and Chief Scientist at Pinterest, spoke with us on Thursday, April 19 about his research in applying machine learning to network data, his advice on how to do meaningful, high-quality work efficiently, and the two questions that one should always ask before undertaking a new project. 

Professor Leskovec’s current research investigates questions of how we can leverage information and social networks in order to build machine learning models that can solve different and more difficult problems compared to traditional models trained on matrix data. Dr. Leskovec's work in this area ranges from modeling disease and properly functioning tissues as networks of proteins and their interactions to taking advantage of the vast amount of driving data collected by companies like Volkswagen. He also teaches at the graduate level about network analysis and mining massive datasets. 

Before becoming a member of the Stanford InfoLab and AI Lab, he was a postdoctoral researcher at Cornell University and a PhD student at Carnegie Mellon University. While there, he also worked on problems surrounding analysis of networks, and spoke to us about how the most important two questions to ask before taking on new work are the following: "Why should I work on this problem?" and "Why should I work on this problem now?"  

In addition to talking about his work, Jure told us about his journey as a curious, driven student in Slovenia to the United States and some of the earliest projects that he completed at that time. We really enjoyed hearing about the research questions he investigated as a secondary and university student in Slovenia, as well as his experiences as an intern at HP Labs here in Palo Alto and elsewhere. When asked about his tips for success, he stressed the importance of sleep, not "spinning constantly," and making time for leisure activities as a way of recharging. He also encouraged us to actively seek out our needs, whether that is experience, mentorship, or community. 

To learn more about Jure Leskovec, visit his website at www.stanford.edu/people/jure/index.html.

Written by Pratyusha Javangula

Coffee chat with Dr. Carla Shatz

On Wednesday March 7th, members of SymSys Society sat down to chat over coffee with Dr. Carla Shatz, Professor of Neurobiology and David Starr Jordan Director of Stanford Bio-X. The conversation dived into the intersection of computational and biological methods in approaching some of the most pertinent pressing issues of our time such as neuro-degenerative disorders and other neurological pathologies. Carla shared a great deal of intriguing insights into the exciting work that is being done at the very moment at the forefront of neurobiology, both by her lab and that of a few other research labs applying cutting-edge technologies at Stanford.

Written by Kaylie Zhu.

Humans of SymSys: Hope Schroeder

"I wanted a major that would address [these] questions, teach me to think in new ways, and also push me in terms of my technical skills. Bam!"

Hope is a junior majoring in Symbolic Systems with an Individually Designed Concentration.

Introduce yourself: I’m Hope! I like travel, skiing, ice skating, yoga, lakes, art, and VR.

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

Symbolic Systems was on my radar coming into Stanford, but as someone with eclectic interests, I tried a lot of things before deciding on SymSys. Along the way, I was continually drawn to the questions that SymSys forces us to consider. I wanted a major that would address these questions, teach me to think in new ways, and also push me in terms of my technical skills. Bam!

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

Bio150 with Robert Sapolsky, to give an unoriginal answer. I recommend this class to SymSysters and non-SymSysters alike. It will make you think deeply about our bodies and minds as biological agents, and the degree to which biology affects how we interact with each other and our earth. It makes our philosophical discussions in SymSys seem even more pressing.

Fun fact-- Dr. Sapolsky played piano for the musicals I was in during elementary school because his kids went to my school. It was funny to get to Stanford and be utterly blown away by his deep expertise, command of the classroom, and skill at giving an engaging lecture. “Incredible individual” does not even begin to cover it.

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

Yep, I’ve been working for the Clayman Institute for Gender Research since before I came to Stanford! Gender equality might not seem like a topic that meshes easily with SymSys, but over time, the overlap has emerged. I’ve done linguistic analysis of performance evaluations in tech companies to see how the language differs in describing the performance of men and women for a few years now. This year, Chris Potts is advising me in developing a computational tool to do a quantitative analysis of these evaluations to complement the qualitative work we usually do. It’s a perfect marriage of my interests, and SymSys allowed me to see a new way of studying this societal problem.

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

When choosing how to spend your time at Stanford in the summer, think about what excites you. Are you applying for things because they’re what you’re supposed to want, or are they what you actually want? The world is huge and exciting, and Stanford has the resources to help you pursue your wildest dreams. Consider making those a reality! Get a grant for research (some even let you travel!), start something, or even take time off from Stanford if you need it, either on your own or in a study abroad program.

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

One topic I’ve been thinking about is the general idea of abstraction versus instantiation. The models we make in SymSys are abstractions-- we abstract things that are experienced at the individual level into patterns. Minds, both virtual and real, are instantiations of abstractions. When we abstract experiences at scale, what is lost? How good of an abstracted model of experience can we hope to get? Where is the limit to what we can understand about human experience through patterns?

As a diverse major with a lot of flexibility, many students struggle to find continuity across their coursework. (How) do you address this?

Personally, I’ve  never felt more continuity than I do now. I’m concurrently enrolled in Ling130A, CS124, and CS103. It’s exciting to feel like learning logic has paid off in every one of those classes. They’re all speaking the same language in different ways.

During some of my earlier quarters with class combinations like Math51 + Bio150 or CS106A + Psych50, it was harder to feel that continuity. Maybe if I had gotten involved in SymSys society earlier, I’d have felt more overlap in the conversations I’d have been able to have with my peers.

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

I’ve been interested in virtual reality for a couple years now. We should be talking about it more in SymSys, because it’s changing how we talk about and integrate models of reality into our conception of what reality is.

Last year, David Chalmers gave a fascinating talk about the philosophy of VR, and it inspired me to think about VR and AI in a similar continuity as we think about minds systematically interacting with worlds in Symbolic Systems. Shouldn’t we be studying how virtual minds interact with virtual worlds as part of how we investigate how real and mechanical minds interact with real worlds?

Shameless plug: join Rabbit Hole VR if you’d like to learn more or get involved in VR and mixed reality at Stanford!

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

Coffee chat with Tadashi Tokieda

Professor Tadashi Tokieda joined us over coffee and tea last week. Professor Tokieda was previously the Director of Studies in Mathematics at Trinity Hall, Cambridge, and is currently a Professor of Mathematics at Stanford. He will be teaching Math 53: Ordinary Differential Equations with Linear Algebra in the spring. Professor Tokieda began by describing his transition from being a painter in Japan to a classical philologist in France. Despite his love for linguistic quirks -- he casually explained to us the geographical origin of the word “apricot”, which happens to have the same root as the word “precocious”, Professor Tokieda was one day inspired by a biography of a Russian physicist, Lev Landau, to pursue mathematics. He then learned basic math from a Russian textbook (requiring him to learn math and Russian at the same time) and enrolled in a math degree at Oxford (requiring him to learn English over the course of a few months). At the end of our chat, Professor Tokieda emphasized the important distinction between “doing what you really like” and “doing things that you are influenced to think that you ought to like”. And when asked what the most important topic in today’s mathematics is, Professor Tokieda suggested that the question is not a valid one. To him, “mathematical topics are like friends” that he has accumulated over the years -- he possibly could not choose the most important one!

Written by Megumi Sano.

Coffee Chat with Mehran Sahami

This past Monday, SymSys Society members sat down with Professor Mehran Sahami of the Computer Science department, to chat over coffee. The conversation ranged from discussing the intersection of CS and Education to reminiscing on his experience taking CS229 (when there were less than 10 students in the class!). Excitingly, Mehran will be teaming up with professors in the political science department to teach a course on computer science and ethics next year. If you're interested in issues like bias in decision making algorithms, keep an eye out for that!