Research/Thesis/Capstone Project Review

Academic AI/ML projects deserve more than “cool idea” responses. Whether you're working on a thesis, paper, or capstone project, this session gives you deep, constructive, and honest feedback from someone who’s reviewed 100s of research projects and hired from both academia and applied labs.

Here’s what we’ll do:

1. Review your hypothesis, methods, and problem framing
2. Check your model choice and dataset relevance
3. Suggest improvements in evaluation metrics and baseline comparisons
4. Spot red flags in reproducibility or scope creep
5. Offer feedback on writeup structure (if publishing or submitting)
6. Brainstorm how to make the project job/PhD-ready

You'll get actionable feedback that goes beyond “add a chart” or “clean your dataset.” I’ll also suggest how to talk about your project in interviews and how to adapt it for a GitHub portfolio or blog post. Ideal for final-year students, master’s candidates, or aspiring researchers looking to elevate their work.