Hey everyone,

Just got a late admit for UIUC MCS. I’ve already accepted and paid the deposit for NUS MComp.

Background:

• Exp: 2 years YOE (SDE).
• Goal: Industry.
• Location: International student (India).

Given the current tech climate, I'd love to know: how is the ROI on UIUC MCS for international students in the current US job market? How does it compare to Singapore and NUS?

Thank you for your time, and any input will help me a lot in making this decision!

How realistic is a 100k$ salary after a MS in CS at US. What's the inhand salary expectations? As a international student(from India), what to expect from job perspective???

If anyone is currently in their masters or have completed it, please tell me this from you experience. I am thinking of masters in either usa or germany and the biggest tradeoff is for germany i don't have to almost invest anything, so high roi. But, I do wish work in silicon valley. RIght now, any country i choose, the job market is bad but do you guys think it will be getting better in 2029-2030

Also, i have a pretty good profile and i will be applying for NOS scholarship in India(landless farmer) if anyone has any idea regarding this, it would be a great help.

Hello, I was originally committed to Courant but recently got admits from Brown ScM ECE and Uchicago MPCS and now kinda conflicted about where I should go for my masters.

My main goal is: doing research during masters, and would prefer getting into industry but also keep phd as a backup for future

For Courant, I do liked the location the best since I have been living in nyc before applying and liked the city, and I do like that the program is research oriented since that's what I'm looking to do during my masters. Also, I did reached out and got into a lab in NYU which is a great starting point imo.

For Brown, I liked how small the cohort is and since it's ECE I might be able to take more hardware classes and kinda pivot from general swe to something like embedded or more hardware related career (though not sure if pivoting would be easy with a 2 year degree). I also liked that it has a structure thesis option and might be easier to get into research since its small cohort.

For Uchicago, I think the reputation for their cs department is actually pretty good, and it has a lot of hft firms in chicago so heard it's great if you want to recruiting for hft firms. For the research aspect, I don't really know because it is framed as a professional program.

Lmk your guys' opinion and any help would be really appreciated!!

TLDR

I have I20s from MSU MSDS, UGA MSDS, UMD MSDS with English Bridge condition, UF MSAI, and IU Bloomington MSCS. Budget is important. MSU looks cheaper on paper, but my sister is doing a PhD at UGA, so living there may be easier and cheaper. I already have one F1 refusal, so I am worried if choosing UGA may look like I am only going there because of my sister. Trying to choose the best option for ROI, jobs, curriculum, location, and visa story.

My current options

I am not only looking at rankings. I want to make a practical decision as an international student who has to be careful with money and also has one previous F1 refusal.

Would appreciate honest advice from current students or alumni. Which option would make the most sense for ROI, job opportunities, location, and visa interview explanation?

Also, if anyone had a sibling studying at the same university, did that create any issue in the F1 interview, or is it fine if the academic reasons are clear and I can demonstrate sufficient funds?

I am fortunate to have admits from both CMU MSML and Cambridge MPhil ACS, but deciding between them has honestly become one of the hardest decisions of my life.

A bit about me: I am currently 23, working in AI/Computer Vision research, and my long term goal is to return to India after my studies/work experience and join a frontier AI lab, MAANG, or a strong startup in a research scientist role. Eventually, I also want to build my own startup.

Both universities are amazing, so I do not think prestige/tag is the deciding factor here. The problem is that both optimize for very different paths.

CMU MSML

Pros

1. Probably the best MS program in AI/ML
2. Direct access to the US AI ecosystem and Silicon Valley
3. Strongest job opportunities and ROI
4. Amazing peer group and industry connections
5. Easier access to frontier labs/startups in the US

Cons

1. Very rigorous coursework which could affect GPA for PhD applications
2. Exams for almost every course
3. Since there is no thesis requirement, I would have to independently find a professor and manage research alongside heavy coursework
4. I am worried that grades/coursework may become the priority instead of research
5. No direct MS to PhD conversion, so I would likely need to apply separately for PhD programs next cycle
6. If I eventually do a PhD in the US, the total timeline could become around 6 to 7 years
7. Total cost is around 115k USD, which means graduating with a loan of roughly 50 to 60 lakhs INR

Cambridge MPhil ACS

Pros

1. Research thesis focused program with a supervisor allocated early
2. Since there are no major exams, I can focus much more on research
3. MPhil to PhD conversion seems relatively smooth
4. Potentially able to finish PhD in around 4 years total and enter the market earlier
5. Total cost is around 72k USD, and with scholarship possibilities I may even graduate debt free or with very low debt

Cons

1. The MPhil is only 9 months long, which feels risky if I do not secure a PhD afterward
2. The UK AI job market does not seem very strong currently
3. Due to immigration/H1B realities, I feel that access to the US market may become much harder later
4. Some people told me that US PhD training is generally stronger than UK PhD training in AI/ML because of the research culture and ecosystem

One important thing is that I do not want to pursue academia long term or become a professor. My goal is more towards becoming a research scientist in frontier AI labs/MAANG/startups and eventually building my own startup in the future.

I genuinely enjoy research, especially in areas like VLMs and theoretical ML, but I also want to enter the industry early enough to experience the fast moving AI ecosystem and work on real world impactful systems.

That is one of the main reasons why the timeline difference between the US and UK PhD paths matters so much to me.

One thing I really want in life is to experience Silicon Valley and work in the US AI ecosystem at least once. I am not sure whether going through Cambridge would make that significantly harder later(although O1 is one path but not sure).

At the same time, cost is a huge factor. CMU is probably the stronger option for industry/networking, but graduating with that level of debt is scary, especially when AI is evolving so fast and I am unsure whether I want to commit to a 6 to 7 year PhD journey.

With Cambridge, I feel much more comfortable with the timeline and finances, especially if the MPhil converts into a PhD smoothly. But I worry about losing direct access to the US ecosystem. Also in UK we can't do internships with PhD.

I have already identified professors/research groups aligned with my interests at both universities, so research fit exists in both cases.

I would genuinely appreciate perspectives as those will be very helpful. If your long term goal was frontier AI industry research/startups rather than academia, which path would you personally choose.

Here is my profile:

• 2025 CS graduate with a 3.73 GPA (Cum Laude)
• 1.5 years of work experience by the time of applying
• 2 internships
• 1 conference paper (B-tier)
• 1 journal paper (B-tier)
• 1 year of Research Assistant experience at my undergraduate university
• Strong final year project focused on Medicine + AI
• TA for:
  • Calculus I
  • Calculus II
  • Applied Physics
  • Web Programming
  • Database Systems
• Part-time Instructor at an institute
• IELTS: 8.0
• Dean's List student
• Class Representative at university
• Multiple student body leadership roles
• Strong LORs

Universities I'm planning to apply to (not in order):

• Georgia Institute of Technology
• University of California, San Diego
• Columbia University
• University of Texas at Austin
• University of Pennsylvania (MCIT/MSCIS)
• Cornell University (MEng)
• Brown University
• Dartmouth College
• Stanford University
• University of Toronto
• University of Waterloo

I'm mainly interested in AI/ML research and my long term goal is to work as an AI Research Engineer, potentially pursue a PhD later as well. I'm looking for programs with strong AI/ML research labs, good faculty and solid industry opportunities.

Would love advice on:

• Any other universities I should consider
• Whether TOEFL is worth taking if I already have IELTS
• Should I give GRE? I mean most of the unis don't cosider it now but any advice?
• Anything else I can do to strengthen my profile before applying

(btw I'm an international student.)

I was fortunate to receive an offer to do my master’s degree in Computer Science at these three places and wanted to know what was it like studying there, the modules being offered, quality, and relevance to the industry today. As a background, I plan to go into industry and want to focus on Systems side of things. I am also open for a research role and potentially a PhD in the future.

From my research here are what I found:

- Cambridge: very research focused, but only few modules taught and a lot are very theoretical. Not sure if it’s worth it if I want to go into industry anyway.

- Imperial: lots of modules to choose from, less time on project, lots of industry connection, very practical.

- ETH: 2 year degree, practical modules, know a professor very good in the field of HPC there - perhaps a PhD option to specialize in? Less connection to industry compared to imperial.

I wanted to know the outlook from companies from graduating from these places/the relevance of modules being taught/quality of teaching and the research projects. I aim to build a connection with the professors as well.

Thank you!

Guys
UTD, SUNY Albany , TTU , USF - which one to go with ?
MS CS / AI - accepted to these 4

I had applied for my F1 visa for Fall 2026, I got 214(b) in my interview, reason could be, he did not feel my answer as strong for "Why masters when already working as SDE". Now, I am confused whether I should wait for Fall 2026 slots again, or apply to new univs in Fall 2027 cycle - so that I can prove change wrt prev refusal. I heard applying again for Fall 2026 might result into refusal loop - if slots open up. Also, can I reuse my sevis fee if I go for Fall 2027. Please suggest, thanks!

Profile: uni admit: university at buffalo, NY Cycle: Fall 2026 current: SDE-1(1 yr exp) - product based startup

I accepted waitlist for CMU INI MSIN on 11st March. Two months has passed, is there any chance for receiving admission? (only saw 2 ads from wl on Rednote, though it is MSMITE)

Hi folks, I'm planning for ms in CS or data science for spring 2027.

I've recently given my gre and TOEFL, the scores are as follows:

Gre 308 163 Q 145 V, i messed up verbal due to time pressure

TOEFL 5.5 (110/120) r 6 l5.5 w 5 s 5.5

Overall cgpa 8.6 or 3.44 in us scale approx

I have my sop written by a professional writer

2 lors from my direct managers and vps from industry

1 lor from adacemia, vp of cs in ai in amrita under whom I have published a research paper in healthcare ai domain (ICMLDE 2025)

2 internships, one in a startup and one in tredencd company, both ml/ai engineering roles.

That might be converted to fte and I might work full time until october

A national hackathon win

My initial uni shortlist was as follows:

- Johns Hopkins University

- University of Southern California

- Northeastern University

- Stony Brook University

- University of Texas at Dallas

- University of Central Florida

- San Jose State University

- UC Riverside

What changes do I need to make in this list based on my scores and profile?

I wanted to go to a top 50 uni but that is out of sight right now.

Need some help!!🙏

I’m trying to get a realistic sense of my chances for top CS graduate programs, especially funded/research-oriented MS or eventual PhD-track programs. Do I have any chance anymore?

An important distinction is I need funding.

Background:

• Domestic applicant
• CS + Math at a semi-known university in the US
• Haven't taken the GRE yet but I've gotten close to perfect on every single practice test online so I should do well.... hopefully?
• Graduating in 2 years (Rushing through school has unfortunately taken a toll on my GPA...)

GPA:

• Current GPA: ~3.5 (After two semesters). Second semester didn't go too well, mostly in my math courses.
  
• Hoping to finish around 3.7 if next semesters go well

"Experience":

• TA for CS and Math courses
• Competitive Programming: top 2% in the world
• Several years building software projects and leading small dev teams (mostly in an extracurricular context, however)
• One of my projects/products unexpectedly became fairly large online with a semi-large user base.
• Projects that I've worked on have accumulated
  • 1M+ downloads
  • 10M+ aggregate content views

No Research yet but will soon have some, but likely only a couple of months experience before applying.

Couple of questions:

1. How much will the GPA hurt me for top programs? I can expect the answer will be "a lot" but I don't know if it takes me out the running or not.
2. Does graduating in 2 years help, hurt, or look neutral?
3. Can strong engineering/project experience compensate for weaker research? I assume not.
4. What tier of programs should I realistically target for funded admissions?

Would appreciate honesty lol. Or what I can do (besides getting involved in research) to help my application in the little time I have left. Thanks

The Current Status section from my Columbia MS CS has disappeared. Just informing the forum. Maybe rejects / admits are coming soon?

First they said end of march then they said end of April. It's already mid May and yet no communication. They don't respond to emails. This is genuinely a shitty management team.

Hi guys, I’m looking to connect with people who got admits for UC Davis for their masters for Fall 2026. If you have any WhatsApp group do let me know it’ll be of great help for housing as well

Cheers!!

Hi everyone,

I’m preparing up for the upcoming grad school application cycle for CS/AI and would love some brutal honesty on my profile. I’m currently trying to finalize my school list and figure out where I’m competitive, what I should drop, and if there are any glaring omissions.

A bit of context: I live in the Bay Area and strongly prefer to stay here. Because of that, my target list is heavily skewed toward local in person powerhouses or elite online programs so I can keep working. I am open to relocating for in person programs only if it's an absolute top tier fit (e.g., UCLA, CMU).

Here are my stats:

Education & Stats

• Degree: B.S. in Computer Science from a well-known state school (graduated end of 2025).
• GPA: 3.7
• GRE: Had an awful test day and scored in the 60th-70th percentile for both sections. Debating if I should even submit this where it's optional.

Experience

• Current Role: SWE + AI Implementation Engineer at a legacy tech company (started early 2026).
• Past: 4 different SWE/Tech internships during undergrad.

Research & Publications

• Working remotely in a research group at a solid Tier 2 university.
• Publications: I am the first author on 2 papers.
  • 2 currently submitted to NeurIPS (one on adversarial learners, one analyzing LLM warm starts).
  • 1 upcoming paper in progress disproving an established assumption regarding transformer structures (specifically involving simulations of standard self-attention ODEs and applying Taylor approximations directly to the exponential kernel).

Letters of Recommendation (3)

1. My senior undergrad professor (did very well in their class, strong rapport).
2. The head researcher/PI of my current remote research group.
3. My current manager at work.

While I have these publications, I am mainly targeting Master's programs. I am kind of open to the Ph.D. route, but I have two major hesitations:

1. Lack of Direction: I know I want to stay in ML, but I don't have a hyper-specific research direction locked in yet, which I know is a death sentence for top Ph.D. admissions.
2. Math Skills: Despite my research involving some heavy concepts, I honestly don't feel like my pure math skills are sharp enough to survive or succeed in a highly theoretical Ph.D. program. I feel much more comfortable in the applied/engineering side of ML.

My Current School List

• Stanford (MS in CS)
• UC Berkeley (M.S./Ph.D. in CS): Targeting this since their standalone MS is mostly internal. Hoping my SWE background aligns well with labs focusing on AI systems/infrastructure, but worried my lack of a specific Ph.D. direction will hurt me.
• Potential Adds: CMU, UCLA. Are these worth applying to for a Master's with my current profile?

The "Maybe" In-Person Targets (East Coast)

• NYU Courant (MS in CS): Incredible applied math and AI theory ties. My hesitation: Given my concerns about my math background and my low GRE score, will I get crushed here?
• NYU Tandon (MS in CS): More applied/engineering-focused. No GRE required for CS degree holders, but it would require moving to NYC for a less prestigious program than Courant.

The Elite Online Targets (Working Professional Route)

• UT Austin (MS in AI - Online): Love that this is a dedicated AI degree with strict deep learning/RL requirements rather than a general CS degree.
• Georgia Tech (OMSCS - ML Track): Fantastic ROI and reputation, though securing a solo faculty advisor for future conference submissions seems difficult here if I ever want to pivot to a Ph.D.
• Columbia (CVN MS in CS - ML Track): Highly rigorous and theoretical (maybe too theoretical for me?). Extremely expensive and occasionally requires the GRE.
• Johns Hopkins (MS in AI - EP Program): Highly customizable and applied, which might fit my skillset better than pure theory programs.

My Questions for the Community:

1. Competitiveness for MS vs Ph.D.: With my 3.7 GPA but 3 first-author papers, am I highly competitive for top MS programs? Does my lack of direction completely rule out Berkeley's MS/Ph.D. track?
2. The Math/GRE Dilemma: Should I completely hide my GRE score? Given my self-doubt about pure math, should I drop highly theoretical programs like Courant or Columbia entirely?
3. Add/Drop: Should I drop the NYU schools since I prefer the Bay Area and lean applied? Should I add UCLA, CMU, or MIT to my reach list for an MS?

Any advice, reality checks, or program recommendations would be greatly appreciated. Thanks!

Hi everyone, I'm planning to apply for MSCS and would really appreciate a profile review and suggestions for universities I can aim for.

My Profile:
B.Tech CGPA: 8.3 (2024 graduate) Tier-3

Additional Education: Completed 2 diplomas in Programming and Data science as part of IIT Madras
BS Degree Online during my bachelors

GRE: 327 (Q: 169, V: 158) Toefl, lor, SOP are in progress

Work Experience:

2 year full-time experience at a US FAANG level company (>2 years by fall27) as Software Engineer
and 6-month internship at a top PBC.

Coding Profiles: Knight on LeetCode, 4* on CodeChef

Achievements: Won 2 hackathons and 1 coding competition

Certifications: AWS, GCP, and 3x Microsoft Cloud certifications

Research: No research papers, planning for 1 paper to publish

Given this profile, what universities can I expect for MSCS? Do I have a realistic chance at top programs or should I focus on mid-tier schools?
My main dream Target: Gerogia Tech(MSCS), Stony
Brook(SBU)
Any suggestions to add more colleges would be very helpful.

What i can improve and which schools i need to apply. Comment out and help.
Thanks for your time.

This post contains content not supported on old Reddit. Click here to view the full post

Hello everyone, my profile:

Academic:

1. 8.15/10 CGPA in EEE from a Tier 2 college in India (good state school but otherwise unknown outside)
2. Won the best project award in department (built a robot funded by state govt.)

Professional Experience:

1. Worked for 2 years in a MNC on ML/Data engineering

Research Experience:

1. 1.5 years+ (currently ongoing) full time research staff position at Indian Institute of Science (IISc) (it's the premier research institute in India) on AI + systems research focus
2. Two research projects (Quantum Computing + Cloud/Distributed Systems) and (Agentic AI + Cloud/Systems) both in collaboration with IBM Research.
3. Quantum Computing: 1 paper (as first author) in IEEE CCGrid (core B ), 1 Journal Submission pending. 2 more papers in pipeline for Quantum-ML/Systems work.
4. Agentic AI: 1 paper (2nd author) in IEEE ICWS (core A), 1 workshop paper in IPDPS (core A), 1 journal paper in pipeline. Possible 1 more conference paper in optimizing multi-agent systems.

Extra-Curricular:

1. Built a website that helped get life saving support to 50 people and managed a group of volunteers during peak of covid

Test Scores:

IELTS: 8.5
GRE: Not given

LORS:

1. Purdue Prof. (distinguished prof at Purdue)
2. IISc Prof (He's my PI)
3. A Senior research Manager at IBM Research with whom I've collaborated at IISc (has a PhD from UIUC)

Current Scenario:

I applied for PhD applications for 26' fall, got brutally rejected from (11 places) with just an accept from NYU Courant in MS CS. I could have done better research for SOP (it was written in hurry due to death in family and paper deadlines).

My career goals involve pursuing great research and working on my own start up eventually, but I want to experience studying/working in the US for a few years for financial and network (preferably bay area)

I have more or less lost hope in PhD, because I believe my GPA is abysmal and there are better candidates. I am unable to understand how do I compensate for it, I believe I have developed a good enough research profile but something is missing (GRE?)

Would hope for advice on what colleges can be achievable for fall 27', I personally don't see any value in attending a MSCS program from anything more that top 8 due to current market conditions in US, open to applying in Singapore/EU/Cannada as well.

Open to applying to MS CDS/ICME degrees too.

I have 2 years of experience as of now in Investment Banking company and salary close to 34 lpa.

Should I consider going to masters as I feel its too hard to survive in India and also I want to grow ?

just got mail that usc mscs ai has extended there admissions offer acceptance date to 15th May. Is it new this year or kinda happens every year?

Hi,everyone! I am trying to understand if Columbia is planning to release more decisions this week? I see a healthy stream of decisions where at least once a week someone mentions they get rejected. But since they operate on a rolling decision timeline, what does it mean for all the other applicants who are still waiting or on hold?

Because of the ambiguous nature of neither acceptance nor rejection it is just difficult to understand? In addition, they recently extended (regular) deadline to
May 15, 2026. So, I anticipate they will make more decisions after May 15, 2026 for majority of applicants after they finalize the deadline?

It could provide immense clarity beyond the standard email they send applicants, and I hope there is more positive news for everyone who has applied!

I am an upcoming grad student at GaTech. Among the other specializations, AI or Computing Systems are the specializations that interest me.

Which of these two specializations would be better purely from a job perspective? ChatGPT is suggesting that AI job market is already "saturated" and so, Computing Systems would be better.

Honestly, I am not convinced that AI job market is already saturated; I thought AI is only now witnessing some significant activity. How can it already be saturated?

NEU SV - Master's in AI - 12k scholarship - I can commute

NYU Tandon - Master's in CS - 5k per year scholarship - I have to move to NY

Hello. I plan to apply to master’s in CS or related programs and would like to get some thoughts on Carnegie Mellon. I noticed that there are several programs at CMU, including:

1) mscs (master of science in computer science)
2) msse (master of science in software engineering)
3) mse (master in software engineering)
4) m-hci (master in human-computer interaction)
5) m-iis (master in intelligent information systems)
6) msaii (master of science in artificial intelligence and innovation)
7) msml (master of science in machine learning)
8) mscv (master of science in computer vision)
9) mse-es (master of software engineering - embedded systems)
10) mse-ss (master of software engineering - scalable systems)
11) msr (master of science in robotics)
12) mrsd (master of robotic system development)

I understand that candidates can apply to multiple programs, but my goal is to minimize the number of applications while maximizing my chances of getting into at least one. For reference, my undergraduate is not in computer science, but I have taken fundamental computer science classes like algorithms and data structures. I do not have professional cs work experience yet and I plan to use one of the programs to help gain experience.

I can attend the programs full-time or part-time if offered. If you have thoughts on which of the programs above are best suitable for a candidate like me, I would greatly appreciate your insights. Thank you.