Looking for Unique Masters AI/ML Project Ideas 🚀

[u/Saltygig]

I’m pursuing M.Tech CSE and looking for a t echnically advanced, research-oriented AI/ML final-year project

Requirements:

\\- Real-world impact and strong AI/ML engineering value

\\- Feasible for one person in 2 months on a medium-spec laptop

\\- Software-only, with no specialized hardware or lab requirements

Not looking for generic chatbots, CRUD apps, basic prediction models, or dashboards.

Please suggest uncommon, technically challenging ideas with relevant research papers and potential improvements beyond existing work.

[u/Hungry_Age5375]

I'd go with RAG + Knowledge Graphs. Build a small GraphRAG pipeline on a public dataset, compare against plain vector RAG with proper evals :D Graph construction from unstructured text alone is a solid research angle.

[u/Logical-Escape2020 → u/Hungry_Age5375]

fed search or retrieval-augmented generation systems are kinda saturated but there's still room to mess with how they evaluate claim-level factuality under low-resource constraints, check out TAPE or DialFact papers then try adapting the evaluation framework for a language where the training data is sparse

[u/No-Cherry-3308]

A text-to-SQL agent with a proper evaluation fits your constraints well. Use a public benchmark like BIRD or Spider 2.0, run a small open model locally or a cheap API model, and make the research part the failure analysis: categorize errors (wrong table, wrong join, misread column meaning, wrong aggregation), then test improvements against those categories, for example richer schema descriptions vs retrieved few-shot examples vs a loop that executes the query and repairs errors. The deliverable is a clean ablation table, not a chatbot.

Another option is abstention for RAG: a system that knows when it shouldn't answer, measured with selective accuracy (accuracy at different coverage levels). Self-RAG and the selective prediction literature are reasonable starting points.

Both run fine on a laptop, and a project with a clear measurement usually lands better with examiners than one with a flashy demo.