Prashant Gagneja

Computer Engineering student focused on ASR and applied ML: benchmarking models, validating results with cross-validation and error analysis, and deploying the ones that hold up as FastAPI services.

Technical – Core at Microsoft Learn Student Chapter (MLSC) | Thapar University (2025-01 – 2025-05)

• Owned architecture of Auralis across 8 FastAPI route domains (auth, search, recommendations, assistant, audio): async SQLAlchemy/PostgreSQL backend with pgvector semantic search over Spotify-ingested track embeddings, with a Next.js/React frontend.
• Kept the API responsive under load with OAuth via encrypted tokens and Redis one-time exchange codes, splitting jobs across 5 dedicated Celery queues (ingestion, embeddings, waveform, bpm, audio) run by 3 worker processes.

B.E. in Computer Engineering – Thapar Institute of Engineering & Technology (2023-08 – 2027-05)