u/Critical-Fun91

Hey everyone,

I’m a 23-year-old CS grad trying to make a pretty important decision and would really appreciate some honest input from people who’ve been through this.

I currently have an admit from Uppsala University (Data Science ,ML and Statistics) for this August. At the same time, my long-term goal was to get into top-tier AI programs like CMU MS AI (MII).

Here’s my situation:

  • TOEFL: 110
  • GRE: Appearing this May
  • Current role: Research Intern at IIT Bombay
  • Background: Strong ML + systems exposure, including NLP, LLM integration, and a published IEEE paper
  • No financial constraints for either option

Now the dilemma:

Option 1:
Go ahead with Uppsala this year, build profile further and skip US?

Option 2:
Skip this admit, apply to US schools (CMU, etc.) in Fall, and join next year (Fall 2027).

The tradeoff for me is basically:

  • Time vs upside
  • Safe, good path vs high-risk, high-reward

What I’m really trying to understand:

  1. Does waiting 1 year actually make a meaningful difference for programs like CMU MS AI?
  2. Would going to Uppsala weaken or strengthen my chances for top US admits later?
  3. From a career standpoint (AI/ML research or applied ML roles), how big is the gap between a place like Uppsala vs CMU?
  4. If you were in my position, would you take the shot or play it safe?

Would really appreciate any insights, especially from people who’ve applied to top AI programs or taken a similar call.

Background (for context):

I completed my B.Tech in Computer Engineering (CGPA: 9.48) in June,2025 from VIIT, Pune and have been actively working at the intersection of ML and systems.

I’m currently a Software Developer at a startup, where I’ve built a Flutter-based mobile application end-to-end, designed the database architecture using Supabase, and worked on backend optimization with APIs and real-time systems.

Alongside this, I’m also working as a Research Intern at IIT Bombay.

On the research side, I’ve worked on projects like a stock market prediction system combining LSTM time-series models with BERT-based sentiment analysis of financial news, and an adaptive learning system using multiple ML models (Decision Trees, Random Forest, etc.), which was published in an IEEE conference .

I also have experience with LLMs and NLP, including prompt engineering and tool-based integrations, and have built systems that combine real-world applications with ML models.

From a systems perspective, I’ve worked with C++ in low-latency environments, including a trading systems internship where I implemented WebSocket and REST-based real-time data pipelines.

Overall, my interest lies in applied AI systems, especially where ML meets real-world infrastructure and products.

Thanks in advance 🙏

PS: The fee payment deadline for Uppsala is May 15 ;)

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u/Critical-Fun91 — 17 days ago