- Hey! Who are you, what are you currently doing and what is your background?
- How did you decide that you wanted to pursue an MS in the US?
- How did you start your application preparation; can you throw some light on profile building, GRE, LORs and SOPs?
- What colleges did you apply for and what was the result?
- Can you tell us more about the course you chose and what the learning outcomes are?
- What is the cost of tuition and cost of living for the program?
- What does the future after master’s look like?
- Any final words of advice for anyone who aspires to be where you currently are?
- Resources Suggested by TheGradPost
- Connect
Hey! Who are you, what are you currently doing and what is your background?
My name is Aditeya Baral, and I’m currently a first-year graduate student pursuing my Master’s in Computer Science at NYU, specifically at the Courant Institute of Mathematical Sciences. I’m in my second semester now, and I’ve opted for the two-year track instead of the one-and-a-half-year option. This track is more rigorous being research-focused, and will involve a thesis in my second year as well.
I completed my bachelor’s degree in Computer Science from PES University, graduating in 2022. I specialized in Machine Learning and Data Science during my undergrad. After graduating, I joined Cisco Systems, where I worked as an AI researcher and Big Data engineer for the Webex Meetings Team. Previously, I also interned at Intel as an Applied Scientist and was an Undergraduate Research Assistant at my college.
I engaged in ML and NLP research through multiple avenues, whether it was through research labs at college, my internship at Intel Research, or the work I did at Cisco Webex. When it was time for applications, I had over 2 years of research experience which included 2 internal whitepapers and 3 conference papers, some at top venues like AAAI and ACL-ICNLP.
I realized that pursuing a PhD was my ultimate goal, but I didn’t feel fully prepared to take that step immediately after undergrad. So, a master’s felt like the natural next step for me. It’s helping me build the skills, knowledge, experience and valuable connections I need to prepare for the journey toward a PhD.
How did you decide that you wanted to pursue an MS in the US?
When I was exploring master’s programs, my primary focus was on finding a strong research fit. Since my ultimate goal is to pursue a PhD, I wanted to make sure that whatever I did during my master’s would be relevant and actively contribute toward that goal. As I dug deeper into US universities, I found specific institutions and programs where the research opportunities aligned perfectly with what I wanted to pursue and how I envisioned building my academic career.
While I could have applied to some PhD programs straight out of undergrad, they wouldn’t have been at the top universities or aligned as closely with my research interests. I realized that giving myself two more years through a master’s would allow me to build a stronger research profile, gain more publications, and build connections with researchers I’d want to collaborate with in the future. All of this would help me secure a better PhD admission at a university that’s a perfect fit for my goals.
How did you start your application preparation; can you throw some light on profile building, GRE, LORs and SOPs?
Before starting the application process, I had friends who had either applied for or were pursuing their master’s degrees. From them, I understood the importance of giving yourself ample time to complete the entire process. My general game plan was to start early and finish timely. While applying early might not give you a competitive edge in the decision-making process, it definitely gives you room to build your application comfortably, without feeling rushed. This was particularly important for me because I was working full-time and taking out time every day for applications wasn’t possible.
The first step in my application process was researching universities. For me, finding a research fit was the most crucial part of my application. I needed universities that had active research labs in my field of interest, professors doing the kind of research I wanted to be involved in, and most importantly, professors who were open to master’s students contributing to their research. This kind of research takes time—you have to dig deep into university websites, explore labs, faculty profiles, and review their recent work with their current students. So, my shortlist was based entirely on research alignment, not on admission statistics like GRE scores or acceptance rates.
SOP & LOR
After that, I focused on writing my Statement of Purpose (SOP) first since I knew it could make or break the decision. I spent almost two and a half to three months on it because it had to be tailored to each university. I had to clearly demonstrate how my research interests aligned with the faculty, explain how my past experiences were related to their previous work, contributed to my current goals, and show how working with specific professors would help me achieve my future ambitions.
Courant also required a personal history statement where you can elaborate on who you are as a person and your non-academic endeavours. I chose to discuss how my interest in Computer Science grew from my schooling days, my volunteering efforts as part of different organisations and clubs across school and college, how I felt about open-source and the industry, and how my experiences can add to NYU’s diversity.
I was fortunate with LORst. During college, I had worked with several professors as a teaching assistant or research assistant. At work, whether at Cisco or Intel, I had managers and research advisors who were very supportive of my goals and offered to write me as many as needed and were pretty prompt with submitting them on time. I finally submitted 4 LORs to every program distributed equally between college and work.
GRE
For GRE preparation, the first thing I did was take a mock test to see where I stood without any preparation. I realized that the Quant section was straightforward—it was more about time management. The Verbal section, however, was challenging, especially for someone from an Indian background. For Quant, I practised by solving multiple mock tests and problems. I used the Manhattan 5 lb. Book for Quant preparation, which I found helpful since it was slightly more advanced than the official ETS materials. This higher difficulty level helped me manage time better during the actual test. Some other books I would recommend are the official ETS materials and the Princeton Review.
For Verbal, I knew I wouldn’t score as high, so I focused on what I could control, like the reading section. I watched several GregMat videos for strategies and used the Magoosh flashcards app to memorize as many words as possible. I watched a few videos on how to tackle the AWA section from YouTube and that was more than enough. I finally scored 320 in the new format with a 154 in Verbal, 166 in Quant and 4.5 in AWA.
Many programs have stopped accepting the GRE, so I would recommend first checking if your application needs it. The GRE not only takes time to prepare for but is also expensive. However, a strong GRE score of 330+ can boost your application if the program needs it or lists it as an optional material.
Timelines
I started my application process early, around February 2023, with all my deadlines set for December 2023. I gave myself almost 10 months since I wanted that buffer. I dedicated around four months to preparing for the GRE, and completed it by June. I also finished the TOEFL by July.
Once I had everything ready, I started submitting my applications. I realized I had the bandwidth to apply to 15 programs. I began applying in early November and finished by mid-to-late November, well before the December deadlines.
What colleges did you apply for and what was the result?
I applied to 15 universities as below.
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Can you tell us more about the course you chose and what the learning outcomes are?
Once I started at NYU, I realized that many of the courses here are research-focused, especially if you’re looking to specialise in ML. Pursuing research is integrated into the curriculum, meaning it’s something you actively do during the semester as part of your coursework. For example, a significant portion of your final grade—sometimes 50% to 60%—comes from a research project you carry out over the semester.
It’s uncommon to find courses at NYU that follow the traditional structure of lectures, exams, quizzes, and labs. Instead, many courses are structured more like research seminars. Class sizes tend to be small, around 15 to 20 people, and each week, we discuss several research papers. Everyone shares their views, critiques the papers, and we delve into their pros and cons. Your grade depends on how well you understand and engage with the material. Overall, if you’re interested in research, Courant is a really great place.
But there are also courses that are engineering-driven courses aimed at students looking to get into the industry. These comprise semester long SWE projects and are meant to show you a glimpse of building large scale solutions to problems. Many students who aren’t into research but want to work in applied fields (like MLOps, BigML Systems and so on) often pick up these courses.
The cohort size is somewhere between 150 to 200 students—don’t quote me on the exact number, but it’s around that range.
Pros & Cons
In terms of the pros and cons of the college, if you’re someone interested in research, NYU is a fantastic place. There are abundant opportunities both within and outside the curriculum to get involved in research. The professors here are incredible; many of them have done groundbreaking work in their fields. There is always a chance (happened to me twice!) that the topics you’re learning about were invented by the professor taking that class.
On the downside, NYU doesn’t have a traditional campus. It’s more like a collection of buildings scattered throughout the city. So, if you’re looking for that classic campus experience with green spaces and a centralized student life, NYU does not offer that. Most students come to class, meet with professors, discuss their research, and then head back home. The moderately large intake also means that enrollment for courses is competitive with the most popular courses getting filled up in seconds.
What is the cost of tuition and cost of living for the program?
The tuition cost at NYU is roughly $20,000 per semester. When it comes to the cost of living and accommodation, it largely depends on where you stay. Most international students from India don’t stay near campus because it’s extremely expensive. Instead, students typically choose to live in two main areas. The first is Jersey City, specifically a place called Journal Square. It’s like a student town and has a significant Indian community. I’d say about 80 to 85% of students from India stay there, including myself. The other is in Brooklyn.
Your combined cost of living and accommodation can range from $1,000 to $1,500 per month. Most people find accommodation between $900 and $1,200, and the rest depends on your lifestyle.
Scholarship Opportunities (TA/RA)
Regarding scholarships, NYU doesn’t waive tuition fees even if you’re a TA or RA, which is a bit of a disadvantage. Teaching Assistant (TA) and Research Assistant (RA) positions do pay well, but they’re quite difficult to get. For TA roles, you need to have taken the course or a related course to qualify. So, in your first semester, it’s almost impossible to get a TA position since you haven’t completed any courses yet. By the second semester, more people have managed to find TA roles, but even then, the positions are limited, and the competition is stiff, especially when you’re up against second-year students or even PhDs.
TA roles pay around $3,500 to $4,000 per semester, which covers about four months of your rent. As for research assistant positions, it’s nearly impossible to get one with a professor since most professors already have PhD students working with them. Some people do find temporary RA roles that last for a month or two, but these are rare.
What does the future after master’s look like?
The job market is pretty tough right now, and landing offers has been difficult. In terms of internships, I’d say I know maybe five to ten people who have secured one so far, and that’s after nearly six months into the first year. It’s been challenging—most people haven’t even made it to the interview stage yet. It’s a lot of sending out applications and then getting ghosted.
Typically, when you join in the fall, there are two main hiring periods. The first is right after you arrive, but that’s not a significant hiring season. It’s pretty light, and it’s uncommon for people to land anything at that time. The second, more important hiring window starts around the end of January and continues until summer—that’s when peak hiring for internships happens.
Regarding the PhD, this is roughly how the process works. Typically, when applying for a PhD, you target specific professors you want to work with. Each professor usually has a few open spots—no more than three or four—for new PhD students. So, again, it’s highly competitive. PhD students are funded; you receive a stipend each month, which is meant to cover your expenses.
Now, while that stipend is intended to cover all your costs, realistically, it doesn’t cover everything. But it does take care of a good portion of your living expenses and other costs. So when people say PhDs are fully funded, they mean you’ll get enough to handle most of your expenses, though you might still need to manage a bit beyond that.
Any final words of advice for anyone who aspires to be where you currently are?
If you’re someone who’s just starting your undergrad and planning to pursue a master’s later, the first thing I’d advise is to maintain a good GPA. One thing I realized during my application process was that my GPA held me back from several places. Even though I had a solid amount of research experience I still didn’t make the cut at many institutions because my GPA caused my application to get filtered out early.
Another important point is to build your profile around a specific area, field, or skill set. It really helps to show that you have a clear direction and specific goals. Having a broad, jack-of-all-trades profile doesn’t really help in these admission decisions because a master’s is meant to specialize in a particular field. While no one expects perfect alignment coming out of undergrad, there should be some clear signs of your focus. If you can’t show that, it doesn’t work in your favor.
For those specifically interested in research, having a defined research direction makes a big difference. If you’ve worked on research projects aligned with a particular field or problem you want to solve, and even have publications in that area, it shows you know what you want to pursue. It demonstrates that you have goals and are committed to them. On the other hand, if someone says they’re interested in research but doesn’t have a clear path or area of focus, it’s hard to convince anyone of that interest especially for research-centric programs.
One more thing, and this advice is particularly relevant in the current job market but might change in a year or two: picking up some work experience before coming for your master’s can be really beneficial. I’ve noticed that the people who have secured internships so far all have at least one or two years of work experience. Companies are definitely looking for candidates who already have experience in relevant fields.
Resources Suggested by TheGradPost
For GRE/GMAT, especially for acing it in the quant session, try out Target Test Prep (TTP).
Air travel and temporary accommodations – MakeMyTrip
Help with a simpler transactions process – HDFC, SBI, ICICI Credit Cards
Connect
Linkedin – Aditeya Baral
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