What should a tier-3 Indian student realistically focus on to build a strong ETH Zurich AI/ML profile?
I’m currently a second-year Computer Engineering student from a tier-3 college in India, and my long-term goal is to pursue a research-oriented master’s program in AI/ML at ETH Zurich (or similar universities like EPFL, CMU, etc.).
Right now, I’m trying to realistically understand where I stand and what I should improve over the next 1.5–2 years.
Current profile:
• Research internship involving multitask learning and medical AI (reading papers + survival analysis + architecture understanding)
• Another ML internship involving brain tumor MRI classification, benchmarking models, and potentially writing an analytical research paper
• IIT Bombay AI hackathon finalist
• Hackathon wins/finals at other events
• Experience building and deploying projects (computer vision, NLP, AWS deployment, Docker, etc.)
• Interested in efficient ML systems, deployment, and applied AI
What I’m currently trying to improve:
• Stronger research depth instead of just projects
• Better analytical understanding and experimentation
• GRE/TOEFL preparation
• Building stronger relationships with professors for meaningful LoRs
• More consistency and long-term focus
I’d genuinely appreciate advice from people who:
• got into ETH/EPFL/top MSCS programs
• came from non-IIT/non-elite backgrounds
• transitioned from “project-building” to actual research depth
Mainly trying to understand:
- What made the biggest difference in your application?
- What gaps do students usually underestimate?
- What should someone in my position prioritize most over the next 2 years?
Would appreciate honest advice rather than motivation. Thanks.
my_qualifications: 2nd year B.Tech Computer Engineering student from a tier-3 college in India, currently doing ML/research internships and working on medical AI projects.