Index 2024
The conference for engineers building search, analytics and AI applications at scale. https://rockset.com/index-conf/
Date and time
Location
Computer History Museum
1401 North Shoreline Boulevard Mountain View, CA 94043Agenda
9:00 AM - 9:35 AM
Welcome Keynote
Reynold Xin, Co-Founder (Databricks)
Venkat Venkataramani, CEO (Rockset)
9:35 AM - 10:10 AM
Improving Homepage Personalization at Netflix
Shriya Arora, Eng. Manager, Personalization (Netflix)
Julian Jaffe, Staff Software Engineer (Netflix)
10:10 AM - 10:45 AM
How Cognism Rearchitected In-App Search
Stjepan Buljat, Co-Founder and CIO (Cognism)
Dejan Sijakovic, Chief Architect (Cognism)
10:45 AM - 11:30 AM
How DoorDash Personalizes the Shopping Experience
Luming Chen, Machine Learning Engineer (DoorDash)
Sudeep Das, Head of Machine Learning and AI (DoorDash)
11:30 AM - 12:05 PM
Building a Notification System: How Miro Optimizes Timing and Channels
Tarek Mehrez, Engineering Manager (Miro)
12:05 PM - 12:35 PM
How We Built Search for Go-to-Market Platforms at ZoomInfo
Ali Dasdan, EVP and CTO (ZoomInfo)
Joel Chou, Senior Principal Architect (ZoomInfo)
Hasmik Sarkezians, Engineering Fellow (ZoomInfo)
12:35 PM - 1:35 PM
Lunch & Birds of a Feather
1:35 PM - 2:10 PM
Vector Search and the FAISS Library
Matthijs Douze, Research Scientist, FAIR (Meta)
2:10 PM
How Uber Eats Built a Recommendation System Using Two Tower Embeddings
Bo Ling, Staff Software Engineer in AI/ML (Uber)
2:55 PM - 3:30 PM
Panel: New Architectural Patterns in Recommendation Systems
Jaya Kawale, VP of Engineering (Tubi)
Shu Zhang, Director of Engineering (Pinterest)
Shu Zhang, Director of Engineering (Pinterest)
Vishal Kathuria, Technical Director AI Research (Meta)
About this event
- 7 hours 30 minutes
Attend for free, in-person at the Computer History Museum or virtually via Zoom.
Index brings engineers building search, analytics and AI applications together, with a focus on the design and development of search, analytics and streaming engines. You’ll see engineers and architects present on how they built systems to scale to millions of users or centralize search infrastructure to serve a number of applications.
It’s an exciting time in the search space with the availability and accessibility of AI models introducing new ways and means of building personalization and recommendation systems. This conference is a platform to discuss these changes, encouraging participants to exchange ideas, introduce new concepts and collaborate on tooling and best practices for search and analytics.
Index welcomes diverse perspectives- from builders leveraging open source tools like Apache Lucene, Apache Flink and Apache Kafka, building their own infra in house or using cloud-native and serverless technologies. Topics include:
- Search and analytics systems: Discuss system improvements and academic research that offer new solutions to search, matching and relevance problems.
- AI and vector databases: Learn about ANN indexing algorithms, vector databases, online feature stores and the challenges related to production deployments of models.
- Streaming data infrastructure: Discuss challenges dealing with event and CDC streaming data pipelines and tools and mechanisms to achieve better data quality, manage state, and compatibility of schemas.
- Cloud and serverless advancements: Talk about innovations in database-as-a-service and how to address resource isolation and latency in serverless systems.
Index embraces inclusivity, transparency, and shared growth. We want the benefits to be shared by the community; all presentations will be recorded and shared openly.