How I Got Into Columbia University For MS in Computer Science?

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Hey! Who are you, what are you currently doing and what is your background?

Hi! My name is Uttara Ravi. I have a background in Computer Science, having completed my Bachelor’s degree at BITS Pilani, Hyderabad. After graduating, I worked as a back-end engineer at Oracle for a year before pursuing a master’s in computer science at Columbia University. Currently, I’m working as a software engineer at Everlaw, a legal tech company in the Bay Area.

During my undergraduate years, my projects significantly shaped my master’s application. Early on, a cryptography course piqued my interest in blockchain, leading me to explore security-focused projects. In my final year, I collaborated with Professor Barsha Mitra on a project about role-based access control models, which culminated in a published paper—a standout element in my application. I emphasize my interest in security throughout my application, tying it back to my projects and the published research.

My internships also played a role, particularly my six-month stint as a software engineer intern at Blue Jeans Network, which provided hands-on industry experience. Although my earlier PS1 internship was less impactful, these varied experiences helped shape a well-rounded profile.

How did you decide that you wanted to pursue an MS in the US?

A significant push came from the desire of wanting to delve deeper into the field, something that is missing during one’s undergraduate studies, which is natural because one’s undergraduate experience isn’t just about their academic life – it is heavily shaped by the fact that you are  stepping out of your home for the first time, exploring new activities, and experiencing the personal growth that comes with it. A master’s degree, on the other hand, felt like a more focused period where I could truly learn and specialize.

Another major factor was the desire to experience a different education system and gain international exposure. Exposure was a big criterion for me. Why specifically the US? Well, when you see positive examples of people who have done it before you—friends or seniors—it creates a sense of possibility. For me, my older brother was an example, and the US felt like a natural choice. The US (especially the Bay Area) being at the center of innovation and better opportunities in tech specifically also added to this.

How did you start your application preparation; can you throw some light on profile building, GRE, LORs and SOPs?

The whole application process can often feel like a black box—there’s no clear formula. Sometimes, you see someone with an amazing profile get rejected by a school they were expected to get into easily, while other times, people get accepted to ambitious schools but rejected from safe ones. So, I’d say take all this advice with a grain  of salt.

For my game plan, the first thing I did was focus on professors for letters of recommendation. Some professors are really selective about it. I remember in our college, certain professors wouldn’t give you an LoR unless you had perfect attendance or a ten in all their courses. So, you can’t just randomly ask someone—you need to have some sort of connection. If you’re still in college, I’d suggest building a rapport with professors early on. It really helps if they know you personally or if you’ve worked on projects with them. 

GRE/TOEFL

I graduated in 2019, and my job started on July 31st, so I used the time right after graduation to focus on taking the GRE. I thought it was better to do it before work started, so I prepared during the summer and took the exam around July 18th. If you’re in a similar situation, I’d recommend using your final semester or summer after graduation to study—it’s much harder to prep once you start working.

For GRE prep, a friend and I shared a Magoosh account. It’s common—people buy a six-month subscription, use it for two months, and then rent or sell it to someone else for the remaining duration. Along with Magoosh, I used Kaplan’s series of practice tests. I feel like I made a mistake by focusing too much on verbal because everyone said Quant would be easy for engineering students. As a result, I ended up making silly errors in Quant, which brought my score down a notch. So, if I could go back, I’d try to balance my prep better. Ultimately, I scored 326—160 in Verbal and 166 in Quant. 

SOP

Now, coming to the SOP—this is something I’d highly recommend starting early because it goes through so many iterations. It’s not something you can just sit down and finish in one go. Honestly, my SOP wasn’t just my work; I had so many people help me by giving me valuable feedback. The SOP is about telling a story, so you need time to get it right. Start with a rough draft, no matter how bad, and keep refining it.

What colleges did you apply for and what was the result?

I applied to 8 universities as below.

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Can you tell us more about the course and what the learning outcomes are?

As for my learning outcomes, when I was at Columbia, I took courses in machine learning, data mining, and artificial intelligence. However, one thing I learned is that you don’t always get the courses you want. Depending on how large the cohort is, some courses might be full, and there’s nothing you can do about it. I think people often have this rosy picture of a master’s program, thinking they’ll take all the best courses and learn exactly what they want. But it doesn’t always work out that way. 

In terms of crafting my curriculum, I knew I was interested in machine learning, so I took courses in that area, along with natural language processing. I read about the professors teaching these courses—sometimes you find a professor who’s doing really cool work, and you just want to learn from them. I didn’t have everything perfectly planned; I just winged some of it. One of the more experimental courses I took was a foundational course on blockchain. I felt like I had the opportunity to explore a bit, so I did.

Even though some of the things I learned, like blockchain or NLP, don’t directly correlate with my current job, I still feel the skills are transferable. It’s more about learning how to learn, solving problems, and completing assignments. So, while I’m not using blockchain or NLP in my job, the overall experience of doing a master’s was still very valuable for me.

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What is the cost of tuition and cost of living, and how are you planning to fund your studies?

Tuition costs at Columbia were about $88,000. Living expenses and accommodation are a bit subjective—it really depends on individual lifestyle choices and where you live. I went during the COVID period, so for one year, living expenses were relatively cheap, but in the last six months, they became more expensive. One thing to keep in mind about Columbia is that, since it’s a private university, they are quite stingy when it comes to providing financial aid or stipends. At least when I was attending, for a whole semester’s work as a teaching assistant (TA) or research assistant (RA), they would give you around $2,000 to $3,000 total, which isn’t much. In contrast, other schools like UC Davis provide around $2,000 to $3,000 every month and even waive part of your tuition fees. Columbia didn’t offer anything like that.

Personally, I felt that the $2,000 to $3,000 for an entire semester wasn’t worth the stress and extra work. So, I chose not to pursue TA or RA positions. As a result, my master’s was fully funded by a loan from my family.

How was your job hunt process like during Master’s?

Since I graduated about two and a half years ago, my job hunting experience was in a completely different market than what it is now. I started looking for jobs in August 2021, and by that time, the market wasn’t as challenging as it seems today. My approach was pretty much brute force—I just shot my shot everywhere. I opened LinkedIn and applied to as many jobs as possible. A friend shared a website with me that listed roles for recent college grads, so I used that too. The job I have now, I actually found through LinkedIn. I was pretty fortunate with my job search because I ended up landing a job at the second company I interviewed with. I really liked the engineers I interviewed with, the culture and the company’s mission so I decided to stop pursuing the job hunt once I landed this role.

Any final words of advice for anyone who aspires to be where you currently are?

One thing I wish I had known earlier is to do better research. At the time, I didn’t know about a lot of good schools in the Midwest, and I completely skipped applying to that whole group of schools. In hindsight, I should have applied more ambitiously. Many of these schools have great programs and offer good TA and RA opportunities, which can reduce costs significantly. That said, there’s a balance. You don’t want to apply only to super ambitious schools and risk not getting in anywhere.

One thing I believe I did well was my SOP. It went through many iterations, and looking back, I think that made a big difference. My advice for writing an SOP would be: don’t add fluff. People can tell when you’re just writing to meet the word count. Every sentence should have a purpose—think of it as an opportunity to sell yourself. Your SOP isn’t supposed to be a creative writing piece; it needs to show a clear, logical flow. Everything should tie together and tell a coherent story.

Get feedback from people who will be brutally honest with you. Also, find people who have gone through this process recently, especially those who applied to the same schools you’re considering.

Finally, tailor every SOP to the specific university. This might sound like obvious advice, but many people don’t do it properly. Mention professors by name, talk about their research, and explain how their work aligns with your interests. I did this for Columbia—I named professors in the cybersecurity department whose work I found interesting and connected it to the courses I had taken. The more personalized your SOP is, the better your chances. Research the university well, tailor your application, and show genuine interest.

Throughout the process what were some helpful resources, tools and books you used?

For GRE and TOEFL prep, I used Magoosh, Kaplan, and I think Princeton Review or something similar. There was a set of five free practice papers I used—those were quite helpful. For TOEFL specifically, I didn’t do much prep. Honestly, the day before the test, I just watched a YouTube video that explained the format and what to expect. My main suggestion is to practice the verbal section at least once before the test. You might think it’s easy to just speak during the test, but practicing it verbally beforehand helps a lot.

For university selection, I relied on the “BITS to MS/PhD” Excel sheet, which I found pretty useful, and online forums like Yocket where people would post about their profiles and their admits.

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