Built continual-learning, run-time query rewriting systems that learn from interaction data, enabling on-the-fly correction for long-tail entities in speech recognition.
Created deep-learning and generative models to break down user questions into component queries, enabling multi-domain reasoning.
Scaled Alexa to use semi-supervised, weak-supervised, and active learning, cutting the need for extensive human annotation when training LLMs.
Developed query context prediction models that reduced search latency by 1/8th, improved CTR by ~1% via relevance tuning, and built trending search algorithms with anomaly detection.
Created ContX at Amazon Ads, an NLP-based recommendation engine leveraging CPD pricing to show relevant product ads for any webpage.
Created models that accurately convert spoken utterances to text and vice versa, enabling robust transcription and natural-sounding TTS.