What’s your year, pronouns, major, and hometown?

I'm a junior, studying CS and data science, from Santa Clara, California.

Why did you choose those majors?

I came in as a stats major. That's why I joined SAAS my first semester -- I was explicitly seeking out some sort a stats club. But then I switched to data science and then I added on CS because there were some CS classes that I thought were important and helpful to know [for] doing data stuff. I think data analysts a lot of times do a lot more ‘data analyst’ stuff and some modeling, whereas for data science, in some roles, they want you to do more like ‘full stack data science,’ which could involve really everything. I just tagged on the CS major because I think there were some CS classes that I wanted to take.

Do you have a fun fact and/or hobbies and interests that you want to share?

I like doing things that make life feel like it's slowing down because I feel like life moves very fast. So I like going on walks and not really doing anything, or walking around and listening to a podcast.

Are there any particular entertainment things you're into, like books, TV, movies, music, etc.?

I don't really read. I want to read more, but my attention span is like a goldfish. I can't focus. I listen to a lot of music as background music, or I listen to a lot of simpy music when I'm sad. TV shows/movies? I enjoy watching movies. I feel like movies are fun, more so than TV shows. In a lot of TV shows, it's hard to focus because there's so much filler, whereas in a movie, there's actually something going on through the entire movie, so I enjoy that. I don't watch too many TV shows. Occasionally anime, occasionally K-dramas, Itaewon [my SAAS house]. I've watched a couple of HBO shows, like Westworld, I really liked that. But I don't watch too much TV.

What are your professional interests, and why are you interested in those fields?

This is particularly hard to answer right now because I've been going through a lot of mini crises. I think I’ve always wanted to do something related to data science as in, you have this problem that you want to solve, you have some data, how can you solve that problem? That’s a very vague way to put it, but I like that research and discovery aspect of data science. I think I enjoy that more so than the building part of software development, where you're dealing more with the technical problems that come up, rather than the connection of real world problems to translating those problems into data and translating that into a model. I feel like those barriers are more interesting to me than like, ‘Oh, how do I work with this memory constraint?’ or whatever else software engineers do. For example, you get some data, and then you're like, ‘Okay, well, where does this data come from? How can we interpret it in the context that we have right now?’ Like, I really enjoy thinking about the IA project right now. Even though I'm not actually developing for the project. [In terms of what] I just mentioned, you have all this data, what does it mean in the context of the customers? Or the patients? How do you translate that into a model? How do you make it into a feature that works well for the model while still keeping like the core information that's captured in all of these features of the patients? How can you interpret the outputs for the board of the client that we're building this product for? So I think all those problems are really interesting. So I've always wanted to do something like data science-y, which just means something in that ballpark. But I think that is also possible, not just in data science, but also in software development roles. In a startup maybe or at all engineer roles. I think building things is also fun, but primarily, I want some degree of the research part, like data, the part that I talked about.

How do you use statistics in those fields?

It's just like building models, understanding how models work, understanding and interpreting the outputs of models are.

What internship experience do you have, and how is that?

I interned at a startup this past summer. I was doing DevOps stuff on this thing called Terraform, which is infrastructure as code, which just means that you have some code representing some infrastructure, it could be AWS or setting up Kubernetes clusters or whatever. Then, you try to turn that into code that makes it easier to work with, so when you're trying to set something up, you don't have to go inside the AWS console and click a bunch of buttons, and you can lose [your place and forget] what exactly you are changing. Then, [for] version control, reverting changes is harder. So that's what Terraform takes care of. It just converts all of that infrastructure to code. What I was doing is infrastructure as code for the GitHub infrastructure. So it's like the GitHub organization, keeping track of all that in terms of this Terraform code. So when people were making new repositories, or adding a new user to this Github organization or making a new team, you want to manage like access permissions or create a new repository with some default settings, instead of having the developer learn what those settings are, what exactly the security settings that this company wants are, it's just a lot easier to create a repository through there, all of its going to be set up, privacy concerns are gonna be set up. Minimizing security issues helps with things like insurance and all that.

I think I was not really interested in DevOps type stuff before, and I didn't think I was going to be doing primarily DevOps stuff here, so I didn't particularly enjoy the Terraform aspect of it. But what I did enjoy was thinking about how to build this tool that is as easy as possible to use for other developers. So my customers were other developers. No actual consumer was going to be using this code ever. So I think, if you're building a full stack app, there's a front end developer and designers that do a lot of the UI/UX stuff, but here it’s all in code. It was trying to convince the developers to change from their prior experience, which is like creating a GitHub repository by going into github.com and creating a repository. [We wanted to] try to make it as easy as possible for them to use this Terraform tool instead. Then, all of those design considerations for user experience and reformatting everything, writing documentation, and such to make that as easy as possible, was the more fulfilling part for me, rather than actually learning about the DevOps stuff.

Do you have any other campus involvements?

I've done a couple different things. Some teaching stuff. Quite a bit of teaching stuff actually, various teaching things. Also, of course, everything that I've done in SAAS. I've also been working on this Data Discovery project, which is a branch or extension off of URAP, but specifically for data science. I guess I can start off with the teaching stuff that I've done and my journey through teaching at Berkeley. So it started in freshman summer, I didn't really know what I was gonna do over the summer, so I signed up to be an AI for CS 61B, and I really enjoyed that. I put in like a lot of time into that because I realized that I didn't understand 61B as much as I thought I did, so I had to spend a lot of time relearning a lot of stuff that maybe I just missed over or maybe I didn't learn well enough because I was too busy working on some Hilfinger project. I really enjoyed that, and I really enjoyed working with students, helping students on projects, explaining concepts to them, occasionally debugging code because it's kind of painful to read code sometimes. I think that was a really fulfilling experience, so I decided that I might be interested in joining course staff, but I first signed up for CSM in the fall, because course staff applications for 61B were already closed. But I didn't really do CSM well during my first semester. Honestly that first semester was really really difficult for me because I feel like I wasn't a very good teacher back then. I think there's a lot that you learn through the process of holding small group tutoring sessions: how you should explain certain concepts, what pace you should talk, and overall familiarity with explaining the content, not just explaining the content, but explaining the content in a way that works well for students. As Professor Adhikari likes to say, you want to have a lot of different ways of explaining things, like explaining the same concept. So I think that's also important, for example, giving a metaphor for something or explaining it very methodically, like you do this step, and this step, and this step. Also explaining the motivation behind a lot of stuff was something that I didn't have too much experience with, so I didn't think I did that well that first semester. I was also very nervous every time I taught a section. I was on the border of deciding if I wanted to do CSM again, but I ended up doing it because I thought I didn’t do that well, and I want to do better, so I did that again during the spring. I also signed up to be an AI for Data 100 because I really liked it, and I thought it was pretty important to the stuff that I was doing. I could see a lot of connections between the content and all the data science stuff I was doing in SAAS, like RP, CX, and IA. In a lot of that, you touch Data 100 [concepts] a lot. So that was interesting for me, very rewarding for me, and I think I would be better at teaching [Data 100] because I touched so much of that content very often. For example, maybe just debugging a student's Pandas code because I use Pandas so much that it's easier or explaining some of these concepts where I understand the motivation behind when you want to use one model one for the other. That helps when you're explaining things. So CSM that semester went better.

Over this past summer, I was a tutor for 61BL and Data 100. 61BL was honestly a lot of work, I had to teach like three sections a week, like quiz tutoring sections and small group tutoring sections. Data 100 was not as much work primarily because we were just grading and holding office hours, like not really teaching small group sections. I guess that's just how Data 100 formats the sections, and I think Data 100 is a lot more like practice and application heavy. For example, you just need to practice SQL, whereas in 61B, there are a lot of nuances and a lot of the different data structures that you use and the runtime for all of them. It helps to sit down and learn about those in smaller group settings. Like [for the concept of] asymptotics, hearing someone explain a problem is a lot more helpful than just sitting down and fighting the problem trying to figure it out. Whereas if you're doing something like Pandas, maybe just playing around with Pandas and Googling things until you get it may be a little more helpful.

This semester, I’m tutoring for Data 100, which is like the same thing as over the summer, which is pretty chill. What I'm doing next semester is to be determined. But I've also taught on staff for the Web Design DeCal for a little bit. That started freshman year when I took the DeCal freshman fall, I just really enjoyed it. I heard good things about it, and I thought it was really fun making websites—pretty websites. It was all front end, but it was just cool seeing how something you coded was immediately translating into your web browser. So I took that class freshman fall and then I joined staff as a TA sophomore fall, and then I was a TA again last fall. Now I'm an instructor, which is interesting because I don't want to do design or front end as a career. I think I was exploring that idea and then I realized that I just like data science stuff more. But I think it's still fun. Helping other students learn these things and seeing a lot of cool projects that students produced by the end of semester was really rewarding. It's particularly cool that in that class—maybe it's the same as Data 8—where people come from a variety of backgrounds. So some people have not a lot of confidence in their coding abilities, or they’ve never coded before, and they come in and they're like, ‘Oh wow, I was able to make this,’ which is always pretty cool to see. So that's been fun. I think what made me stay this semester and become an instructor was because I think the people are pretty cool. They're just fun to be around. That's it for teaching.

I've [also] been a part of this Data Discovery project since freshman fall. That's actually where I met Ewen. So Ewen, probably aside from you [Jackie], is probably the other person that I've known for all my semesters in college, in SAAS at least. So [Ewen] was originally one of the sub-team leads for the sub-team that I was on for one of these projects. The project is called ‘The Public Editor Project,’ and the goal is [to create] a system that tries to combat the issue of fake news by creating credibility scores for each of the articles. These credibility scores are generated through this citizen science approach, which means that people give feedback through this system for very trivial questions about articles. For example, for this tiny little highlight of the article, is there a logical fallacy here? Is this a slippery slope? Is this high confidence claim backed by evidence somewhere else in the article? So questions that can hopefully reduce as much bias as possible about the article and just about that particular sentence or that like subset of the sentence. So aggregating all of that together, creating credibility scores, like highlights that warn users when they're reading through articles, like, ‘Oh, you're reading this article, [and] these are things you want to be conscious and aware of… so you don't get influenced one way or another. The team that I joined, and now I'm the lead for this sub-team, is the user monitoring, which means that you have all these users who are answering these questions, and you want to make sure they're answering them accurately. They're not inserting their own bias about the article, about the author, about the publication onto the answers that they give. So [we’re] trying to track how far off they are from the average or consensus answer from everyone else, and then we increase or reduce the weight of their opinion accordingly. If they give really bad answers all the time or they're very, very far off from what the rest of the group decides is like the correct answer, then of course, we want to weigh them a little bit less. That's just this very dynamic score that keeps changing, and our job is to design and build a system that keeps track of that score. So it's pretty fun. It's especially fun this semester because I just recruited a bunch of people from SAAS. So Ashwin, Althea, and Sushant are all part of this team now. It's cool that there's a very large intercept. This sounds a little like nepotism, but it's nice because I know a lot of what these people have done before in SAAS, so you can screen for background in that way. So I've been doing that for a while, and I think it was a little bit different as a developer versus [where] I'm leading one of the teams, where you play more of just this PM role of communication, getting the data that people need, sorting out whatever issues, and also that large transfer of information because I was the only person left on this team after last semester. Ewen is busy with grad classes and other people graduated, so it’s just me trying to build a new team [and] communicate everything that we've done in the previous semesters, especially when documentation was not good. So [I built] this Notion [page] that had all the information about what we did previously, which is very different from just sitting down and writing a bunch of code because before it was like, all the information is just stored up here [in my head]. Now I was like, I'm not writing code anymore, so I need to make sure that all of that is communicated well and they have all the resources they need, etc.

How did you find out about SAAS, and why did you join SAAS?

This honestly feels like a while ago, so it's kind of hard to remember, but on Cal Day, there was some stats workshop. I remember they were talking about stats, and then there was one club that was like talking. They were like, ‘Oh yeah we have this organization with a bunch of stats students who do homework together.’ I'm not sure if that was like SAAS or SUSA because I'm not sure when the name changed, but I heard about some club like that, and when I was a freshman, first semester, I was just seeking out this club, and I looked up online, ‘Berkeley stats club,’ SAAS popped up. I was trying so hard to find them on Sproul, but I could not find them! I just don't know why. I couldn't find them until one day I finally found them and I talked to them. I don't even remember who I talked to. It might’ve been Andre because I remember they had a very eccentric personality. I remember it was these two guys who were like, ‘Oh, do you want to give the spiel?’ The other one was like, ‘No, you give the spiel,’ and I was just standing there. I was like, ‘Is someone gonna tell me what you guys do, or what?’ So maybe that wasn't the very best first impression, but I just signed up and joined. I guess that's how I found out about the club. I explicitly was looking for it, which I feel doesn't happen for a lot of people because it seems like there are fewer and fewer stats majors [in SAAS]. There are still some. I think there are some newer people who are stats majors, which kind of surprises me. I'm like, ‘Wow, they still exist!’

Can you list every committee you've been in? Or the role you've had?

First semester, Fall 2019, I was in CX. Spring 2020, I was in RP. Fall 2020, I was in IA. Spring 2021, I was IA Director, and then Fall 2021, IA Director. So I've been in IA for a while now.

What’s your favorite committee?

My favorite committee is probably RP because that's where I developed my skills and knowledge of data science the most. Coming from CX, I had this very high level view of what things were and different models that existed [and] what the overall goal of data science was. [I remember] playing around with a movie data set, where we predicted movie revenue. I didn't really know what was going on, honestly, but it was a good introduction into that.

I enjoyed RP because coming from that minimal or high level background, [I gained] a lot more experience of how to actually create a data science project from start to finish. That's the first time I realized, ‘Oh wow, data is hard to come by.’ So trying to collect that data from somewhere [and] clean up all that data took a really long time. Trying out a couple different models, seeing how those worked, [and] going through that entire process was really helpful. I think that experience carried very well into IA and all the other data science stuff that I've done before. Understanding how to work with different data formats, looking things up, how to model different types of data, because that was unsupervised clustering-ish. I say “ish”, because I didn't necessarily explicitly use only clustering techniques. But the problem, in essence, was an unsupervised clustering problem, which is very different from: you have A, you have B, how do you predict B from A? That was interesting to think about.

I just learned a lot, and that semester also was when I started getting more involved with the club. First semester, I was pretty shy. Going to, I remember you [Jackie] and Gracie would be like, “Oh, is anyone going to study hours?” and we’d be like, “Uhh, we're all kind of shy,” and no one ended up going. But I think next semester, after having been in the club, and being a returning member, and not a new member, just makes it a lot easier to go to stuff, and then I want to retreat that semester. We had a great time at retreat! I think that was when I really started to get to know people better and like a lot of new clubmates. That semester was [a] really positive experience for me.

What was your favorite SAAS semester?

Probably this semester so far at least. I think it's actually really crazy whenever I think about how much the club has changed socially. I think between like [my] freshman year when people weren't as social. I think that the club has gotten a lot more social, and also the difference between remote everything and in person [is huge]. We had our IA social on Friday, and it was really cool seeing everyone just chat very easily. It seemed like people were all already friends, not just committee members that were just going there and sitting there. Seeing everyone get along, it makes me really happy. I guess we more or less did our job of making the committee a pleasant place to be. So seeing all that happen and also all the events [makes me happy].

Honestly, when I joined SAAS, I didn't know if it was gonna be a community that I would make a lot of close friends in, or if it was just like I was here to meet some people, find people to study together, study with together, and just learn stuff. But I think now all my closest friends are definitely just in SAAS. I feel like I spend so much time with people in SAAS, and there's a lot of club [activities], things that we do in clubs, just like completely outside of clubs. [There are also] a lot of close friends that you tell your problems to. Also, I just happen to be living with three other SAAS people now, so I think it's nice.

I think [my favorite semester] is probably this semester because I feel like I've gotten very, very, very, very deeply integrated into the club now. I feel like it's also nice seeing other people get more integrated, more well-integrated into the club and meeting everyone.

Another thing to add is you [Jackie] know how Rachel [said] it was hard as IVP to tell if people are socializing or not? Whereas here in person [as a Director], you get to see the fruits of your labor. I tried to make sure that the committee is a nice place for people to be and the club is a place that people enjoy. That was something that I spent a lot of headspace thinking about, especially around recruiting: making sure everyone felt comfortable, making sure everyone had someone to talk to and was able to find friends and all that. That’s also the point of houses and [the] big little [system] and all that. But even just how you approach new people, like prospective new members [is something I care about]. Now, seeing people on the #spotted [Slack channel], where people will take pictures of you [is amazing because] they recognize each other and will take pictures with each other. Whereas during freshman year, if there was someone I knew, I'd be too shy to say hi to them and I would just detour. Now, it’s like, ‘Oh my God, it's [whoever], and seeing people hang out and willingly go on these coffee chats—I don't know how willing that is. [But in terms of] donutbots, a lot of people are willingly going on weekly donutbots whereas [in previous semesters], weekly donutbots happened in the first two weeks and [then] it just died. But we're in the thick of midterm season, and people are still doing it relatively often, like new members and returning members. Also just seeing IA members organize time on their own to work on some assignment—even if it's between different groups—it's something that didn't really happen before, but even if it did happen you can really see it, so I think now that we're back in person after a year of online, you can really see people being friends with each other, learning a lot, and you can see that they're paying attention in meetings because they're like, they have to—they can’t turn their cameras off—so that's always really nice.

Why did you decide to stay in SAAS?

The first semester, it felt very survey-y in CX. You got to see some [a broad range of topics in lecture]. It felt very “survey-y” as in the people too, where you got to see some people, but you weren't really interacting with a lot of people. So I think I wanted to get more involved with people after that first semester because the only person I really talked to was you [Jackie]. So I wanted to get to know more people. I also wanted to learn more, but I think a lot of it was like, okay, I don't have a reason to leave. So I'll just stick around and see how it goes, and from there, the next semester was a lot more enjoyable for me, even though we got booted out of Berkeley halfway through [due to coronavirus]. I think that semester was a lot more enjoyable, and since then, it hasn't really been a ‘Might as well stay, see what happens’. It doesn't ever cross my mind that I would want to leave because I’ve made a lot of friends here, like I really enjoyed it here.

How has SAAS helped you with your professional development?

I think because I've been in SAAS for like four semesters now, it's honestly been the core of everything professional development wise [that I’ve done]. First semester, I didn't really know what I was going to do. So it was a good intro into what [professional development] is like [with SAAS’] different workshops, like professional development workshops, course selection workshops, and recruitment workshops. You hear all these people asking what classes do you think are important for data science, classes that are important for SWE, or for quant—not that that's something I want to do. But it's like, I know all of these things, because of these workshops that I've seen in SAAS, and also, I think [SAAS has] given me the opportunities to work on a lot of cool projects to talk about, like [my] RP project. I've talked about that a lot in interviews or such. [Professional development] is something that you could do on your own, [but] it's just a little bit harder to do on your own. First of all, [it’s difficult] to find the motivation to do that, and also, to have that sort of mentorship.

For example, how do you know to use something like TF-IDF to vectorize whatever papers that you have, right? Like, I wouldn’t know, maybe I would first Google, ‘intro to NLP’ and then see something about vectorizing. Then from there, [there are] different ways to vectorize a paper and then we go from there to some low cost TF-IDF or whatever. Then maybe it's like how do I know to use this LDA model that I used? Like what is Latent Dirichlet Allocation. How would I have stumbled across that? How would I have known to use that? Maybe I would have spent hours and hours reading a lot of different models that I could use to try to determine which one's best, but how do I know which one is best because I'm new at this? Instead, I had God bless Nicole, my RP mentor. She would send me stuff, like, ‘Oh I talked to these people about this or like I've used this before, look into this, look into that.’ Even just a ‘look into that’ narrows your options down by a lot or what you want to look at next by a lot… Now your scope and pool of what you want to look at is all of data science, but now you’re like okay, we have these couple of things I might want to try out first. Maybe if I do more research about this, I’ll learn more about other stuff that might work as well. So I think having that kind of mentorship specifically in something like RP, helps you develop [your] project more efficiently, probably more in depth too, especially more in depth in the same amount of time that I would have spent just like doing all this on my own.

Also just like being in IA, or now being a director, professional development wise, I think professional and personal development, like being in leadership helps you learn a lot. It's hard to explain to people that have not been in leadership, but it's like, ‘How do you deal with people? How do you make sure everyone's doing their work?’ Those are things that people might ask you in behavioral interviews, and it's hard to fabricate all of those experiences. You have to go through some of these things to talk about it. ‘How do you deal with disagreements with people? Also, how do you try to create a positive, healthy environment in a meeting?’ Especially on Zoom, it was even harder when people didn't necessarily want to be there? ‘How do you make it relatively entertaining for them? Now in person, how do you make sure everyone feels comfortable? How do you address someone's questions?’ All those tiny little things add up, and you'll learn a lot about how to work in a team [and] how to lead a team as a director. Overall, SAAS has been the majority of my professional development, as in the IA projects [and] RP projects that I've worked on, getting all this help and mentorship, asking people about resume advice, recruiting advice, spamming Brian random questions all the time because normally who would you ask [those advice questions] to? Maybe you could post on Piazza, but [that’s] a lot less personal. Response time is going to be longer, so having that community to ask all these questions to, where people are very willing and enthusiastic about helping you is nice.

What is your favorite SAAS memory?

Probably Spring ‘20 Retreat. I think that was the first time where I felt like I got to know a lot of people better because the only people I knew before were you [Jackie] and Philip. We [also] knew who some people on leadership were, but it was the first time I really got to know people and it was also really inspiring to me because there wasn't a lot of professional development talk, but even during the car ride, hearing people just talking about what they’ve done before in SAAS [and] what they’ve done outside of SAAS, [I’m] like, ‘Wow, these people are really cool. They're really smart. They've done a lot of cool things, and they're just a lot of fun people that I want to get to know better.’ So that kickstarted me to put myself out there more and talk to people more. So I'm really glad I decided to go on that retreat.

How did you make friends with people in SAAS, and how did you meet them?

I think primarily just through committees, maybe not even that. I feel like [I meet people the most through] working with them on stuff. Period! So that could be like in CX, like when we were working on the movie project in CX, meeting you [Jackie] and Gracie. Then, [there was] our poppin’ [Stat] 140 group.The weekly suffer parties were always really fun. Now, I don't really know, because I don't feel like there's a clear answer. I feel like there are so many different types of activities in SAAS, so you can have different avenues of meeting people, like through committees. I've made friends through committees, like you [Jackie] and Gracie. I guess it just got harder online. But there are also classes, which I think is a big part, because we're spending all this time in [the same] classes anyways. You might as well be friends with the people that you're taking classes with. [In terms of] committees. I would say that I'm friends with my committee members right now. But they're also friends with each other, I think and hope. [Also], making friends within houses. Of course, there are different levels of friends. ‘How did I become friends with Rachel?’ I don't know. But there are a lot of different ways that people make friends, like different levels of friends. Pretty much, I've made friends in a lot of different ways, and I think people can make friends in a lot of ways. [You] just need to put yourself out there. That's the core part.

The SAAS values are community, exploration, and mentorship. Choose one, and explain what that SAAS value means to you.

Most important is community. Most of my close friends now are in SAAS or I've made through SAAS, so it's hard to not choose that option. The people that I decided to room with are because of SAAS. Honestly, we weren't that close before we moved in together, but now we're really close. But it's [because] I met them through the club.

At a lot of different clubs, there are a lot of different vibes, different people have various energy levels, have different interests, they spend their time doing different things. Here, there are a lot of people and a lot of different people, but I think we're all in the same ballpark of the types of people that we are. I think in finding this community where there's some level of diversity and what people are interested in, like what people do, there's a lot that brings us together. So I think [clubs are] a really good way to meet friends. Whereas just going out and trying to meet friends everywhere else is a little bit harder because you’re trying to find people that just happen to align with things that you're interested in and be close enough to who you are is all more difficult. So [I enjoy] having this group to make friends from or just being friends with many, many different people in the club. I also think it's because it's hard to make friends in college if there's not something that brings you together. So being here [in SAAS] and being with people who are in the same ballpark of the types of people that they are and also having something that brings you together, whether it's like learning together and getting professional development experience, working on projects, or learning about data science, while being around people, I think that just naturally brings you closer. Like you'll just be working on some CX project or IA project, and you’ll be talking with people. Then, you just become friends that way because you just end up having to spend time together. Having that sort of thing that brings you together. It's like seeing people in your classes. You make friends with people in your classes in high school. It’s a lot harder in college, but having something that simulates that, but hopefully it's a little more fun and rewarding. It's also just like people that you can take [Statistics] classes with, like 140 or 135. I think those are like the most, like involved group chats [that we have in SAAS].

I think that's what I have to say about community, but I want to throw something in there about mentorship. When I was a freshman, my older sister was actually a junior. So before I got more involved in SAAS, it was easy to find someone to ask questions to, about school, about clubs, about recruiting, mostly just about school and life. But if I didn't have an older sibling figure or just someone that I can ask questions to, I don't know what I really would have done. I feel like I would’ve been a little bit lost. It's like, ‘How do you find someone to ask questions to, who is enthusiastic about answering your questions?’ So I think in SAAS, there’s a really big benefit [because of Slack]. You can ask on the #advice channel, you can ask on your committee channel, or you can ask on #random. You can literally DM someone, they'll probably answer you and be pretty enthusiastic about answering you. Or just show up at an event and just ask them a question. They're gonna be pretty happy with that. Or at study hours. There are many, many avenues of asking questions and people have very easy access to that [in SAAS] which you might not get elsewhere. For example, a lot of seniors [in SAAS] are advisors, or Education members. They’re not someone you would come across in your day to day as a freshman or a sophomore. But here, you have very easy access to asking them questions, like DMing them or a lot of [professional development] events. I like to say, ‘Education is literally a committee exclusively to help people learn in CX.’

What is your personal vision for SAAS going forward?

I think a part of my vision is always that I hope it's a place that people can join, where they don't have to try very hard to be involved because there are systems in place to help them get involved more easily. For example, the Big/Little system. That’s something we [directors and executives] spent a lot of time thinking about, but also the houses or all these like various events. I think it's also a culture inside returning members to make [new members] feel comfortable and involved. Having that community where people can feel very comfortable without too much effort and really feeling like they have to force themselves to go to events is really important to me. I think we've made pretty significant progress towards that. As in people in IA, for example, are all talking to each other.

With big-little, people seem to be fleshing it out more. People seem to be a lot more involved with their littles. There are a lot more big little pairs that are more involved. Of course, a lot of that just comes with being in-person rather than online. But you see people voluntarily going to stuff and actually doing something every week. People like actually going to have socials every week. Sure some weeks are more busy. Some weeks, less people go, right, but a lot of people are going to these things. So I think [it’s important to] create a club where people see it as a community, not as an opportunity to work. It's also an opportunity for mentorship, of course.

How has SAAS changed during your time in the club?

It's become a lot more social. I think it's because for a lot more people, it's become more of like a community and not just like a place to work. I think before it was like that for a certain subset of the club, but I feel like that subset is expanding. So I think that's a big way that things have changed, just that it's become more social. I think there's also this ‘jump’ between people just seeing it as a place to work versus seeing it as a community. There's also this ‘jump’ between people seeing it as something for the resume versus people seeing it as a place where they can learn a lot and they can contribute a lot to.

What advice would you give to newer SAAS members?

Talk to people! I think it's good that people are doing coffee chats and donutbots, but by ‘talk to people,’ I mean [that] there are so many different perspectives and experiences that you can learn about that you wouldn't if you didn't talk to people. It's like, ‘How do you know that you're gonna get one very strong takeaway that someone has for you?’ Maybe one thing they say is really gonna resonate with you, and that's gonna change your perspective towards a lot of things for the rest of your college career. You don't know when you're going to get that one line [of advice], you don't know who you're gonna get it from, and you don't know what that one line is. But you'll never know unless you put yourself in situations where you can learn about things like that. So maybe you'll learn about a career path that you didn't know before. Maybe you’ll learn about a certain senior’s perspective on career and college that you didn't know before as a freshman. All these things you just wouldn’t know unless you talk to people! So I think talking to people is really important. It's really easy to think about college as like this beautifying path, especially where people are interested in SWE, for example. You take these classes, you declare CS, you get an internship, you get another internship, and then you get a return offer. Well, there's like more to life than that. I think it's easy to get pigeonholed into that mentality of, ‘Oh, that's what's important out of college.’ But I think [in] talking to different people about their experiences, maybe some people will tell you like, ‘Yeah, making friends is a lot more important.’ Like the relationships that you make, like the network that you build, what you learn about people, and like, what you learned about yourself, those are all really important as well. Seeing those concrete examples through people's experiences, I think is really beneficial, just to anyone.

What’s your favorite class?

Probably [Stat] 140. I thought it was really fun. Also because our group [with Jackie] was fun.

Who’s your favorite professor?

I feel like most of my learning in college has just happened on my own. I have a couple of least favorites, but I don't think that's appropriate here. My favorite professor might be the Stat 140 textbook. But if Professor Adhikari wrote it, then maybe that’s my answer?

What’s your favorite Berkeley memory?

I can't think of anything in particular. I don't think there's like one single memory, like one thing that jumps out.

What’s your favorite spot on campus that more people should know about?

I don't really go anywhere. It’s not Moffitt. Less people should go to Moffitt, so I can finally find a seat.

What’s your favorite place to study on campus?

I think before [Moffitt] was my favorite place because it was open very late, but I really like East Asian [Library], like those tables right next to the window because of the sunlight.

What’s the prettiest building on campus? Alternatively, what’s the ugliest building?

I don't actually understand the Evans hate. I think it's not necessarily nice, but it's just kind of there. I [have] never really noticed like, ‘Oh I wish it would burn down or something.’ Ugliest building? I don't even know if it's Berkeley-affiliated, but you know that building between Martinez Commons and Crossroads, the really old, crusty, wooden one [the Institute for the Study of Societal Issues]. I'm like, ‘That's hideous! Why is it there?’ Maybe that's appropriating some [architectural style]. I don't know. Maybe that's not [appropriate], maybe I'm gonna get cancelled for saying that.

Prettiest building? Maybe just East Asian [Library]. I think it just looks very nice. The study rooms in East Asian are so nice. I've been [in one of the study rooms] once for one CSM section, and it was really nice.

What’s your favorite bathroom to use on campus?

One where no one else is in it. Any one that has no one else in it. Favorite bathroom? Yeah, I don't really know. I can't say.

What’s your favorite restaurant in Berkeley?

It's not my absolute favorite, but I like Tasty Pot because I like hot pot.

There's one place called Southside Station. It's like across the street from The Dwight. It has really good garlic noodles. I’ve only been there once. It's far, but it's only like two blocks from me because I [live] all the way down here. It was last Friday, but I was so sad because I ordered this lychee tea thing, like one of the combo things that comes with a drink. I added $3 to get this lychee tea and then I was really ‘brain off’ walking back. When I got my food, I forgot to get the drink. I only realized two hours later when they were closed. I was like, ‘No, my tea!’

Speaking of tea, what is your favorite boba shop?

I went to Asha for the first time. I had that Asian pear [drink]. I thought it was so good. It reminded me of Taiwan. Asian pear just reminds me of Taiwan.