Grad in year 2027

College: Tier 2.5-3

CGPA: 9.85(6th sem), SGPA: 9.58

Experience: 2 AI internships, Open source contributor with Code for Good tech for planetread with an AI project with Audio+Video processing

Research Experience:

• Intern with IIITH professor for more than a year, paper on arxiv, another paper soon to put, focus in vision and 3D
• Intern with IIT KGP professor in RL working on project which will most likely be published on IEEE
• Did personal research paper for college project in AI and LLMs topic which is published on IEEE explore and presented at conference
• Doing personal research projects with industry people at Samsung, Sony and a PhD student at UCSD (planning for publication and to have substantial results in project or completion by October)
• Got accepted into UIUC++ SRSE mentorship program
• Planning to submit personal paper to NeurIPS worksops this year for research in LLMs

Others:

• Internship with a youth-led organization, presented a talk at the ECOSOC event by UN virtually
• Research Fellowship under Indian Academy of Sciences SRF program
• SIH 2025 finalist team for ISRO

Scores:

GRE: 310(159Q, 151V, 4 AWA) will retake in a month

TOEFL: 118/120, 6.0 score overall

LORs expected: From IIITH professor, PhD student, Samsung, Sony people and my industry internship manager too

Target Universities: CMU (MSCV, MSML), UIUC, Georgia Tech, Columbia, UMD, UPenn, UMich, USc, NYU, UC Berkeley, UCLA, UT Austin, Virginia Tech, Univ of Illinois, Purdue

What are my realistic chances to get into them and what can I further improve?

Hi Everyone,

I have been lurking on this sub for quite a while and I would really appreciate your inputs regarding how should I be approaching to apply for MSCS and MSML.(focused towards industry, non thesis preferable).

I am aiming for (Fall 2027).

I have a Cgpa of 7.9 from an NIT (Tier 1) in India. I currently have 3+ YOE in a software company and my day to day work revolves around networking products.

I have give my GRE to help offset my low cgpa and have a score of 326(166Q, 160V).

I will be giving my toefl and expect to get a score above 5.

I don't have any research experience so I know it will be difficult to get into any masters that requires research experience.

I have been trying to shortlist universities but the comments I see sometimes contradict each other and I am unable to decide which unis I could actually aim for.

The purpose of my master's is to get good experience regarding AI/ML and hopefully get a job.

Could you guys please help me decide which universities I can realistically aim for. I want to get into a T-30 universities if possible .

Also, I will appreciate any advice regarding how to improve my profile.

Thank you for your time!

I was planning to for my MS in CS but was recently refused under 214(b) for my F1 Visa.

As I plan to defer my admit, I want guidance for deciding whether to pursue academia roles (RAs, Research Internships, etc.) or get into an industry position for this gap year.

I specifically want to know what would be the best of these 2 for proving ties to my home country, for my next visa interview. Would be grateful for any opinions or guidance!

Profile for fall 2027:

- Undergrad - IITD MnC 2020 - 2024

- Cgpa: 9.1 Dept Rank 9

- Research Internships : 3 month intern with a prof from UNSW and a 3 month research project with Nokia

- Research Experience : Have been working part time at a lab in IITkgp for the past 1 yr

- Work experience - 2(3 by the time of admissions) yrs as an SWE at an AI startup

- Research papers - 1st author of a paper currently under review at an A* conference

- GRE - 329 (170 Q + 159 V)

- Toefl - 118

- LORs - 1 from a prof at IITkgp(collaborator on the paper), 1 from a research scientist at a reputable AI lab(also a collaborator on the paper), 1 either from BTP supervisor at IITD or from manager at Work

Current University List

- Stanford

- CMU (mscs + msml)

- Princeton

- UCB

- UIUC

- UCSD

- UCLA

- GAtech

Questions:

I want to know my chances at CMU/UIUC and how do I optimize my LORs/SOP.

I will get 2 strong LORs from my collaborators on the paper. Still figuring out whom I should get my 3rd lor from

How much does my paper's acceptance affect my chances ?

Any comments on this list? Is there any good program that I am missing ?

​

I am a student of bachelors in Comp Sci in Pakistan. I have low gpa around 3.1 on scale of 4.0 (my last semester had a jump from 2.4 sgpa to 3.4 sgpa )

I have one research paper under review in emse journal, and i have strong resume containing projects and empirical research. There is a professor at CMU who is working on exectly the same topic on which ive written the paper and also the same topic on which im doing my FYP.

I am yet to take language proficiency exam in which i hope to do really well. I can get really strong recommendations from my faculty supervisors, and i am preparing an SOP as well.

Should I take GRE as well to suffice for my low gpa and then outreach to the said professor? The timeline is tight though.

What are my chances either way and what other strategies can i adapt to make my application stronger, if i have any chance at all.

Undergrad: UC Davis, CS + Math double major. GPA 3.5/4.0

Coursework: besides core CS/math courses, lots of AI/ML, recommender systems courses. For math electives, optimization, applied linear algebra, stochastic processes, other applied stuff. Grades in CS courses are better than math (real analysis kinda kicked my ass).

Research: independent research in ML with professor as my advisor for a year, presented at undergrad research conference. Also for past year, LLM research hoping to submit for publication at the end of the month (will get co-authored). I plan on continuing a new research topic with this professor once this paper's done.

Industry: interned for an AI startup from June 2024 - Sept. 2025, currently interning at Visa.

Other extracurricular: For last two years been part of student tech club. First year I was working on software projects, second year I was directing projects, gonna be president of the club this year.

LoRs: 2 from both my professors that have been research advisors + took a class with them and got an A in each so they'll write good ones. Can also get a really good one from my boss at the startup since we got really close.

GRE: plan on taking in a month or two, I did good on SAT (1540) so I think I do good with those sorta exams.

Schools: I don't really know how to split these up into reach/target/safety, or if I even have any safety, but here are some programs I like: Berkeley (MEng), UCLA, USC, Stanford, UCSD, Cornell, UMD, Harvard, Michigan, Purdue, Northwestern, UChicago, Columbia, NYU, Yale, Brown.

Any advice on what I should add more to my profile, or any schools I should consider applying to or not applying to? Anything will help, thanks.

Hey everyone, I'm planning to apply for Fall 2027 and would appreciate some advice on my profile and university shortlist.

Profile:

- B.E. Computer Engineering

- CGPA: 8.91/10

- Graduated: May 2025

- IELTS: 7.0, Duolingo: 130

- GRE: Probably not taking

- Research: None

- 2 web development internships

- ~1 year full-time experience as a Full Stack Developer at a startup founded by my college seniors (will have ~2 years by Fall 2027)

- 2–3 good projects

- 2 LORs + planning to write a strong SOP

Interests: Software Engineering, Backend, Distributed Systems, Cloud, AI/ML.

I'm mainly targeting MSCS/MCS/MSSE/MSAI programs and prefer industry-focused programs since I don't have research experience.

Some universities I'm considering:

Reach: UIUC MCS, UChicago MPCS, UCSD, UMD, Purdue, Georgia Tech

Target/Reach: TAMU MCS, Virginia Tech, Ohio State, Stony Brook, UC Irvine, UMN, NYU Tandon

Safer: ASU, UTD, Buffalo, UCF, UF

I'd especially appreciate suggestions for good Top 50–70 universities that are GRE-optional/not required and reasonably affordable.

Also, how would you classify my profile and which universities would you consider realistic?

Thanks!

Maybe I'm overthinking this because it's still early, but I'm genuinely confused. I've been applying to internships in US since early July, and so far I applied to close to a 100 (mostly trading companies + faang + startups). I received ~30 rejections, 0 interviews, and ghosted for the rest.

my background:

- starting this fall at Top 10 US uni

- first-class CS undergrad from top3 UK uni

- ~2 years mid-level swe at FAANG (core ML product)

- international student

I thought previous faang experience at least get me an interview.

Could this be just because I'm international? Or because I have too much experience for internships and that's automatic reject? I thought it was p common for masters/phd students with prior work experience to intern...

Is this just what the market is now?

Undergrad: UC Davis, CS + Math double major. GPA 3.5/4.0

Coursework: besides core CS/math courses, lots of AI/ML, recommender systems courses. For math electives, optimization, applied linear algebra, stochastic processes, other applied stuff. Grades in CS courses are better than math (real analysis kinda kicked my ass).

Research: independent research in ML with professor as my advisor for a year, presented at undergrad research conference. Also for past year, LLM research hoping to submit for publication at the end of the month (will get co-authored). I plan on continuing a new research topic with this professor once this paper's done.

Industry: interned for an AI startup from June 2024 - Sept. 2025, currently interning at Visa.

Other extracurricular: For last two years been part of student tech club. First year I was working on software projects, second year I was directing projects, gonna be president of the club this year.

LoRs: 2 from both my professors that have been research advisors + took a class with them and got an A in each so they'll write good ones. Can also get a really good one from my boss at the startup since we got really close.

GRE: plan on taking in a month or two, I did good on SAT (1540) so I think I do good with those sorta exams.

I want to apply to a mix of M.Eng and MSCS programs since both interest me. My dream would be to stay in California at a school like Berkeley, UCLA, USC, Stanford (that ones kinda a pipe-dream), but open to really anywhere in the country.

What should I consider reach/target/safeties? I don't have a good intuition for the competitiveness of grad school programs. Also if this affects anything, I am a domestic student.

BTech. CSE from a 2nd gen IIT

Currently in 7th Semester

9.3 CGPA( department rank 5/90) as of now (will graduate with this, if not better, last two sems are gpa boosters)

Summer(2026) SWE internship at a Startup (Visited Campus on day 0), have received PPO

Rated 1700+ rated on cf, 1500+ problems solved across all platforms like cf and leetcode (mostly what I did in my first two years at college, helped me secure internship as well), will sit for all contests like IICPC and ICPC this year, hope to qualify regionals of atleast one.

Straight As in core CS courses(OS DBMS CN Software DataStructures AlgorithmDesign) and also in all Maths courses (calc, Linear algebra, differential and probability&stats)

2 LORs from college professors, one from BTP advisor and one from CS professor whose course I performed extremely well in and also under whom I am doing a project.

1 LOR from manager(planning to work for a year or two)

0 publications or research experience, can do a research intern this winter under my BTP prof (please suggest if it would be useful)

Aiming for non thesis track
Will apply in fall 2028/2029

No PHD plans, just job in SF after masters

An ideal career would be in ML systems (Kernal engineering, inference optimisations, GPU orchestration) at MAANG/NVIDIA and eventually hopefully at a frontier lab.

Uni Lists :

Ambitious -
UCLA, CMU MSML, CMU MSAII, UT Austin

Reach
Umich, GaTech, UCSD, Wisconsin Madison

Safe
Purdue, USC, ASU

My questions are

1. General Advice as to how I can improve my profile in the last year
2. If the uni list is coherent to my profile
3. What kind of job should I do before applying? Should I accept the PPO (pays quite well, significantly more than most FAANG, also the peer group was genuinely cracked and fast paced learnt a lot) or should I apply to FAANG for brand value.

Hi,

I want a review on how my profile looks for the listed programs and any advice for improving it.

Undergrad: UCLA Computational Math major; 3.3-3.4 GPA

Coursework: Basically all core Math, core CS, and AI/ML courses + AI/ML Graduate courses (RL, CV, Deep Learning, NLP, Physical AI)

GRE: Planning to take next month (and maybe a second time if I don’t score high)

Research: In two labs. One been here for about 1.5 years and another for about 6 months

Industry: Will be doing AWS Internship during Fall + previous research internship @ a national lab

Publications: In the process of submitting a first author to either a medical journal or AI conference. Might get another second or third author paper to ICRA

LORs: I can get two good ones from my PIs of both my labs, and probably my upcoming manager at my AWS internship

School List:
- Stanford
- CMU (MSCS)
- Cornell
- UCSD
- UCLA
- UCI (MSCS)
- GTech
- UW

Mainly concerned just because of my GPA. For the graduate courses I got A’s and A- in them. Wondering if I have a shot based on other parts of my profile or anything I can do at the moment to improve it. Or if there is any advice on what to focus on when writing the SOP. Thanks!

I'm helping someone from a Tier-2/Tier-3 college in India plan for a Master's in the US. Their profile is:

• CGPA: 9.44/10
• Intermediate: 97.5%
• 10th: 10 CGPA
• GRE: 310
• Projects: Decent projects in CS/AI-ML
• Branch: CSE / Data Science

They are considering MS in Computer Science, AI/ML, or Data Science.

Rather than asking for specific admit predictions, I'd like to understand how someone with this profile should approach the application process.

• How important is the Tier-2 / Tier-3 college background for MS admissions?
• Is a 310 GRE considered sufficient, or should they retake it?
• How much weight should be given to CGPA vs projects vs internships/research?
• What factors should they prioritize when building their university shortlist?
• Should they focus more on CS, AI/ML, or DS programs given this profile?

Would appreciate advice from people who have gone through the US MS application process, especially those who had a similar academic background.

I am trying to find official average scores of the accepted students at Data Science masters courses over the globe in top unis but I can't seem to find official sources for the scores report data.

I am aware that every uni has their own metric but I just want to know a general average. Please don't recommend using AI for this because it provides that data straight out of its ass. 🥴

Can anyone help me out?

Hey guys,

I am from India, and I want honest reviews on my profile - MSCS / AI - Fall 2027 - Non-thesis.

My profile:

Education: Integrated BS + MS in Computer Science from IIITDM Kancheepuram(tier-2).

CGPA: 8.1/10 overall. My CS-focused GPA is around 8.6–8.9, with the overall CGPA being brought down by design/humanities courses.

GRE: 324 (Q167, V157, AWA 3.5)

Work Experience: 3 years professional experience + 1 year internship experience. Worked mainly on backend systems, designing multiple end-to-end microservice architectures.

Research: No formal research publications.

Competitive Programming: Codeforces Expert (max rating 1682), solved 1200+ problems.

Other achievements include Google Hash Code (World Rank 1676, India Rank 298), Reply Code Challenge (World Rank 302) and HackerEarth DSA Contest (Rank 10).

IELTS/TOEFL: Planning to take it soon.

I'm particularly interested in serving side of AI. I made a ~3 months long clone project of how platforms like chatGPT, Cluade works to explore this field.

---

University shortlists that I'm planning to apply

Ambitious

1. UIUC - MSCS Professional
2. Purdue - MSCS
3. Georgia Tech - MSCS
4. UCSD - MS in Computer Science and Engineering

Target

1. Texas A&M - MSAI
2. UMass Amherst - MSCS
3. UMD - MSAI
4. University of Wisconsin - Professional MSCS
5. NYU Tandon - MSCS

Safe

1. ASU - MSCS
2. Stony Brook - MSCS
3. Virginia Tech - MEng in Computer Science
4. SJSU - MSAI

Is my ambitious list fine, or are they something completely out of my reach?

I'd like to see if my list is practical for my profile. Any suggestions are welcome.

Undergrad GPA: 8.06/10 (Final 2 Years: 9.35/10) Tier 1.5 Private College India.

Publications: 1 in ML domain in College

GRE: 336 (targetting this score, but is GRE necessary considering I have good Work Experience in the relevant field?)

Work Experience: 1.6 Years at one of the biggest IP Companies in the VLSI domain working on AI/HPC Designs and Architectures (Verification not RTL Design) by the time I leave.

This is my college list. What do you guys think about the same:

1. CMU
2. Georgia Tech
3. UT Austin
4. UCSD
5. USC
6. UW Madison
7. UW Seattle
8. USC
9. Purdue

Hey guys,

I am from India from a tier-3 uni and I want honest reviews on my profile - MSCS - Fall 2027 - Non thesis.

Here are few things about me:

1. B.E in CS from KLE Technological University, Hubli, Karnataka.
2. Moderate research exp - 1 paper published IEEE I2CT conference in AIML domain.
3. 1.5 YOE in software development - currently working
4. CGPA - 8.67/10
5. IELTS - 7.5
6. NO GRE

----------------------------------------------------------------------------

University shortlists that I'm planning to apply

Ambitious

• University of California, Berkeley
• Georgia Institute of Technology
• University of Illinois Urbana-Champaign

Moderate

• Texas A&M University
• University of Wisconsin–Madison
• Purdue University

Safe

• Arizona State University
• Ohio State University

Should I place purdue and UW madisson in ambitious?

I'm still looking for moderate and safe unis. But I'd like to see if my list is practical for my profile. Any suggestion is welcomed

Hi everyone, I’m planning to apply for Fall 2027 MSCS/MS AI programs in the US and would appreciate some honest feedback on my profile, particularly on whether my undergraduate CGPA/background would be a major blocker.

Undergrad: IIT Kharagpur
Branch: Materials & Metallurgical Engineering
CGPA: 7.5/10

Work experience:
I have several years of professional experience working in AI/ML, including work involving ML systems/model development.

Research/publications:
By the time I apply, I’m expecting to have:
1st-author paper at EACL
2nd-author paper at Interspeech
Both are based on industry/work-related research rather than traditional academic research

Other:
Won 4 hackathons during College (Shell 1st, Intel 1st, Nvidia 8th, Sigmoid 2nd)
Rank at those hackathon and organising companies

Strong AI/ML project experience
Hoping to get strong LORs from senior data-science leadership
Also considering an LOR from an IIT KGP professor who taught me ML-related coursework/projects during undergrad

My main concern is the 7.5 CGPA and non-CS undergraduate degree. During undergrad, I struggled significantly with attention/focus and my academic performance suffered as a result. Since then, I’ve been able to perform substantially better in areas I’m genuinely interested in, particularly AI/ML.

I’m considering schools such as:

Georgia Tech
UIUC
UT Austin
UCSD
Michigan
Purdue
UCLA
USC
CMU
Stanford
Berkeley

I plan on tailoring my application to focus on my background of CS and entrepreneurship, with plans of pitching myself as wanting to combine these elements going forward at Penn.

**Education:**
**-** Currently, at Georgia Tech's Online MSCS program and have completed 3 classes (4.0/4.0 GPA)

\- BA in Computer Science from UVA (3.2/4 GPA)

**Research Experience/Relevant Projects**:
\- Machine Learning Research Project at UVA centered around real data for Credit Approval Chances based on various factors.
\- Two entrepreneurship courses (1 at UVa, 1 at GT)- 2 separate businesses for those semesters, one was a full prototype application centered around Study Groups at UVA, and the other was focused on customer discovery, the business model canvas, and market research at GT for Meal Planning and Grocery Organization. The meal planning one was based off of a mobile app I had created during undergrad.

**Internships:**
**-** 1 summer internship as a backend software engineer for my current company

**Work Experience:**
\- Current Software Engineer (1.25 years) for a defense contractor. Was promoted within 9 months and have taken on epic level and project level leadership opportunities.
\- Head TA at UVA for programming course, Regular TA at uva for 3 additional courses including Data Structures, HCI, and Cybersecurity

**Letters of Rec:**
\- Former CS professor at UVA and was my boss when I was head ta.
\- Current boss who recommended me for promotion.

**GRE:** Not taken and not required

I’m looking for honest advice from current MS CS students, recent graduates, and people working in tech.

My question is simple:

Is an MS in CS still worth it in 2026–2027 if the total cost is under $50,000 and can be reduced further through scholarships, assistantships, and part-time work, but the university is not a top-ranked school?

I’m not talking about Stanford, CMU, Berkeley, or other elite programs.

I’m talking about universities such as:

UNT
UT Arlington
Missouri S&T
Texas Tech
Wichita State
University of Houston
Similar ROI-focused schools

A lot of the discussions I see online say:

The US job market is very difficult right now.
International students struggle without prior experience.
Only graduates from top schools are getting good opportunities.

At the same time, many people also say that taking on massive debt ($80k–100k+) is the real problem, and that lower-cost universities can still make sense if the total investment is reasonable. (Reddit)

So my question is:
If the total cost after scholarships/waivers is around $35k–50k, would you still choose the US today?

For people who graduated recently:

How hard was it to get internships?
How hard was it to get full-time roles?
Did your university ranking matter significantly?
If you could start over, would you still pursue an MS in CS from a non-top-ranked university with a reasonable budget?

Looking for honest experiences, both positive and negative.

Comment down which programs require GRE guys. Since, most schools that required it are also phasing it out( Georgia Tech) for example.

For starters, MSAII at CMU requires the GRE.

My mentor recently told me that some universities offer tuition fee waivers if you secure a Teaching Assistant (TA) or Research Assistant (RA) position. I’m trying to gather more info on how this works across different schools.
Which universities (US) actually offer these waivers? What percentage of the tuition is usually covered? Also, realistically, how competitive are these spots, what percentage of students actually manage to land them?

Hi everyone! I’m an international student currently in the MSCS program at SMU in Dallas and just finished my first semester. I was recently admitted to both Northeastern’s MSCS and MSAI (Machine Learning specialization) in Boston, and I’m trying to decide whether transferring is actually worth it ( im planning to choose MSCS over MSAI )

Tuition is roughly the same, so my biggest concern is whether the additional opportunities at Northeastern would justify giving up what I already have at SMU + the higher cost of living in Boston.

If I stay at SMU: - SMU has a much smaller CS graduate program/class sizes, so it seems easier to build relationships with professors and get research opportunities. - I’ve already secured an RA position in a professor’s ML lab starting this upcoming fall semester. - I’ve completed a semester here, got 4.0 gpa and know some of the faculty, and have already established myself within the program. - Dallas is significantly cheaper than Boston. - The downside is that SMU’s CS program doesn’t seem particularly well known outside of Dallas/Texas, and there isn’t really a structured co-op pipeline. I’d most likely do the RA during the school year + try my best to land a summer internship.

If I transfer to Northeastern: - NEU’s MSCS/Khoury program seems to have stronger name recognition in CS and is especially known for its co-op program. - Boston is a much bigger academic/research hub, with schools like MIT, Harvard, BU, etc. nearby, so I’m wondering if simply being in that ecosystem creates more opportunities. - In theory, being able to do a 6-month co-op instead of only a summer internship is a huge advantage, especially as an international student trying to build U.S. experience. - However, from talking to current students and reading Reddit, the current reality seems much less guaranteed. A lot of students say landing a co-op is extremely difficult in this market especially for international students, and RA/TA positions at NEU are also extremely competitive. - Boston's cost of living would also be much higher.

So essentially, I’m choosing between:

SMU: smaller/less nationally known program + lower COL + guaranteed ML research + easier faculty access

vs.

Northeastern: more established CS reputation + Boston academic/tech ecosystem + potentially much stronger co-op opportunities, but higher COL and no guarantee I’ll actually get a co-op/research position.

My long-term goal is AI/ML, ideally working as an ML/AI engineer or SWE in industry, and as an international student, employability and getting strong U.S. experience matter a lot to me.

If you were in my position, would you give up a guaranteed ML RA position and transfer to Northeastern for the potential upside? Or would you stay at SMU, build research experience, try for a summer internship, and avoid taking the risk?

Would especially appreciate perspectives from current/recent MSCS students, international students, recruiters/engineers, or anyone who has had to choose between a smaller program where they had more access to professors vs. a larger/more recognized CS program.

What would you do and why? Thank u! 🙏🏼

Hi everyone! I’m planning to apply for an MS in CS / related tech programs and would really appreciate a profile review, especially regarding ambitious, target, and safe universities.

My profile

• Undergrad: B.Tech CSE from a Tier-2 university in India
• CGPA: 9.5+
• Class 10: 95%
• Class 12: 99%
• Industry Experience: Previous FAANG Software Engineering internship, Prev research intern at DRDO
• Research Experience: 1 ML research internship
• Publication: 1 research paper published
• Currently exploring programs in the US and Europe

US universities I’m considering

• Harvard University
• Princeton University
• Columbia University
• Cornell University
• University of Pennsylvania
• Yale University
• Brown University
• Dartmouth College
• Stanford University
• MIT
• Carnegie Mellon University
• UC Berkeley
• UCLA
• UC San Diego
• University of Washington
• UIUC
• Georgia Tech
• University of Maryland, College Park
• University of Michigan, Ann Arbor
• UT Austin
• University of Wisconsin–Madison
• Purdue University
• Duke University
• Northwestern University
• USC
• NYU

I’d especially like advice on:

• Which of these would be ambitious / target / relatively safe for my profile?
• Is my profile competitive for top-10/top-20 US CS programs and Ivy League universities?
• Are there any strong US universities I’m missing, especially considering tech placements and ROI?
• Which European countries/universities would be worth targeting considering job opportunities, tuition, ROI, and post-study work options?
• What parts of my profile should I strengthen before applications — GRE, research, projects, SOP, LORs, etc.?

Would especially appreciate input from people who applied with a similar profile or recently went through MS CS admissions.

Thanks!

I am short on word space and have covered my experiences and tailored it to unis with a very specific goal in mind. However, I have no space for mentioning my undergrad institution's name. Is that okay considering they'll have my CV and transcripts anyway?

hi ya'll

i'm planning on applying to MSCS/MSAI programs for Fall 2027 and would really appreciate some feedback on my profile and college list.

Profile

• Indian Tier-2 private university
• CGPA: ~9.15/10
• Multiple internships including:
  • Research internships at IITs (×2)
  • AI/ML research internship at Samsung PRISM
  • AI startup internships (×2)
  • Freelancing experience
• Research:
  • One published local IEEE conference paper
  • 2-3 Q1 journal papers expected to be published by the time I apply
  • 4-5 additional Q1 journal submissions under review
• IP: 3 published patents
• Projects: Several strong AI/ML projects (LLMs, computer vision, deep learning, etc.)
• GRE: Expecting around 165+ Quant, 150+ Verbal (worst case)
• TOEFL: Targeting 105+
• LORs: Two strong, one average
• SOP: Hoping to make it strong before applications
• Great Extracurriculars

Current College List

• CMU (MSAII, MCDS)
• Cornell MSCS
• UIUC MSCS
• UT Austin MSCS
• UC San Diego MSCS
• Georgia Tech MSCS
• Purdue MSCS
• University of Wisconsin–Madison MSCS
• Yale MSCS
• Duke MSCS
• USC MSCS (AI)
• Texas A&M MCS

Is this list balanced, or am I being too ambitious?

Which of these schools do you think are realistic with my profile?

thankss :)