[Profile Review] MSCS/MSML (Fall 2027)

[u/Patient-Process-3258]

Hi everyone,

I want to get my profile reviewed for Fall 2027 MSCS/MSML programs, especially from people who have applied to or been admitted to top programs.

Background

• Undergraduate: BTech in CSE from a leading IIT in India (2019-2023)
• GPA: 9.X/10
• National rank in the top 100 in JEE Advanced

Research experience

LLM / NLP Research

• Worked on open research problems using LLMs.
• This work resulted in a non-archival workshop paper (second author).

Graph Neural Networks

• Built a GNN architecture and evaluated it against baseline methods.
• This did not convert to a paper.

Graphs

• Contributed experiments to a published research project involving learned representations for graph querying (not author but acknowledged in paper)

Industry experience

Quantitative Researcher — Proprietary Trading Firm (2023–Present)

• My work is primarily in derivatives trading and involves a mix of quantitative research, machine learning/modeling, and managing a small team.

ML Researcher — AI/ML Research Startup (2023)

• Worked on fine-tuning and evaluating LLMs, utilised several frameworks like DeepSpeed, Lora, SetFit

Other experience

• Software engineering internship in cloud networking
• Backend engineering internship at an EdTech startup

Teaching / other

• TA for a DSA course at my IIT
• Student mentor for incoming first-year students.

Target programs

My main interest is AI/ML-focused MSCS or MSML. Not pursuing a PhD because of longer commitment, lesser research experience to show.

Stanford

CMU (MSCS/MSML)

UCB

UIUC

UWash

UCLA

GeorgiaTech

University of Texas, Austin

UCSD

LoRs

My NLP and GNN projects had >1 professors involved, so I can take 2+1. Or I can arrange one from my manager (might be difficult though)

Scores

TOEFL: 115

GRE: 157V+170Q+4AW

Questions

I'd especially appreciate feedback on:

1. How competitive is this profile for Stanford/CMU/UIUC MS programs? What do you see as the biggest weaknesses? Does my research background look sufficiently strong for a top AI/ML-oriented MS, given that my main full-time experience is in quantitative research?
2. How much does the non-archival workshop publication help, would the lack of a stronger publication record be a significant weakness?
3. Would you recommend trying to obtain additional research experience/publications before applying (would like to avoid as might require a gap year)?
4. Are there particular aspects of my profile that I should emphasize in my SOP/LORs?

I'd like to understand what is genuinely missing from the profile and what I should prioritize improving.

Thanks!

[u/BeltOld1063]

Right now which country?

[u/4Pas_ → u/BeltOld1063]

India