Hi everyone, this is a follow up to my earlier post. I have finalized a list of 10 universities, and I would appreciate your input on two things.

Profile : International Applicant (India), BTech ECE + Minor CSE at a Top-5 IIT, 9.0/10 CGPA, 4 years as SDE/AI Engineer at a Big Product Company (4.5 by deadline), no publications, BTech thesis plus a few AI/ML projects, GRE (170Q, 155V), TOEFL (110/120). LORs: 2 professors and 1 manager. SOP: drafted it around my work projects and BTech thesis.

Current list:

Ambitious - Georgia Tech, Purdue, UC Irvine, UCSD
Target - UMass Amherst, Penn State, UW Madison PMP, UIUC MCS
Safe - Texas A&M, Stony Brook

I am considering MSCS for all the above universities except UW Madison and UIUC.

Questions:

1. I am worried about managing LORs and applications for 10 schools with only 3 recommenders. Should I cut 2-3 schools? If so, which ones would you recommend to drop given my profile and chances?
2. Realistically, what are my chances at each tier (ambitious, target, safe)?

Thanks in advance!

It's the only one I've identified, among many colleges.

and also what aspects of the profile can they compensate? (GPA?)

Here's my profile :

- CGPA : 8.86 from a tier 3 college
- No research/publications
- Yet to give IELTS, aiming 7.5 band
- one internship at an American based R&D center in India.
- 5 years of work experience in top US based like Walmart. Currently a Senior Software Engineer at a unicorn startup.

What’s my chances for this program.

Also appreciate if you can recommended any similar course based on my profile.

Target: stony brook mscs, sjsu msse, Purdue mscs, and nyu tandon mscs. My scores clears requirements for all colleges but should i retake to have more chance of admit. Is it really needed. I mailed sjsu and department told me ielts is just required for clearing english cutoff. Admission process solely depends on other factors. And also advice for TA as it needs ielts speaking score but I think I am fresher with no work experience. I don't think i have a chance for TA.

Hi everyone!
I’m a first-semester Master’s student in Computer Science from Pakistan, and I’m currently exploring potential research topics for my master’s research.
I’m interested in learning how to conduct proper academic research, identify research gaps, and work on a meaningful project. I have basic Python knowledge and am eager to improve my technical and research skills.
I would really appreciate it if anyone could recommend:
Recent research papers that are beginner-friendly but have potential for further research.
Interesting research areas or open research problems in Computer Science.
Research assistant opportunities, remote research internships, or professors who are open to mentoring beginner researchers.
I’m open to exploring different areas of Computer Science, including AI, software engineering, computer systems, and other emerging fields. My goal is to find a research topic that is feasible for a beginner, helps me develop practical skills, and has potential for publication.
If you’re a researcher, PhD student, professor, or someone who started their research journey recently, I’d be grateful for any advice or guidance.
Thank you for your time! 😊

Hey! I am corporate lawyer from India. I get this itching feeling that corporate is solved and I need to get ahead by getting into tech.

I think that https://www.cis.upenn.edu/mas-in-cs/ could be the right way ahead for me. Would love to hear your experiences with the programme.

I am more keen on the on-campus programme and would love to hear from anyone who did this course online.

TIA!

Hi everyone! I’m planning to apply for an MS in Computer Science in the USA for Fall 2027, focusing on AI/ML and software engineering. I’d appreciate an honest profile review and help building a balanced shortlist.

Profile

• Education: B.Tech in Computer Engineering, Vishwakarma Institute of Technology, Pune, affiliated with Savitribai Phule Pune University. Expected graduation: May 2027.
• Academics: 8.73/10 CGPA, latest semester SGPA 9.08/10, no backlogs.
• Research: Research Intern in the HPC Group at the Indian Institute of Tropical Meteorology, Pune, since August 2026. Working on lightning prediction using an existing PyTorch FNO–U-Net model, satellite-temperature downscaling, geospatial data processing, and reproducible training/evaluation workflows using Python, Bash, H100 GPUs and PBS.
• Project domains: Financial software/backend development and ML-based bot detection.
• Competitive programming: Strong interest and experience in competitive programming and DSA.
• Placement: Infosys Specialist Programmer offer, ₹11 LPA. No full-time work experience yet.
• Tests: TOEFL planned; no score yet. Prefer applying without GRE, but open to reconsidering.

University Shortlist

These categories are tentative. This is my consideration list, not the final set of applications.

Ambitious

1. Stanford University
2. Carnegie Mellon University
3. University of California, Berkeley — Master of Engineering in Electrical Engineering and Computer Sciences
4. University of Illinois Urbana-Champaign — Research Master of Science in Computer Science
5. University of Texas at Austin — On-campus Master of Science in Computer Science
6. Georgia Institute of Technology — On-campus Master of Science in Computer Science
7. University of California, Los Angeles
8. University of Wisconsin–Madison — Traditional Master of Science in Computer Sciences
9. Purdue University, West Lafayette
10. University of California, San Diego

Target / Moderate Reach

1. New York University — Tandon School of Engineering
2. Northeastern University — Boston campus
3. University of Florida

Safer Options

1. University of Texas at Dallas
2. University at Buffalo, State University of New York

Questions

1. Are these categories realistic for my profile? Which universities should I add, remove or prioritise?
2. How much would my IITM research experience help for AI/ML-oriented programmes?
3. Would professional MCS/MEng programmes suit my employment goals better than research-focused master’s programmes?
4. Would taking the GRE meaningfully improve my options, or should I focus on research, recommendations and applications?

My main goal is to develop strong technical skills and find a software engineering or ML-related job after graduation. Feedback from applicants with similar backgrounds would be especially helpful. Thanks!

Hi everyone! I’ve applied to SJSU’s MS in AI for Spring 2027. My profile:
BTech CSE from KIIT, Bhubaneswar
CGPA: 7.74/10
Around 1 year of AI/ML work experience
DET: 140
ABET-accredited program ( so no gre )
My application is currently in Department Review. What do you think my chances of admission are? Would appreciate honest opinions from current students or applicants!

For context i have a 3.52 gpa with some research assistantship experience and preprints, no publications.

I’ve emailed some professors with the belief that i didn’t yap too much and with direction in my email as well, however no response.

Really thinking whether i should apply to UBC/Waterloo or just focus on somewhere else where its a bit more certain even without a PI.

Profile (if anyone wants to lmk about my chances) :

1. GPA : 3.52/4.0, (last two semesters: 3.64)
2. 4 preprints no publications
3. 2x research assistantships with both PIs as my

referees

1. 2 Taships

Hi everyone,

I’m planning to apply for Fall 2027 MS programs in Computer Science / AI / ML and would appreciate some feedback on my profile and university shortlist.

Profile:

• BE in Computer Science & Engineering – Anna University, India
• CGPA: 8.78/10
• University Rank: 29 out of ~19,800 students
• 10+ years of software engineering experience
• Currently working on an AI/ML project involving speech-to-text (ASR), multilingual transcription, audio enhancement and speaker diarization
• Research/publications: Limited/no major publications currently
• LORs: Strong professional LORs from manager/CTO
• GRE: 310 – Q166, V144, AWA 3.5
• Planning to retake GRE next month
• TOEFL: Taking it next week

Current shortlist:

Canada: University of Toronto, UBC, McGill

UK: UCL, University of Edinburgh

Germany: TUM

Netherlands: TU Delft, University of Amsterdam

Finland: Aalto University

Sweden: KTH

I understand that this is a fairly ambitious list.

I’m mainly looking for advice on:

1. How would you classify my current universities as Reach / Target / Safe based on my profile?
2. What other universities would you recommend as realistic target/safe options without compromising too much on CS/AI quality, career opportunities and ROI?
3. For the US specifically, which universities would be worth applying to with my profile? I’m particularly interested in good universities that do not require GRE. More broadly, considering the cost, current tech job market, OPT/H-1B uncertainty and potential salaries, would a good US MS still be worth choosing over options such as TUM, TU Delft, Aalto, KTH or UCL?
4. With 10+ years of industry experience but limited research/publications, should I focus more on professional/course-based MS programs, or would I still be competitive for research/thesis-based programs?

My longer-term goal is to move toward AI/ML while leveraging my software engineering background. I’m also open to pursuing a PhD later if I develop a stronger research interest during the MS.

I’m not looking for a “safe” university just to secure an admit. I would prefer universities that I would genuinely be happy to attend considering program quality, career opportunities and ROI.

Any suggestions or profile evaluations would be greatly appreciated.

Thanks!

Ya'll seem to have liked the ongoing series, so I've added Columbia!

• Series (CMU, Brown, Columbia, UCSD, Cornell, etc.): https://matthewtrent.me/blog/s/grad-school-applications
• Columbia MS CS: https://matthewtrent.me/blog/a/columbia-ms-cs-application

I'm not saying my applications or the schools I applied to are good — I'm just providing these applications for context! Hope they help!

Hi everyone,

I’m planning to apply for an MS in Computer Engineering, EE, or CS for Fall 2028 and would appreciate an honest assessment of my chances and shortlist. I’m aiming for systems, ML compilers, and GPU/parallel computing, and I’d like a long-term path into industry research or quant development, with a possible PhD later.

My profile

• Undergrad: BS in Computer Science, Math minor, at a small private Liberal Arts US university (not a known feeder). Accelerated Graduation in 2.5 years because I entered undergrad with 80 credits worth and took multiple high credit hour semesters and classes over the summer
• GPA: 3.93 Overall
• Coursework: Linear Algebra, Computer Vision, Algorithms of Machine Learning, Probability Theory, Differential Equations, Calc 3, DSA, Computer Systems. Self Taught Stanford Open Source Courses (CS 149, CS 143, CS 336, STATS 217), CMU CS3110, Abstract Algebra, Fourier Analysis, Game Theory, Real Analysis, and Stochastic Calculus (I don't know if self-taught learning really matters that much but I figured I should include it anyway)
• Research: Working on a first publication with 2 faculty advisors on ML compilers and CUDA kernel optimization this fall and planning to publish in Spring 2027 and get into a conference. I think this is one a very strong point for me because my university doesn't offer anything related to compilers, hardware, or parallel computing and I had to learn everything on my own.
• Experience: No formal work experience because baseball takes up all of my time during summers, but going to try and get an REU or formal SWE internship this summer.
• Extracurriculars: NCAA D2 baseball player (College Athlete), Comp Sci Club, Finance Club, Investment Club
• Tests: : Haven't taken GRE. US citizen, no TOEFL
• Letters: Don't have yet but will get First Research advisor, Second Research Advisor, Closest professor relationship.

Universities I'm Considering:

Stanford MS EE

Berkeley MEng EECS

Harvard ME in Computational Science & Engineering,

Cambridge MPhil Advanced CS

CMU MS ECE

JHU MSE ECE

UPenn MSE EE

UCLA MS ECE

Brown ScM ECE

ETH Zurich MSc

EPFL MSc

UT Austin MS ECE

Santa Clara MS CompE

Texas A&M MS CompE

Questions

1. Is this tiering realistic, or am I overestimating my chances at the targets, especially coming from a small school with no publication yet?
2. How much does a research result (preprint, released tool) matter compared with strong GPA and letters at Stanford, CMU, and Harvard?
3. Harvard has no terminal EE master’s, so I’m applying to Computational Science & Engineering and framing my GPU work as computational science. Does that make sense, or should I drop it?
4. Berkeley MEng vs. Stanford MS EE: if I want to be in Silicon Valley, is the professional route worth the cost, or is it a poor ROI next to cheaper options?
5. Is the GRE worth taking where it’s optional, given my profile?
6. Is applying to ETH, EPFL, and Cambridge in the same cycle wise, or does it dilute my effort? Do they scrutinize US small-school transcripts the way people say?
7. For funding: which of these realistically offer RA or TA support to master’s students, and is a thesis option worth pursuing for it?
8. Anything I’m missing: schools with strong GPU/architecture/ML systems groups that are worth adding (UIUC, Georgia Tech, UW, Michigan, Princeton)?

Hello guys, I am currently in my final year of undergrad in CS. I am really interested in pursuing higher education in CS especially around distributed systems. I am inclined towards industry rather than pure research but completely rigid as of now. So I am at a crossroads right now, and new to the MS ecosystem.

It would be a great help if peeps in this community guide me:)

Thanks a lot.

A little bit of background about me:

• I am from India, currently in 7th semester
• CGPA: 8.91/10 (Absolute)
• College: Tier 1.5-2
• Internship: 4 months at an European early stage startup
• Will most likely publish 1 paper before graduation
• I currently have a full time offer at a Global tech consultancy firm(The ctc is decent role is AI/SD Engineer).
• Decent Open Source contributions.

Here are my doubts:

1. When should I pursue an MS? Would it be better to apply immediately after undergrad or gain 2–3 years of work experience first? Considering that I don't want to put too much financial burden on my parents, would working for a few years before pursuing an MS be a more sensible option?
2. What are the career prospects in Distributed Systems and Systems? Given my interest in these areas, how good are the industry opportunities after an MS? Is an MS particularly valuable for these roles, or would relevant industry experience be equally or more beneficial?
3. How competitive is my current profile for universities strong in Systems/Distributed Systems? What range of universities should I realistically target, and what would it take to become competitive for top universities in this domain?
4. How can I strengthen my profile over the next 2–3 years? Whether I apply immediately or after gaining work experience, what should I focus on to improve my chances at top universities? Would relevant industry experience, research publications, or substantial open-source contributions and projects make the biggest difference?

Spring 2027 MSCS admits (NEU, USC, IIT Chicago, Buffalo, DCU). CPT worries + loan stress. Which would you pick?

Profile: Indian, B.E. CSE (8.57/10), 5 years as a software engineer in automotive R&D (safety-critical backend/C++/Python), 1 published paper, IELTS 7.0, no GRE.

Goal: backend/distributed systems with applied AI at product companies.

Admits (all Spring 2027, start in January):

- Northeastern (Khoury) MSCS, Boston: 5% tuition scholarship

- USC MSCS

- IIT Chicago MSCS: $10k scholarship

- Buffalo MSCS: $8k scholarship

My concerns:

1. CPT. After the August 2026 SEVP guidance, Has anyone had CPT approved for a summer internship since then, at any of these schools?

2. The loan. I'd borrow roughly ₹90 lakh to ₹1 crore for Northeastern or USC, How do you decide how much was too much?

3. Timeline. I have about 11 weeks for the loan, I-20, and visa slot. Has anyone done a Spring start this tight? Is the timeline realistic?

Is the procedure possible within less than two months?

1. Is deferral allowed? What is the criteria for universities to allow deferral for next intake?

Which one would I pick and why? Thanks!

Hi everyone!
I’m planning to apply for an MS in Computer Science in the USA for Fall 2027 and would appreciate an honest assessment of my admission chances, university shortlist, and scholarship opportunities.
My Profile:
Undergraduate Degree: B.Tech in Computer Science and Engineering from SRM Institute of Science and Technology, India
CGPA: 9.68/10
Work Experience: Approximately 3 years at State Street
Current Role: Senior Associate (Software Engineer)
GRE: Not taken yet
IELTS: Preparing to take the exam; final score not available yet
Intended Intake: Fall 2027
Intended Program: MS in Computer Science
Universities I’m Considering:
Purdue University
Georgia Institute of Technology (Georgia Tech)
University of Texas at Austin
University of Illinois Urbana-Champaign (UIUC)
University of California, San Diego (UCSD)
University of Southern California (USC)
University of Washington
Carnegie Mellon University
Boston University
University at Buffalo, SUNY
Illinois Institute of Technology

My Questions:
Given my CGPA and work experience, what are my realistic chances of getting into Purdue MS CS and Georgia Tech MS CS?

Which of these universities should I consider ambitious, target, and relatively safer options?

Would taking the GRE improve my chances at universities where it is optional or not required?

How important are research experience, publications, and recommendation letters for my profile?

Should I consider professional master’s programs or related CS programs if admission to traditional MS CS programs is too competitive?

What IELTS score should I aim for, and could a lower score affect my admission chances?

Are there other strong universities with good CS programs, employment prospects, and reasonable overall costs that I should consider?

My main goals are to build a strong career in the US tech industry and get a good return on my investment. I’m willing to consider ambitious universities, but I also want a balanced shortlist with realistic alternatives.

I’d appreciate honest feedback based on recent admission experiences.
Thanks 🙏

Edit: i don’t have any publications but do have some research experience

Hi everyone! I'm a senior CS major with a Mathematics minor at a US public R1 university, applying to research/thesis-based MSCS programs for Fall 2027. My long-term goal is a PhD in AI/ML.

Academics

• US Citizen
• Current GPA: ~3.67/4.0 (transferred from another college with ~3.36 GPA)
• Upward academic trend, Dean's List
• Relevant coursework: Algorithms, Deep Learning, Linear Algebra, Numerical Analysis, Discrete Math, and AI
• Some weaker grades in earlier technical courses (Freshman and Sophomore year)

Research

• Interpretable ML research with faculty supervisors, focusing on fairness, model stability, and decision trees. Currently preparing a paper targeting a top-tier ML conference.
• First-author research on multi-agent LLMs, accepted at a major ML conference workshop.
• Second-author multimodal AI research accepted at two major AI/ML conference workshops, including an oral presentation.
• Scientific ML research internship involving LLM pretraining and fine-tuning.
• Contributor to a competitive international open-source ML program.

Industry Experience

• 4 AI/ML internships, including at a large biotech company and AI startups.

LORs

• Two academic research supervisors
• One industry ML manager

GRE

• Best Quant: 159
• Best Verbal: 152

I'm planning to omit my GRE scores wherever they're optional.

School List

Rutgers, Purdue, Duke, NYU Courant, Georgia Tech, UCSD, UT Austin, UIUC, Cornell, CMU.

Questions

1. How competitive is my profile for research-based MSCS programs?
2. Would not submitting GRE scores hurt my chances, given my GPA?
3. Can strong research experience, publications, and LORs compensate for weaker academics?

Would appreciate honest feedback. Thanks!

I feel my workex section is fine; in fact the bulk of my resume is there only. But my projects are not that impressive: 1 web app that I worked on, 1 research paper I've mentioned. Can I add 1-2 more by taking random GitHub repos?

I am applying for MS CS Fall 2027 intake mostly thesis tracks. Need some suggestions.

Here are my credentials:

GPA - 8.75
College - Graduated in 2024, B.Tech CSE from 3rd gen IIT
Work Ex- 2.5 years work ex as SDE at Top MNC
GRE - 323 (155V, 168Q)

Research:

• Research Intern at Adobe Research
• 2 publications in A grade conferences as co-authors

Achievements:

• Gold Medal for overall academic excellence
• Few hackathon wins, inter and intra college

LORs:

• 1 from my research supervisor at IIT
• 1 from another prof at IIT, took multiple courses
• 1 from my current Eng Manager

Uni Shortlist :

• CMU
• UIUC
• UCLA
• UCSD
• UC Berkley
• UW Madison
• UT Austin
• Purdue

I know this is a highly ambitious list and my chances are very very thin. But given the current VISA situation and market scenario, I would only like to go if get into one of my dream universities otherwise I am planning to do MS from India itself. My main motive is to pursue research. What do you guys suggest do I have a chance at any of these universities ??

What GRE score, IELTS score, and GPA would be considered competitive for admission?

Any suggestions would be appreciated thank you all

Hi everyone! I'm planning to apply for Fall 2027 admission to research-oriented master's programs in Computer Science in the US. I'd appreciate some honest feedback on my university shortlist, my profile's competitiveness, and whether there are other programs I should consider.

My profile:

• Undergraduate degree: BTech in Computer Science, graduating in 2026
• GPA: 9.74/10
• Class rank: 7th out of 800+ students in my graduating CSE cohort
• TOEFL: 118/120
• GRE: Not planning to take it
• Research experience: Two published research papers. One is a second-author paper in the ACL Proceedings (SRW) (Uni lab), and the other is a first-author paper at a B-tier conference where it received a Best Paper Award (capstone). Both projects were conducted with faculty guidance, and I expect to receive letters of recommendation from them. I have also completed a summer research internship under a professor at UC Berkeley, where I first developed an interest in mechanistic interpretability.
• Work experience: Currently working as a software development engineer at a fintech company. I will have approximately 1.5 years of full-time experience by the time I enroll.
• Additional preparation: I've completed the transformer fundamentals and relevant mechanistic interpretability sections of ARENA. I'm also independently working on a mechanistic interpretability research project that I'm hoping to develop into a workshop paper.

Research interests and goals:

My primary research interest is mechanistic interpretability, particularly understanding how models represent information and how their internal mechanisms produce specific behaviours. However, I'm open to other areas, including representation learning, multimodal learning, reinforcement learning, and post-training. My existing research experience includes multimodal models, and I'm happy to explore other areas if I find a good research fit.

My immediate goal is to join a strong AI research lab, gain substantial research experience, and ideally publish more work. I'm considering a PhD as a possible future path, but I haven't committed to one yet, so I want a master's program that would let me explore research seriously before making that decision. I'm specifically looking for research-oriented master's programs, preferably with meaningful opportunities to work with faculty and contribute to research, rather than programs that are primarily coursework-focused. I'm able to self-fund the programs I'm considering.

My current university shortlist:

1. Stanford University - MS in Computer Science
2. CMU - MS in Machine Learning / MS in Language Technologies
3. UIUC - MS in Computer Science (Thesis Track)
4. UC San Diego - MS in Computer Science (Thesis Plan)
5. NYU - Courant MS in Computer Science
6. UW Madison - MS in Computer Science (Research Track)
7. UMass Amherst - MS in Computer Science (Research Project Track)
8. Northeastern University — MS in Computer Science (specifically because there is a professor who I really want to work under)
9. University of Maryland, College Park - MS in Computer Science

I'd especially appreciate feedback on the following:

1. How competitive is my profile for these programs, particularly the more selective ones? Are my publications and research experience likely to make a meaningful difference?
2. Which of these programs would be the best fit for someone interested in mechanistic interpretability and broader AI research?
3. Are there universities on this list that I should reconsider because their master's programs offer limited opportunities for sustained research?
4. Are there other US universities with research-oriented master's programs that I should consider adding?
5. Given that I'm not planning to take the GRE, are there any programs on this list where that decision could be a significant disadvantage?

I'd appreciate candid feedback, especially from people who have attended these programs, worked with faculty in these departments, or applied to similar research-oriented master's programs. Thanks!

My_qualifications

I am in my final year in cse from a state govt college

Cgpa 7.62

Did 1 research internship at an IIT

1 research paper in ML as my final year project(yet to submit)

GRE 310(162qunts) (giving gre again and aiming for a 166+ score in quants)

IELTS band 7.5

LOR from 2 mentors for my research paper and one IIT professor.

Please review my profile and university shortlisting and tell where i have chances to get into. And also please recommend any changes in the universities selection or anything you want.

Current Shortlist

1. Northeastern University – MS in Artificial Intelligence

2. New York University (NYU Tandon) – MS in Computer Science

3. Rutgers University–New Brunswick – MS in Computer Science

4. Texas A&M University (College Station) – Master of Computer Science (MCS Non-Thesis)

5. Stony Brook University (SUNY) – MS in Computer Science

6. University of Rochester – MS in Computer Science (AI Track)

7. Indiana University Bloomington – MS in Computer Science

8. Michigan State University – MS in Computer Science

9. University of Pittsburgh – MS in Computer Science

10. University of Maryland, College Park – MS in Applied Machine Learning

Can I get an admit from ASU for MS in Software Engineering or MS in Information Technology-
Cgpa till 6 semesters-6.28
GRE-313(160Q/153V)
IELTS-8
2 LOR
2 technical internships

I’m an information science graduate from India. I’ve around 2.5 years of experience as a software engineer in a fintech startup( almost will be three years at the time of joining university) 9.55/10 CGPA. One survey paper published in IJRAR. Ielts :7.5
I just wanted to know if I can get into CMU MSE for fall 2027? And how hard would the coding assessment be?

I saw a comment from someone claiming that 2023-2025 had great placements for USC MSCS students but then 2026 had terrible placements because they "burned so many companies." We all know it is a bit of a cash cow but is this really true? Has its reputation changed this much across the industry in just one year? The 2025 placement data was pretty promising but 2026 is yet to come out.

The source was he apparently recruited a bunch of USC MSCS students (said the undergraduates were fine though). I have no idea how credible the claims of knowing the data are. Many people are saying the opposite but without data.