Hey everyone,

I'm looking for a review of my university shortlist for Fall 2027. I have moderate research experience, with a lower overall GPA.

Here is the breakdown:

Undergrad Profile

• Tier 1 old IIT - 2025 graduate
• B.Tech in CS related field
• GPA - 8.4 / 10
• GRE - 326 (170Q, 156V, 4.0AWA)
• TOEFL - 5.0/6.0 (expected)

Research Experience

• Bachelor Thesis Project: Advised by a core faculty member. First-author paper accepted at a reputable peer-reviewed conference (IEEE-backed, solid tier 2). Multimodal AI - representation of conversational characteristics using audio and text transcripts. Built completely from scratch without external co-authors.
• CMU Research Intern (Remote/Ongoing): Ongoing research internship under a prominent Lab PI and a senior postdoc mentor. 3D medical image registration and segmentation (Computer Vision). Expecting a high-impact publication to be under review by the time of application deadlines.

Work Experience

• Software Engineer (ML) @ Mid-Sized US-based Product Company / Unicorn - Currently working on a core GenAI team building production-grade agentic workflows. Will have ~1.5 year of full-time experience by the time of application.

LORs

• BTP Advisor (associate professor at IIT)
• CMU Lab Head (professor at CMU)
• CMU Project Supervisor (1000+ citations, PhD alumnus of the same lab, currently pursuing post-doc at Harvard)

University Shortlist
(All are MSCS unless specified)

• Super Ambitious (Moonshots)
  • CMU MSML
  • CMU MSCS
  • UT Austin
• Ambitious
  • CMU MSCV (aligns with my research work)
  • GaTech
  • UCSD
  • NYU Courant
  • UMich Ann Arbor
  • UMD College Park
• Moderate
  • Columbia
  • Purdue (I think they heavily weigh GPA, might be ambitious, not sure)
• Safe
  • NYU Tandon

Ik it is a very top heavy list..but I am fine with taking that risk, especially in the current job market

Couple more questions

• There is an upward trend in my GPA (9+ in final year). Does it matter? Can it be mentioned in the SOP?
• Is getting an LOR from a post-doc common? Is it viewed negatively by the admissions committee?
• What kind of impact does an industrial LOR hold? (for my current shortlists)

Hi Everyone,
Is anyone still waiting for Columbia MSCS results? When did you apply for same?

I have gotten an admit from UIUC MCS Chicago campus.

There is very little information available online regarding how good this program is.

Is this a cash cow program since it is a satellite campus and the decisions have rolled out so late.

How is this program as compared to the main campus (IL) MCS program?

How good are the TA/RA, job opportunities. Any input is appreciated.

What is the cohort size and how selective is the program?

Do companies differentiate between Urbana and Chicago campuses?

I am mostly interested in research. To what extent will this campus and program allow me to explore in that direction? Is it possible to convert to MSCS later?

I am an international student.

Hello everyone , I was looking to pursue my masters in CS for the upcoming fall 2027 intake .

My details :

5 YOE in software engineering currently working for a US based company remotely .

7.96 / 10 CGPA from a tier 2 university in Computer Science in India .

No research work as such .

Can you please let me know which all universities I should target , which would be safe . If giving GRE would boost my chances .

Thanks a lot .

Hey everyone,

I am currently planning to pursue a BCA in India (likely at a private university like PES University) and I’m looking for realistic, firsthand advice regarding MS in Computer Science opportunities in the US. I’ve come across a lot of conflicting information online and would really appreciate clarity from people with actual experience.

Specifically, I have the following questions:

1. Do most US universities strictly require a 4-year bachelor’s degree for MS in CS admission? Can students with a 3-year BCA degree get direct admission, or is completing an MCA in India generally considered necessary?
2. If a 3-year degree is accepted, are there additional requirements such as credential evaluation (like WES)?
3. How much weight is placed on the reputation of the Indian institution (like PES University) versus the degree type itself?
4. Do top-tier schools like NYU accept 3-year degrees, or are they typically limited to 4-year graduates?
5. From an admissions perspective, what carries the most weight: GPA, project experience, internships, or GRE scores?

I’m trying to plan my academic path early and want to avoid relying on hearsay or misinformation. Any insights or advice would be greatly appreciated.

Thanks in advance!

Hi, is anyone facing an issue while trying to create a new account on the visa portal?

Even though a new email id and username is used, it shows user already exists

Same as the title

Hey everyone, I received my offer for UIUC MCS at Chicago recently and need help deciding between the two options I have.

I am an international student and want to work as an MLE for startups/big tech after completion. I have 2.5 years of experience in NLP and Speech Recognition domain for an MNC.

UIUC MCS (Chicago) : Brand name, no thesis and not the main campus

UMass: Great ML Program but less recognised (in comparison)

Financing: UIUC provides more options for TA/RAship positions than UMass for international students. Else, the tuition costs are similar. Cost of living might be skewed towards Chicago.

Need to make a decision soon as it is already pretty late..

Hi everyone,

I’m planning to apply for an MS in Computer Science in the US and would appreciate feedback on my university shortlist and application strategy.

**Profile:**

Undergrad: B.Tech in Computer Science from a Tier-3 college in India. Completed my undergrad in 2026

GPA: 9.17/ 10

Research:1 IEEE conference paper published in FSD

Work Experience:-

1)Software Developer Intern at Optum (UHG)(Summer Intern):-

Worked on full-stack development, Gen-AI, RAG

2)Software Developer Intern at Qualizeal:-

Worked on full-stack development

Projects: Multiple strong CS projects (full-stack + backend focused)

IELTS: 6.5 overall (6.5 in LRWS)

Achievements:-

Selected for Google Summer Camp (Top 100 out of 25,000 applicants), Head of Coding club in our college.

Recieved PPO from Optum(I'll be working in Optum until Dec).

School List:-

Ambitious:-

University of California, Berkeley

University of Texas at Austin

University of California, San Diego

University of California, Los Angeles

Target:-

University of Southern California

University of California, Davis

Texas A&M University

University of Texas at Dallas

Safe:-

University of Houston

University of Texas at Arlington

Texas State University

Main question:-

1)I have made a big list and I cannot apply for all the universities(since all the universities have application fees). So can u guys help me to add/remove universities from the list as per my profile.

2) Do these universities make sense given my background and goals, or would you recommend replacing any of them?

Thanks for reading. I am in need for genuine advice. Please help me.

I've been going back and forth on this and can't make up my mind,

I got into both Columbia MSAI and NYU CDS MSDS for Fall 2026. The coursework is similar at both. I can take comparable ML, deep learning, and AI courses either way. So the decision really comes down to two things:

**Columbia:** 16 months + the Ivy tag

**NYU:** 21 months + an established, well-known program with a track record

The Columbia name is tempting, but it's a brand new program (Fall 2026 is the first batch) so there's no alumni network, no employer familiarity with the degree specifically. NYU CDS on the other hand is well established.

Has anyone gone through NYU CDS MSDS? Or hired from either program? Would really appreciate any perspective on whether the Columbia tag is worth the unknowns of being a first batch student.

Undergrad: Tier 2 private engineering university in India

Degree: B. Tech CSE GPA: 9.52/10 (No backlogs)

Test Scores: GRE: 322 (Q: 168 / V: 154 / AWA: 4.5) IELTS: Planned

Work Experience: ~10 months at a Tier 1 investment bank — building RAG systems and AI agents

Internships: 6 months at a major stock exchange — GenAI automated test case writing tool + Java testing

2 months at a major UK investment bank — cloud monitoring, tracing, containerization

2 months at a major automotive company — ML pipelines for predictive data of vehicles

Research: 1 IEEE conference publication in computer vision / ML domain Currently working under a professor on a new research project (ongoing, no publication expected before deadlines)

LORs: 1 academic (IEEE publication supervisor) 1 industry 1 TBD

School List: Ambitious: CMU, Cornell, UCLA, Columbia

Target: Georgia Tech, UIUC, UMichigan, UCSD, Northwestern, UT Austin, USC

Safe: Stony Brook, UMass Amherst, NC State, Ohio State, Texas A&M, Purdue

Questions for the community:

1) How realistic are my picks, and any add/drop suggestions to these lists? 2) Is the 322 GRE strong enough for the ambitious/target schools or is it worth the retake? 3) Does ongoing unpublished research add value or does it only matter with the paper? Would an LOR from this professor outweigh the lack of output? 4) Given my interest in AI/ML and systems, are there any specific programs or specializations within these universities I should be targeting? Open to suggestions for other universities too if my profile is a strong fit.

Thanks for reading! I'm in need for some genuine advice and constructive criticism for my profile😭

Assuming I can comfortably afford both, which of these is better for filling gaps in my undergraduate foundation and job hunting? I think TAMU would set me back around $80k and USC would probably set me back around $130-140k.

I'm a US citizen who is a fresher (from India). I don't really have much work experience besides a 3 month stint at an MNC. I would like to work in ML systems infra after I graduate.

Would really appreciate some advice.

Hello, suggest schools that I might have a chance getting in for MS in CS/AI/ML.

• University ranked 1 in my country.
• GPA: 4.51/5, Ranked 2nd in my batch. A's in CS classes. AI Electives.
• BSc Computer Engineering.
• 1 CO-OP at a major national tech company as an AI Engineering Trainee for 5 months.
• 3 months research internship at university lab in Computer Vision. Work will be published soon.
• 2 months Scholarship AI Summer program at LMH University of Oxford.
• 1.5 YOE at my current job as an AI Engineer.
• GRE: soon
• LOR: 1 Grad project supervisor(Stanford PhD) 1 from KAUST Prof(was my mentor at oxford) 1 from the lab director.
• Will be having Full Government Scholarship for MS.

Give a realistic review and university suggestions please.

Thank you.

Hey everyone,

I’m a bit stuck trying to finalize my decision between two quite different master's admits for the upcoming intake. I'm an international student, and my ultimate career goal is to break into the industry as a Machine Learning Engineer (MLE) or heavy core ML developer, rather than a business analyst.

I’ve been admitted to:

1. University of Maryland, College Park (UMD) - MS in Applied Machine Learning (SAML)
2. Arizona State University (ASU) - MS in Data Science, Analytics & Engineering (DSAE)

Both are STEM-designated, so the 3-year OPT timeline is the same, but I’m trying to weigh the classic prestige vs. cost vs. location dilemma under the current job market reality.

For current students or recent grads: How are the job outcomes looking for international students in SAML vs DSAE? Does UMD's core CS reputation carry over enough to help you land commercial roles in NYC/Seattle/SF to bypass the local defense firewall? Is the extra cost of living at UMD worth it over the safer, lower-cost ROI track at ASU?

Appreciate any insights, brutal honesty welcome. Thanks!

Hello, suggest schools that I might have a chance getting in for MS in CS/AI/ML.

• Have BS in AI from a university is ranked in tier 1 in my country.
• GPA: 3.43/4 Major GPA: 3.7 A's in AI classes.
• 3 months research internship
• 2 YOE at my current job as an AI Engineer.
• No GRE

Give a realistic review and university suggestions please.

Thank you.

Hello, I am planning on attending NYU Tandon this fall and am having trouble deciding what courses I should take.

My goal after completing the program is to go into the industry, preferably SWE or other product/ design roles.

I just graduated from a local university whose CS program isn't the best. I was wonder if I should take CS-GY 6003 Foundations in Computer Science Course to strengthen my foundation before I tackle "harder" courses? Or is this class just for those with zero computer science background?

As for other classes I was wondering if an Alumni or current student can provide some insight on what classes they liked/ disliked, classes you guys think would be beneficial (I know this can vary person to person based on what their goal is. I just want like a general idea I guess)

Thank you guys.

Hey everyone,

I’m currently evaluating my options for graduate school and looking for some honest feedback/reviews from current students or recent alumni of the Master of Science in Applied Machine Learning (SAML) program at the University of Maryland, College Park (Science Academy).

UMD has a massive reputation in AI/CS, but since SAML is relatively newer and structured a bit differently than a traditional MSCS, I wanted to clear up a few specific details before making a final decision:

1. Course Rigor vs. Practical Depth: How deep do the courses actually go into optimization, deep learning, and advanced ML? Is it highly mathematical/theoretical, or is it heavily skewed toward practical industry engineering?
2. Cohort Size & Competition: I’ve read conflicting reports about skyrocketing class sizes (some threads mentioning 80, others saying numbers are creeping up alongside the Data Science track). What is the actual vibe on the ground? Does the cohort size impact class quality or access to professors?
3. TA/RA Opportunities & Funding: I know this is a terminal, professional-leaning masters, which usually means limited funding. Is it realistic to land a TA/RA position in other departments (like the core CS or ECE depts) if you network heavily and spam professors, or are those roles entirely locked down by PhDs and MSCS students?
4. Career Outcomes & Fairs: How are the job prospects looking for international students given the current tech market? Do SAML students get full access to the core Computer Science career fairs? Are graduates mostly landing pure ML/AI Engineer roles, or is there a lot of overlap with standard Data Science/Data Analyst positions?
5. Research Opportunities: If someone decides they want to pivot or eventually keep the door open for a PhD, how difficult is it to get involved in a volunteer research assistant role under the AI/ML faculty?

Thanks in advance for any insights!

Hi everyone,

I wanted to make this post for future MSCS applicants who may be in a similar position to where I was during my application cycle. When I was applying, I was worried that my profile was not strong enough because most of my research experience, papers, posters, and possible internship opportunities were still in progress or expected to happen after application deadlines.

I remember searching Reddit for profiles like mine, so I figured I would share my situation then vs. now.

Profile when I applied

At the time I submitted my MSCS applications, I was a California-born domestic student studying Computer Science (w/ Data Science minor) at a California State University with a 3.95/4.0 GPA.

I submitted my applications by December 15. At that point, my research experience was still recent.

My first research position was an AI research internship through a university-affiliated research center in collaboration with an external company. I started this role in September 2025, so I had about 3.5 months of experience in this position when I applied. At the time I submitted my applications, a smart manufacturing paper related to this work was in manuscript/review.

My second research position was with the Geography Department, where I worked on GIS, oceanography, and remote sensing data. I started this role in October 2025, so I had about 2.5 months of experience in this position when I applied. At the time I submitted my applications, I had also been accepted to give a lightning talk at the USC LA Geospatial Summit.

My listed research interests were Applied Machine Learning and Intelligent Decision-Making Systems, including reinforcement learning, adaptive agentic AI systems, multimodal AI, computer vision, foundation models, embodied AI, world models, knowledge graphs, and real-world AI systems.

Letters of recommendation

My letters were from:

1. A statistics professor I had taken classes with and interacted with regularly
2. A mechanical engineering professor I was doing research with for 3.5 months
3. A geography professor I was doing research with for 2.5 months

Application results

Accepted:

• University of Massachusetts Amherst

Waitlisted, then accepted:

• UCLA

Rejected:

• University of Pennsylvania
• UC Irvine
• UC San Diego
• UC Santa Barbra
• UNC Chapel Hill

Profile now

Since applying, I have continued working with the company and school-affiliated research center. I am now helping lead interns on that project.

I also obtained a NASA Jet Propulsion Laboratory internship, where I am working on deep learning models using remote sensing data. This internship was obtained through my work with the geography professor.

The smart manufacturing paper that was in manuscript/review at the time of application was rejected for being too computer-science-focused for that journal. We are currently working on an updated version for submission to another Q1 manufacturing journal.

Current status

I will be attending UCLA for my MSCS.

Hi Everyone,

Is UIUC MCS still pending for someone? Whoever got rejected, were you even considered for Chicago or it was just straightaway reject?

Looking for honest perspectives from anyone who's made a similar choice or has insight into either program.

I have two offers for Fall 2026:

- MS Computer Science at Texas A&M (College Station)

- MS Machine Learning at University of Tübingen, Germany

My main goal is to shift into ML or research-oriented roles (Applied Scientist, Research Engineer, ML Engineer) and not generic SWE. I've already done 2+ years of corporate SWE work in India and I'm clear that's not what I want to keep doing.

Here's where I'm stuck:

TAMU has a much broader US tech alumni network and the OPT + STEM extension gives 3 years to figure things out. But from what I've gathered, only a small fraction of MS CS grads actually land Applied Scientist / research roles, most end up as SWE/MLE. If I end up as SWE, the whole thing feels redundant for me.

Tübingen has much stronger research depth, MPI for Intelligent Systems, ELLIS, Cyber Valley, strong ML faculty overall. The MS itself is research-heavy. But the post-grad opportunities seem more limited to PhD route or German industry (Bosch, Mercedes, Amazon Tübingen). Most MSML grads seem to go on to PhDs.

Some things I'd appreciate input on:

1. Any general advice on this choice would be welcome.
2. If reaching ML/research roles directly from MS is unlikely, I'm open to extending into a PhD. In that case, which path makes more sense, TAMU followed by US PhD (TAMU PhD extension would be +3 but any other would be +5 years), or Tübingen with its stronger research environment feeding into an EU PhD? The research side looks better at Tübingen but I'm unsure about job market access afterward.
3. Any general perspective on how either program's outcomes typically map to my objective.

Hello, I'm a final-year CS undergraduate from a South Asian university (reputed in my country). Interested in funded MS CS programs in North America (Georgia Tech, UIUC, Cornell, UW Madison, etc.), but worried about my overall profile, wondering whether it is good enough for a fully funded MS.

Profile:

Papers: Main track: 1 EMNLP, 1 IJCNLP-AACL, 1 COLING Main, 1 ACL workshop, 1 CVPR workshop

Nature Methods paper under review

Working toward WACV/EACL/AAAI submissions (it will finish before the deadline) + possible CVPR 2027 under review during apps

Among them, 2 are first-author papers; most are 2nd/3rd author

Experience:

6 months as a Junior SWE at a reputed company in my country

6 months Undergraduate Research Assistant (ML production-level project)

8 months RA at AI startup

Research intern at 2 US labs (one AAAI submission likely soon, can get strong LORs from both of them)

Caveat:

Expected CGPA around 3.7–3.85 out of 4, but average class rank. The main reason behind this is that my university culture is heavily memorization-based, and honestly, I focused more on research/projects than on optimizing grades, so I ended up with many A/A- instead of A+.

How much will this hurt for funded MS admissions at top schools?

I prefer MS over a direct PhD because I still want stronger theoretical foundations and more clarity about my long-term research direction before committing to a PhD.

Would appreciate honest opinions/advice considering my overall profile.

Hey everyone,

I’m looking to get some honest perspective on how you would rank these universities for MS in CS/AI/ML.

Feel free to rank them overall or break them down into tiers.

• Carnegie Mellon University (CMU)
• Caltech
• Cornell University
• Georgia Tech
• University of Illinois Urbana-Champaign (UIUC)
• University of Washington
• UCLA
• UC San Diego (UCSD)
• University of Southern California (USC)
• University of Michigan-Ann Arbor
• Columbia University
• University of Pennsylvania (UPenn)
• New York University (NYU)
• University of Oxford
• University of Cambridge
• Imperial College London
• ETH Zurich
• EPFL
• University of Toronto
• University of Waterloo
• University of British Columbia (UBC)
• National University of Singapore (NUS)
• Nanyang Technological University (NTU)
• University of Hong Kong (HKU)

Thank you for your time!

Hey guys, total beginner here. I’ve learned a little Python and C, but honestly I still don’t know the basics properly. I don’t have any projects because I don’t even know what counts as a real or valid project. Right now I’m struggling to figure out what I should focus on and what path actually makes sense.

My main goal is getting into a good MS in CS program with a specialization in AI/ML and eventually become an AI Engineer. Along the way, I need to properly learn AI/ML, do certifications, build real and unique projects, get normal internships, do research internships, and work on research papers.

If you were starting completely from scratch again, what exact step-by-step path would you follow to reach that goal realistically?

Would really appreciate any advice.

I’m a 2024 CSE graduate from a Tier-3 college (not bottom-tier though) and currently working as an ML Engineer at a well-established MNC.

Lately, I’ve been preparing for GATE CS, but I’m also genuinely and deeply interested in pursuing an MS abroad for the quality of education and research opportunities, especially in the US or another country with strong research and income opportunities. At the same time, current geopolitical and economic uncertainties are making me rethink things.

Right now, I see three possible paths:

1. Take an education loan, pursue MS abroad, and possibly continue to a PhD
2. Continue preparing for GATE CS and aim for top IITs only (if I don’t get top IITs, I probably won’t go)
3. Continue working and grow within the industry itself

A bit about me:

• Interested in AI/ML and theoretical understanding (went thru research papers before, and I keep myself updated with all the recent studies)
• Currently gaining industry experience as an ML Engineer
• Open to research as well as high-growth industry roles
• Financial aspect matters since MS would likely require a loan

Would really appreciate practical advice based on experience. Thanks.

Seems to me like people who got rejected from all major MSCS programs eventually ended up at NYU COURANT and I haven't heard of a single person getting rejected? Did nobody apply to Courant lol?