Search 360°: From Query Understanding to LLM-Enhanced Retrieval

Hybrid event: In-person, Zoom and YouTube

If you want to join discussion remotely, you can submit questions via Zoom Q&A. The zoom link:
https://acm-org.zoom.us/j/99559399340?pwd=VIgWCBHabs0ckWkbFDJy8s3YT56i4j.1
Join via YouTube:
https://www.youtube.com/watch?v=ceXO6vyUz2M

AGENDA
6:30 pre-sign in to test and chat
7:00 SFBayACM upcoming events, introduce the speaker
7:15 speaker presentation starts
8:15 - 8:30 finish, depending on Q&A

Join SF Bay ACM Chapter for an insightful discussion in person at VRP

Description:
Search systems are evolving rapidly, powered by advances in deep learning, embeddings, and now large language models. This talk offers a 360° view of modern search architectures: from query understanding and candidate generation to pre-ranking, ranking, and re-ranking. We’ll explore how hybrid retrieval (sparse + dense), multi-task learning, and LLM-assisted query understanding are redefining search quality and personalization. Attendees will gain a systems-level understanding of how each layer contributes to relevance, diversity, and user satisfaction, and where to focus next for scalable innovation.

Audience:
AI practitioners interested in understanding how modern search systems work end-to-end. Also suitable for product engineers and researchers. Beginner to intermediate level: designed for attendees familiar with basic ML and data concepts, but not requiring deep expertise in search or ranking systems.

Speaker Bio:
Gauri Sarode is a Senior Machine Learning Engineer at Doordash, where she builds large-scale personalization and search systems that shape the customer discovery experience. With an M.S. in Computer Science from New York University, Gauri combines academic depth with real-world production experience. She holds multiple certifications in Generative AI and Retrieval-Augmented Generation.
LinkedIn: https://www.linkedin.com/in/gaurisarode/
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