Humans of Symsys: Antonio Aguilar

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“This is becoming the theme of my blog post, but I’d advise students be intentional about who they are modeling, about developing relationships with the right models and mentors, and about asking oneself when it is best to go in a wholly new direction.”

Antonio graduated in 2018 and is a current Advising Fellow for the major, so he helps prospective and current SymSys students navigate their journey at Stanford. His office hours for Fall 2018 are Tuesday 9:30am-1:20pm in 460-040A.

What drew you to SymSys?

When I was growing up, I wanted to be a civil engineer like my grandfather. He built roads and bridges for the Costa Rican government for years. However, I got really into philosophy in high school. I started a weekly reading group which introduced me to the joy of discussing ideas between friends. I wondered then if I really should be pursuing a day job that was so separate from the intellectual life I wanted.

Before coming to Admit Weekend, I came across SLE and SymSys. I thought this Stanford combination sounded like the ideal liberal arts education for the 21st century, the perfect blend between technical disciplines and the human questions that really interested me. I looked through the SymSys core and realized that I would take all of those classes even if I didn’t need to fulfill the requirements of a major. SLE even knocked down Philosophical Foundations 1!

As my Admit Weekend came to a close, we ProFros got to hear from Srinija Srinivasan, one of Yahoo’s first employees and a SymSys alum. I remember being so impressed by her eloquence and the way she spoke about her own education that I practically locked down my decision right then and there.

Why did you pick your current concentration? Why did you decide to become an AF?

Many times I have made significant decision in my life, it has been because of role models. That is, I’ve seen something in someone else that has made me say “I want to be a bit like that”—Ms Srinivasan, for example.

So the answers to these two questions are actually the same. I attended the SymSys Student-Alumni-Faculty reunion during homecoming of my freshman year. (I highly recommend these, they are really fun!) There I talked to a junior called Cristian, who was an AF in the Artificial Intelligence concentration. The long conversation I had with him, sophomore Gerardo and alum Aman dispelled any doubts I might have had about SymSys and made me look further into AI for myself.

But just as important as that intellectual component was looking at someone who was joyful, Latin American, involved, excited about his work, and setting my nav roughly in that direction. I declared AI with Cristian, figuring I could change my direction later. It has taken more time, more models (people like Jure Leskovec in the CS department) and a 13th quarter to really commit to that path, but I am really happy for it. Getting involved in the SymSys community and working for it as an AF has been a phenomenal part of the process which was kickstarted that afternoon.

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

It’s hard to choose! The list of non-SymSys-related classes I’ve taken is quite a bit smaller. The answer to that question is likely Phil 81: Philosophy and Literature. I think that class brings up essential questions about what makes a well lived life in relationship to art. In the realm of SymSys, I’ve yet to fully replicate the levels of flow and deep work I experienced while coding for CS106A or working through problem sets for Stats 116. The AI classes that I’m taking this quarter are giving me that feeling again, which makes me enormously excited.

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

I came to Stanford as an international student from Costa Rica. Especially during my first years here, I looked at others around me to model how to choose my classes, much to work on them, how to spend my spare time. I see now that I didn’t always make the right choices for my particular circumstances and qualities and aspirations. This is becoming the theme of my blog post, but I’d advise students be intentional about who they are modeling, about developing relationships with the right models and mentors, and about asking oneself when it is best to go in a wholly new direction.

What (loosely) SymSys-related topic are you excited about right now?

Other than the AI stuff I’m studying and working on, I’m really excited that more people are becoming aware that technology often does not help us live the kind of lives that we truly want to live. I’m interested in better business models and design frameworks that help realign our technology with our humanity. I’m also invested in minimalism as a practical philosophy that seeks to bring our focus to what is truly important to us and brings us value.

What other groups or activities are you involved with at Stanford?

I was very involved in the Sigma Phi Epsilon community, especially with the project to house a part of our members in a multi-organization, multi-gender space. I have also been an active member of the Catholic Community at Stanford. Things change as a commuter, but I’m particularly excited to help kickstart the Thomistic Institute, a new offshoot of the Catholic Community that focuses on our intellectual tradition and the philosophy of Thomas Aquinas.

Humans of SymSys: Allen Nie

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Allen Nie (MS '17) works on NLP and AI research with Professor James Zou in the Biomedical Data Science department at the Stanford School of Medicine. 

What drew you to the SymSys master's program? Why did you pick SymSys as opposed to other programs or related fields?

I've always been very interested in interdisciplinary fields. SymSys (unlike other cognitive science programs) has a strong focus on computation. It studies artificial intelligence and its surrounding fields without the need to focus on a particular approach (such as a cognitive science approach, symbolic/logic approach, statistical approach, etc.). It allows the students to understand the merits of all approaches and delve into the one they can believe in. In the age of artificial intelligence, I would like to see Symbolic Systems grow and become an actual department or institution with full-time researchers studying the mechanisms and fundamentals of intelligent systems and their behaviors.

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

LING 130A with Chris Potts and EE 376A with David Tse. LING 130A focuses on understanding language using tools of logic and the later one focused on probabilistic systems and information theory.

Both classes teach a tool that allows students to understand aspects of the world. LING 130A teaches logic and EE 376A teaches probabilistic operators such as entropy and mutual information. Without getting into a philosophical abyss that is epistemology, the human scientific exploration focuses on featurizing the world, using models (sometimes our own brain) to find meaningful signals, discretizing the finding into digestible patterns or rules or “discoveries”, and call it knowledge. In order to study a field of interest, an analytical tool must be acquired. Both classes provide tools that allow us to model our hypotheses of the world and verify them.

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

Find a field that you'd like to study. It can be music, language, cognition, nervous systems, molecules, networks of humans, and think about the best tool you can find to study them.

What's something cool you recently worked on? 

Universal sentence encoding, building interpretable NLP models, and ML safety where the model has the chance to abstain/reject when it is not confident about its decision. 

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

I've been working on universal sentence representation and I'm applying these representations to low-resource domains (a problem with very limited training data) such as analyzing clinical text. My other area of interest is to make NLP models more interpretable. In the past decades, we haven't had models that can truly match human-level performance on language tasks. But now we do. Is there hidden knowledge that we can learn from these high-performing predictive models? This is what statisticians have been doing in the past -- using a predictive model to conduct feature selection, and a clinician will jump out and spit out “definitive proof" about wine drinking and living long age. With the seriousness of correlation and causation aside, which may very well be part of a larger philosophical debate, are we able to discover valuable patterns on language from a high-performing predictive model with minimal inductive biases? Would those patterns contradict current linguistic theories? Sam Bowman (a Linguistics professor at NYU) has published some amazing work on this topic last summer.

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

I don't think SymSys program provides continuity. Instead, each student needs to define the continuity from their own interests. If you are interested in language, you can follow the path of studying language and acquiring various tools, but you need to find the common threads among the classes you take. A professor in a statistics class won't tell you that Andrey Markov was thinking about fitting the vowels and consonants in Pushkin's poetry after he developed Markov Chain, or Charles Spearman, who invented Spearman correlation, is a highly revered Psychologist and regarded his own statistics work as secondary to his quests on Psychology (human intelligence). In order to find continuity in your work, you should first find out your personal interest and construct your curriculum and research around it.

If you could go back in time and be a Stanford student again, what would you have done differently and why?

There have been classes that I'm very interested in but was not able to take, such as MKTG 355: Designing for Happiness or CS 181: Computers, Ethics, and Public Policy — especially considering the Uber incident, who is to blame and to punish when a software that seemingly possesses agency kills someone? And since machine learning is marching into healthcare, is a line such as “our system on average only makes mistakes and kills 1000 people (less than 5000 people in a human-based setting) in your hospital each year” defendable in the public scrutiny?  I imagine I might have gotten an answer if I took CS 181 :)  

Humans of SymSys: Sonia Targ

"SymSys and other interdisciplinary programs teach you to become comfortable analyzing phenomena at many different levels, which overall enriches your understanding of any field."

Sonia Targ did her B.S. in Mathematical and Computational Science, with a secondary major in Symbolic Systems. She's currently finishing up her coterminal M.S. in Bioengineering, and then she’ll be off to med school at UCSF! 

What drew you to the SymSys major, and what is your concentration? 

I was initially drawn to the SymSys major because it aligned with my interests in linguistics, philosophy, and neuroscience. I thought it was super cool that there was a single major that touched on so many of my favorite topics. I decided to do my concentration in the neurosciences since I find the neurobiological mechanisms that give rise to behavior and experience incredibly fascinating. 

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

I really liked LINGUIST 130A: Introduction to Semantics and Pragmatics. It was fun to apply set theory and logic in a context outside of mathematics or computer science. I enjoyed learning how language works from theoretical and practical perspectives. I also liked that many of the ideas tied in with topics I had learned in philosophy (like “possible worlds”), making those concepts seem more applicable.

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

I’d encourage younger students to plan out their degree more than I did! Have some goals in mind about what types of knowledge and skills you’d like to come away with, and try to build your academic plan around that. Sometimes students in Symbolic Systems say they feel like they did 5 minors, rather than a major, so if that seems like a problem to you, maybe choose a specific topic in your SymSys concentration in which to develop your expertise. 

What's something cool you recently worked on? 

I recently took the class BIOE 273: Biodesign for Mobile Health, a project-based course at the intersection of technology, healthcare, and entrepreneurship. My team decided to tackle the issue of post-surgical wound infections by developing a wearable wound sensor linked to a mobile app that alerts patients and doctors to problems with wound healing. While I had done plenty of laboratory research and engineering before this class, this course exposed me to aspects of product design and marketing, which form a large part of bringing impactful products to the public. My team won funding from the Stanford Byers Center for Biodesign to continue our project, and Nokia Bell Labs has expressed interest in partnering with us!

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

As I finish my M.S. in BioE and begin medical school, I hope to continue learning about the intersection of STEM and the lived human experience. To this end, during undergrad, I studied Medical Anthropology at Oxford University through BOSP, which complemented my SymSys and BioE background well. I got to think deeply about topics ranging from the medical definition of death, the ethics of organ transplantation, and how culture wildly affects the experience and pathology of disease. I think that my diverse academic background will help me to tackle the various problems I will face as a physician, some technical and some distinctly human.  

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

I never really found continuity across my coursework in the way you would in a more traditional major. However, I noticed the themes of reductionism (explaining complex phenomena by breaking them down to their fundamental units) and emergentism (understanding how parts of a whole interact to give rise to new properties) appeared over and over again throughout my coursework. SymSys and other interdisciplinary programs teach you to become comfortable analyzing phenomena at many different levels, which overall enriches your understanding of any field. For example, I learned to analyze the brain from the perspectives of anthropology, philosophy, neurobiology, engineering, and computing. 

What else are you involved in at Stanford? 

At Stanford, I have been involved with various organizations, including Stanford Students in Biodesign, Stanford Sympony Orchestra, and Taiwanese Cultural Society. I also write poetry in my spare time and have been published in Leland Quarterly and Z Publishing House’s anthology California’s Best Emerging Poets. I enjoyed promoting wellness on campus as a Peer Health Educator during my junior year. I started Stanford Music + Mentorship, a club that does music education outreach in East Palo Alto. As for research, I’ve done work on projects related to regenerative medicine and cognitive neuroscience in the Helms and Parvizi labs, respectively. I also feel lucky that I’ve gotten a chance to pursue my passion for teaching by being a TA for classes in Chemistry, Symbolic Systems, and Neurobiology.  

California Cognitive Science Conference 2018

On Saturday April 28, 10 Stanford students rolled out to Berkeley to attend the 10th Annual California Cognitive Science Conference. Hosted every year by UC Berkeley’s Cognitive Science Student Association, this conference invites undergraduates in the Bay Area to hear talks from researchers in the field and to present their own research during the poster session. This year’s two keynote speakers were the renowned neuroscientist, VS Ramachandran, who talked about the phantom limb, synesthesia, and xenomelia, and the author of Theoretical Neuroscience, Peter Dayan, who presented his view on model-based versus model-free decision making. We also had Hyo Gweon, Professor of Psychology and PI of the Social Learning Lab at Stanford as one of the focus talk speakers as well as other influencing researchers such as Lera Boroditsky. The topics of the focus talks ranged from brain machine interfaces to cognitive development to word embeddings.

 

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However, it was not just the talks that we found inspiring. The CalCogSci Conference is a wonderful place to meet new people who share your own interests. We met with Professor Paul Li who teaches Berkeley’s introductory cognitive science class and had dinner with Professor Zachary Pardos who works at the intersection of informational science and education. He uses vector space to predict what course a student should take next based on their past enrollment sequence. We talked about AI, art, and education while eating spicy Indian food. Last but not least, congrats to Steve Rathje, a senior in psychology who presented his research in the Stanford Mind and Body Lab and was presented the People’s Choice Award given to the best poster of the year!

Written by Megumi Sano

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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

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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

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"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

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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!

Humans of SymSys: Paul Gregg

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"Get a Master's if you want to play with magma."

Paul is a recent grad who got his undergraduate degree in Symbolic Systems with a concentration in Decision Making and Rationality. 

Introduce yourself: I graduated in 2017, have since been taking really great "gap" time, and am now looking to settle into a job. Some of my fondest memories at Stanford were made with Fleet Street, Camp Kesem, my quarter with BOSP Australia, and being an RA in Roble. I love making music and running around outside (ocean, mountains, you name it)!

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

I've always considered myself a generalist, and throughout college my interests were always pretty varied and hard to narrow down. Freshman and sophomore year I tried to pick classes based purely on interest, and when I looked back after a few quarters, my transcript screamed SymSys. I guess I chose Symsys over related majors because I wanted a sense of breadth/a "liberal arts" education, but also liked the sense of cohesion Symsys offered.

What is your concentration and why did you choose it?

I concentrated in Decision Making & Rationality! I started off in Learning, because I've always loved working with kids and have been fascinated by their brains, but changed course once I discovered that the "other" learning — machine — was not my passion. I chose DM&R because I felt like I could spend another 4 years at Stanford taking just classes from the concentration list. I think the concentration is so applicable to life: it helped me to understand myself and other people as decision-making agents from multiple points of view. After all, life is just a series of decisions!

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

I think Moral and Character Education was my favorite Symsys class I took. I took it senior year, and it really clicked as something I genuinely loved and found really important, not just a class I felt like I had to take for "skills." Some other contenders are CS 103, Johan Ugander's networks class, Brian Knutson's neuroeconomics class, POLISCI 356A, and the developmental psych Bing observation lab.

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

Don't treat college as just laying the groundwork for your career. Life is about finding balance between working towards long-term goals and enjoying the now. At Stanford, it's really easy to be poorly balanced. Sleep more. Don't let self-care be a productivity tool. Make time to do nothing with your friends -- that's when you create the memories that'll last. You've already shown that you have the brains and the dedication to achieve; those won't go away overnight. Your chances at the many other rich and meaningful experiences that only college offers will. And support your friends at it too! It's tough to fight the duck syndrome alone, but if you encourage others, they'll find the courage to support you too.

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

I'd say there are multiple flavors of continuity. Say I love to dig. I could pick up a shovel one day and dig one continuous hole through all of earth's layers until I hit the middle and finally figure out what's hiding down there. Or, I could dig a bunch of small holes all over the place and discover "whoa! There's dirt here, there, AND over there. They're all kinda different, this one's gravelly and that one's loamy, but they're all dirt! Who knew?" Both are pretty neat, and I think both offer some version of continuity. Symsys really only offers the latter kind. Get a Master's if you want to play with magma.

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

Well, this prompt reminded me that I haven't checked in on the whole full-body transplant saga in a while. I was bummed to google it and find out it (maybe?) happened and sorta fizzled out. I think the experiment has fascinating repercussions for the whole "who am I, really" philosophy of mind debate. Also, as trite as it is, I think the impending age of AI and automation of the workforce is really important for everyone to think and talk about!

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

 

Coffee Chat with Josiah Ober

Josiah Ober, Mitsotakis Tsakopoulos-Kounalakis Professor in Honor of Constantine Mitsotakis Professor of Political Science and Classics, about his work on political theory and the lessons that modern society can learn from the practices of the ancient Greek world. 

Professor Ober’s current research investigates the conditions which must be met in order for a democracy to rise and thrive, with specific reference to Greco-Roman antiquity. Over the course of the afternoon, he gave us his take on the "rational ignorance" problem in a democracy as it scales up to include hundreds of millions of citizens (as is the case in the United States), if a democracy should selectively weight the voices of citizens who would openly use their voice towards a hateful end, and what problems arise when liberalism is intersected with democracy. 

Before becoming a professor at Stanford, Professor Ober was a Professor of Politics and Classics at Princeton University, prior to which he was a Professor of History and Philosophy at Montana State University. 

When asked about if he finds any troublesome aspects of the United States' democracy today compared to those of the ancient Greek world, Dr. Ober said that he certainly finds some. However, he clarified that in assessing the state of our democracy, it is imperative not to get bogged down in the daily news cycle. He also mentioned that it is altogether too easy to drive oneself crazy trying to take in every opinion and "hot take" available via news outlets and social media, to the point of unproductivity. 

Towards the end of the afternoon the conversation took a turn towards questions related to the difference between applied and theoretical political science in terms of what can be learned by studying each subfield. In addition, we spoke with Dr. Ober about how politics interacts with scientific discovery, and if there are any answers to be found in studying the ancient Greek world and its reconciliation of new science with new political systems. 

To learn more about Josiah Ober, visit his profile on the Stanford Classics Department Website at https://classics.stanford.edu/people/josiah-ober


Written by Pratyusha Javangula

Humans of SymSys: Devangi Vivrekar

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"The systems we study, whether they are languages, computers, or minds, are all different layers of the way we understand the world, and I like reflecting on which part of the biological or technical stack I’m learning about..."

Devangi is a Symbolic Systems coterm who got her undergraduate degree in Physics. 

Introduce yourself: Hi! My name is Devangi and I’m a SymSys coterm. I recently finished my undergrad degree in Physics with a notation in Science Communication. I’m currently researching the theory behind persuasive design techniques under my advisor, James Landay. I’m also working with Paul Fuoss at SLAC to understand the user experience of scientists conducting experiments using the LCLS x-ray laser. I like solving problems using technology, studying how interfaces affect cognition, and attempting to understand the universe from first principles.

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

I’ve always been a very interdisciplinary person, and as an undergrad, I naturally gravitated towards classes in over fifteen departments on campus. SymSys was the major that best fit the classes that I would have taken anyway, which is how I knew it would be a good fit!

What is your concentration and why did you choose it?

Although I don’t have an official concentration, most of my SymSys classes have been related to human-computer interaction. I chose to study this field because I wanted to understand how minds and machines complement and affect each other, and how they can work together synergistically to create positive change at both an individual and societal level.

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

My favorite SymSys-related class so far has been SymSys 115: Critique of Technology! It was an amazing seminar taught by Damon Horowitz, who is both a philosopher and a technologist. We read essays ranging from Aristotle to Heidegger in order to understand the various definitions of technology, the line between the natural world and the humanmade, and the ways our minds “enframe” technology. It was a great way to step back and look at some of the larger questions about the way technology is embedded into our lives.

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

Yes! I’m interested in how social media websites often manipulate and persuade us to do things they want (click this! watch this!) by benefitting from some of our cognitive and social biases. In my HCI research class, we wanted to see whether whether revealing to people in real time the little ways they were being manipulated by Facebook could do a better job teaching them about persuasive design techniques than traditional teaching methods. We built a Google Chrome extension that annotated people’s Facebook feeds to point out these manipulations, and found that people using the extension had significantly better transfer knowledge about persuasive design techniques.  

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

Let yourself take whatever courses really pique your interest even if you can’t see how they all relate right now. Looking back, you will definitely see a way they connect and your diverse background will actually be an asset for whatever you choose to work on next!

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

One of my underlying interests since high school has been the study of consciousness. I want to learn more about phenomenology and interdisciplinary approaches to tackling things like the hard problem of consciousness: why is the “what-it’s-like”-ness of experience the way it is?

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

I’ve tried to embrace the eclectic nature of our coursework and trust that meaning will eventually emerge. The systems we study, whether they are languages, computers, or minds, are all different layers of the way we understand the world, and I like reflecting on which part of the biological or technical stack I’m learning about.

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

I’m really excited about the ethics of technology design. There is an important movement gaining traction in Silicon Valley right now regarding the ethical responsibility that large, monopolistic mass consumer websites have towards their users. The attention economy incentivizes such companies to capture the most eyeballs for the longest time, which leads them to use techniques that “race to the bottom of the brainstem,” as people like Tristan Harris have put it. How might we encourage the designers of these technologies to be more mindful of their user’s attention, intentions, and cognitive resources?

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

Coffee Chat with Anthony Wagner

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Psychology professor Anthony Wagner chatted with us over coffee last Friday. Professor Wagner is the PI of the Stanford Memory Laboratory and teaches several courses on memory, including Psych 45: Learning and Memory. 

Wagner discussed how deciding and changing one's focus in grad school relates to the idea of "exploration vs exploitation," and how he decided research in memory satisfied his curiosity early in his career. He also discussed the technology he uses in his research, which includes imaging techniques such as fMRI and computational approaches such as machine learning. He discussed how neuroscience can be applied in legal systems, such as being an expert witness in court cases. 

When asked for tips on improving memory, professor Wagner emphasized the importance of recall and practice. Often, the pressures of school can led to us cramming for exams, which leads to good short term performance. However, spaced repetition is key for long-term retention. Wagner hoped that psychologists and educators could work together to improve students' learning and incorporating techniques like spaced repetition into schools. 

Written by Lucy Li.

Humans of SymSys: Andrew McCabe

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"Start going through midlife (aka mid college) crises as early as possible. And really embrace them. The work you put into digging your way out of them will hopefully help you see new meaning in avenues and ways of thinking that you hadn't before [...] [and] try to catch yourself viewing the world as black and white..."

Andrew is studying at the Learning Design and Technology program at the Graduate School of Education. He majored in Symbolic Systems with a HCI concentration.

Introduce yourself: I'm a student in the Learning Design and Technology (LDT) program at the Graduate School of Education; I love what I do everyday. Never before have I been so happy to read what I'm being assigned in my classes, and never before have I connected on such a fundamental level to my classmates (like, mind-reading level) and material. Learning science and frameworks are definitely my jam. I was a SymSys undergrad with a concentration in Human-Computer Interaction. I spent my entire life prior to college as a student athlete balancing school with gymnastics and was on the varsity team here at Stanford for my Freshman and Sophomore year. While I'm happy to have had gymnastics be such an influential part of my life, I'm also happy to have left it behind to be able to focus on all the things it was distracting from. It was like this big distortion effect. I wanted so badly to pay attention to so many other things that felt so obviously more important but didn't have the time or energy or mental space to do it. Like, why was I at Stanford? What was I here to study? What was I going to contribute to after leaving? What do I do about my increasing suspicion that I can't solve the world's problems with tech even though everyone on my email lists is telling me I can? And of course: how was I going to pay off all my loans???? Spoiler: despite having quit gymnastics to answer these questions, I still don't know the answers. But I think that makes sense. These questions take a long time to answer and the longer I think about them, the more people I meet (like my great LDT classmates), the more I realize none of them are black and white.
 

What drew you to the SymSys major? Why did you pick SymSys as opposed to other (especially, related) majors? What was your concentration and why did you choose it?

I picked SymSys because my parents and I were always convinced I was interested in psychology growing up. Always thinking about "how people's brains work" (though it wasn't until senior that I took a class called relational sociology with Dan McFarland and realized that my psych interest was really an interest in sociology). I also found out about HCI as a field of study right before applying to college and I convinced myself that it was this amazing way to combine psychology and tech and make buku money doing it. Passion and money. It was a miracle. And then when it came down to it, SymSys just had less intense classes than the CS major and I was trying to avoid the harder engineering classes like the plague.

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

My favorite SymSys class was probably Ling 1 (Jk). I'm not sure I really had a favorite SymSys course. To be quite honest, none of them really jammed with me. I guess I just wasn't very into thinking... symbolically? The SymSys courses I took were kind of just mandatory hurdles I had to get over in order to take my HCI classes. My favorite HCI class was CS247. It was a real confidence booster that made me finally feel like I didn't have to be good at thinking computationally or symbolically(?) to have a skill set seen as valid at Stanford. Nowadays I'm still trying to figure out where I stand on the ethics of the mindsets and practices that I think HCI + design thinking can foster but, like I said before, it doesn't seem like a black or white question anymore either.

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

Following CS247 I worked in Michael Bernstein's lab with one of his PhD candidates Niloufar Salehi. She was a great mentor. Super compassionate, super supportive, and so so good at thinking critically and creatively about her work. Anyone that's interested in being more critical about the practice HCI should totally reach out to her. I think she has the critical consciousness and awareness (+ compassion) about her work that I wish we were all taught to have in our classes. Even though I don't think I was that much of a help to warrant being a co-author, I helped her write a paper detailing a crowd-work system called Huddler, which optimized familiarity of project teams.

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

Start going through midlife (aka mid college) crises as early as possible. And really embrace them. The work you put into digging your way out of them will hopefully help you see new meaning in avenues and ways of thinking that you hadn't before. Also, I think this is the third time I'm bringing this up but, try to catch yourself viewing the world as black and white, Good and Bad. I'm a person that's often really easily influenced by my friends/the people around me and their viewpoints. Especially when they're really passionate and there's deep emotion behind what they're saying. As I've started to realize, this tendency has led me to adopt beliefs and stances that I haven't thought very critically about. Case in point, I'll feel really strongly about something and then when inquisitive people start saying, "Oh, that's interesting. Tell me more about why you feel that way," I struggle to give an answer that's based on much reasoning at all. And then a lot of what I saw as reality feels much less convincing than it did before. As enlightening as they are, I'm trying to avoid those moments in life from now on.

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

None really. In undergrad I was most preoccupied with the question of why Connie Chan kept sending me emails telling me to work for X or Y AI/Machine learning start up and trying find glimpses of a world where working for one of those companies wasn't the only version of success.

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

I'd say trust in your concentration. SymSys as a major didn't mean much to me as a whole. I didn't see the application of most of the general requirements to my life or future life. But I did appreciate the focus of my concentration. And in my Senior year I finally realized that HCI wasn't the only concentration that I could have taken that probably would have felt grounding. Given my current interests, I think I could have felt just as at home and productive (if not more so) in the Learning concentration. And for some, I'm really convinced of the application of Philosophical Foundations. I'm realizing now that just being able to exercise your mind in critical and curious ways is really an essential skill not just in any pursuit but also in being a fulfilled person. And I think if you go about it right then the philosophy track and others can be really good ways of building that skill.

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

Learning! Find me on Stanford Who and ask me for my favorite readings and topics. I'd love to talk about learning science, educational philosophy, and frameworks and would be grateful to be pushed by any questions or insights you have.

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

 

Coffee chats: Peter Bailis

Peter Bailis, Assistant Professor of Computer Science, spoke with us on Thursday about his research in post-database data intensive systems, his advice on how to navigate the wide variety in the field of computer science, and the importance of incorporating feedback into the decision-making process as much as possible. 

Professor Bailis’s current research investigates questions of what the future of "big data" will look like. More specifically, Dr. Bailis' work focuses on data systems beyond databases, how companies and individuals can make better use of the vast amounts of data collected from their products, and the intersection between the rise of machine learning and the future of systems. He also teaches at the undergraduate level about database design and use in applications, and at the graduate level about database management systems and data-intensive systems through the lens of original research. 

Before becoming a member of the Stanford DAWN Project, the Future Data Systems Group, and the Stanford InfoLab, he was a graduate student at UC Berkeley. While there, he also worked on problems surrounding data management and data-intensive computing, and spoke to us about how each problem gives rise to 10 more equally compelling problems, explaining to us that he prefers a depth-first approach to choosing what problems to solve next.   

When asked about how to stay engaged in the work he does and decide when to dive into something new, Peter stressed the importance of remaining curious and designing avenues for feedback throughout one's life. He emphasized incorporating feedback facilitates better assessments over the course of your life about what's working and what's not in terms of professional, academic, or even personal trajectories.  

To learn more about Peter Bailis, visit his website at www.bailis.org.

 

Written by Pratyusha Javangula

Humans of SymSys: Sam Reamer

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"[My classes] have helped me in that they have caused me to think more deeply about the world that I live in..."

Sam is a senior majoring in SymSys with an individually-designed concentration in the Artificial Intelligence and Logic.

Why did you decide to major in SymSys over related majors such as CS, linguistics, etc.?

I took CS 106a winter quarter freshman year and really liked it, so I knew I wanted to do more programming. I was debating doing CS and found that the department had a lot of requirements I didn’t want to fulfill. I really liked cognitive science from a class I had taken at UCLA when I was in high school. I also don’t consider myself a techie or a fuzzy, I really like both, and SymSys seemed like a perfect way to blend the two. I also liked how Symsys allowed for a lot of flexibility. I was also thinking of doing CS + X, but the unit count made it such that I would have had to take pretty much all my classes toward my major, rather than leaving room for the classes I wanted to take for fun.

How do you think your SymSys background has benefited you (in your current job, in the way you approach problems, etc.)? 

I don’t really view things in terms of how they’d benefit me. I don’t know if philosophy of mind will ever benefit me in the workplace, or if human behavioral biology will ever come into play in what I do professionally, but I think that they have helped me in that they have caused me to think more deeply about the world that I live in, and they have been enjoyable experiences.

What is the ‘must take’ class in the SymSys curriculum? ('must take' can mean favorite, most rewarding, etc.)

I think the most interesting class that I’ve taken at Stanford was Human Behavioral Biology. You learn a lot of cool anecdotes, and the professor is amazing — even though the class is pretty long. It’ll make you a more interesting dinner guest.

If you could have lunch with one faculty member associated with SymSys, who would it be and why? 

I feel like Ken Taylor would be an interesting dinner guest, even though I’ve only heard one lecture by him. The reason I’m not listing Robert Sapolsky is because you shouldn’t meet celebrities. I don’t know if who he is in person could live up to his performance in lecture.

When someone asks you “what is Symbolic Systems?” how do you usually reply? 

I think it depends on your concentration. I feel like my version of SymSys is cognitive science, but with more of a focus on computer science. In general, I think that SymSys is what you make of it.

Which subfield of SymSys (e.g. CS, linguistics, psychology, philosophy) were you least familiar with before declaring? Did anything surprise you?

I kind of had an idea of what all of them were before declaring, because I had taken a lot of classes before declaring. Coming into Stanford, I didn’t really have an idea of what CS was like, so I was most surprised by how interesting and fun programming can be. I definitely think CS has the most fun coursework.

If you could go back in time and be a Stanford student again, what would you have done differently and why?

I would have realized that classes can be a lot more fulfilling than they were in high school. I think that in high school, I supplemented a lot of classes with extracurriculars, but I think that you can have a fulfilled quarter by focusing on classes. In high school I wanted to be a part of everything, but in college, I think that you can benefit by taking the time to engage with the material.

Outside of SymSys-related topics, what else are you interested in?

I’m really interested in world mythology and reality television (especially Survivor).

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

Humans of SymSys: Caroline Ho

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"What ethical issues arise when developing intelligent/autonomous systems, and how should we address them? How can we build technologies which promote human autonomy, justice, and fairness? It is my hope that SymSys will help me build both the ethical/social foundation and technical background necessary to answer them..."

Caroline is a junior majoring in SymSys with an individually-designed concentration in the Ethics of Technology.

Introduce yourself: I'm a junior majoring in SymSys with a concentration in Ethics of Technology. On campus, I serve as the exec lead of Girls Teaching Girls to Code, a co-chair of HackOverflow (WiCS exec board), a peer counselor at the Bridge, and a VR programmer at the Virtual Human Interaction Lab. In my free time, I write a satire blog on tech/CS, go out to social dance events, take long walks around campus, participate in hackathons, and yell about AI ethics. Also, I made a meme about SymSys once.

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

I really love the breadth and flexibility of the SymSys major – as someone with interests in both tech and the humanities/social sciences, I was super excited about the fact that I could learn about areas of which I had no prior knowledge (i.e., psychology, neuroscience, linguistics) while going deeper into my personal areas of interest (i.e., computer science/AI, philosophy). Also, while this wasn't really a reason I chose the major, SymSys is basically the "meta-major": you get to think about the nature of thinking! How cool is that?

What is your concentration and why did you choose it?

When I first came to Stanford, I was deeply interested in political science and ethics, and while my passions may have shifted in a more technical direction, that hasn't changed. As a result, I've developed an individually designed concentration in Ethics of Technology, which will allow me to augment my CS coursework with classes providing a more critical lens on my technical interests. Since I'm currently planning to go into the tech industry, I figure it's my responsibility to ensure the products I build and algorithms I design are beneficial for society.

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

I can't say enough good things about CS 103 – it's an incredibly well-taught course which made me fall in love with math again. Plus, you get to learn the mind-blowing philosophical/social/technological implications of the theoretical content you learn along the way. Want to know why you can never build a completely secure voting machine or whether we can prove all truths to be true? To find the answers to these questions (and more!), take CS 103.

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

This year, I started working for the Virtual Human Interaction Lab through the Virtual Reality Intensive Training Seminar (VRITS), which has been a very "SymSys" experience since the lab combines elements of CS and psychology in its research. Currently, I'm programming the environment for a study on how various VR experiences impact people's emotions.

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

Explore as much as you can, and don't be afraid to dive into subjects you know nothing about! While this definitely relates to SymSys, you should take it more broadly as well – there's so many amazing fields of study at Stanford that probably weren't offered at your high school, so why limit yourself to the ones you're familiar with?

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

As an aspiring AI ethicist and engineer, I'm interested in a couple questions in particular: 1) What ethical issues arise when developing intelligent/autonomous systems, and how should we address them? 2) How can we build technologies which promote human autonomy, justice, and fairness? It is my hope that SymSys will help me build both the ethical/social foundation and technical background necessary to answer them.


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

Humans of SymSys: Matthew Libby

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"I'm really interested in the ways that emerging tech, the human brain, and art can interact. Tech has already revolutionized everything from film to music to sculpture -- but what happens when those human-computer artistic teams become more computer than human?"

Matthew is a recent grad who majored in Symbolic Systems with a concentration in Cognitive Science and a strong interest in the arts.

Introduce yourself: I graduated from Stanford in June, and am now living in Los Angeles. On campus, I acted and directed for Shakes, worked on Gaieties, was a tour guide, and RA'ed in Burbank. These days, I'm pursuing a career in the film industry.

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

I've always been someone who loved both STEM and the humanities. Though I've wanted to work in the arts professionally as long as I can remember, I loved taking math classes and others that are more analytic in nature. I knew I wanted to continue that at Stanford -- and in SymSys I found a program that combined subjects I was interested in, in ways that I knew would satiate my intellectual curiosity.

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

Human Behavioral Biology with Robert Sapolsky was my favorite class I took at Stanford, period. Not only was the material fascinating, but it exemplified the interdisciplinary mindset that made me enjoy SymSys so much: in that class, looking at a subject from multiple points of view gave me a clearer sense of the subject than looking at it from just one would have.

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

I never did research in the SymSys department, but my senior year I participated in the Arts Institute's Honors in the Arts program, where I wrote a full-length stage play for my thesis. The play was about artificial intelligence, namely artificial creativity, and speculates a future in which we can't tell human art from machine art. I did a lot of research for the project -- mostly into Generative Adversarial Networks (GANs), which are super cool -- and my SymSys education was instrumental into creating it.

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

As my thesis might indicate, I'm really interested in the ways that emerging tech, the human brain, and art can interact. Tech has already revolutionized everything from film to music to sculpture -- but what happens when those human-computer artistic teams become more computer than human?

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

With all my newfound time post-graduation, I recently started reading Douglas Hofstadter's insane 750-page opus Gödel, Escher, Bach. It's a great SymSys supplement if you have the time to dig into it!

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

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