AahilKhan

Teaching multilingual SpeechLLMs to cope with accents they were never really trained on.

• Work-let: accent-invariant representation learning for SpeechLLMs, mentored by Dr. Spandan Dey and Hirak Mondal.
• Reproducing and benchmarking baseline multilingual pipelines: SALM, Qwen-Audio, SALMONN, then running accent failure analysis to find which accents actually break, and why.
• Building parameter-efficient adaptation using LoRA adapters, accent-aware front-end encoders and MoE dynamic adapter routing to improve ASR/AST on accented and low-resource speech, without retraining the whole model.
• Closure deliverable is a peer-reviewed publication, so the bar here is a paper rather than a demo.

Building an AI interview platform end to end — frontend, backend and the realtime layer.

• Shipping across the frontend, backend and LiveKit service: custom interviews, realtime sessions and recruiter workflows.
• Built audio interview evaluation pipelines on AWS S3 and the Gemini Files API, storing structured scores, recording metadata and recruiter-facing report data.
• Added versioned prompt templates with centralised resolution logic, so changing a prompt stops being a find-and-replace across the codebase.
• Recruiter pipeline tooling with server-side filtering and candidate workflow management.

Re-architected an exam scheduling system that couldn't survive a page refresh.

• Moved from session-based state to a persistent MySQL-backed workflow — the core fix.
• Secure authentication, multi-user support and savepoints, so partial work resumes instead of starting over.
• Improved the generation workflow, cutting scheduling errors by 40%.
• Integrated with Oracle PeopleSoft to automate structured data ingestion and export between the legacy system and the new one.

Led 3 engineers building a lecture archival platform for 15,000+ students.

• Backend APIs and dashboards for lecture uploads, metadata management, access control and search.
• Built a CLI sync tool for local lecture management with automated YouTube uploads and diff-based updates, which took a large bite out of upload times.
• Evaluated Elasticsearch against PostgreSQL full-text search and migrated the search infrastructure — less operational complexity, same performance.
• Used k6 load testing and deployment tuning to hold up under concurrent traffic on college-hosted Linux servers.