Index 2024

Index 2024

The conference for engineers building search, analytics and AI applications at scale. https://rockset.com/index-conf/

Date and time

Thursday, May 16 · 9am - 4:30pm PDT

Location

Computer History Museum

1401 North Shoreline Boulevard Mountain View, CA 94043

Agenda

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)


With 260+ million members in over 190 countries and a billion hours of streaming each month, Netflix is the world’s leading online entertainment company. The highly personalized experience on 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)


Search is key for sales prospecting, helping sales teams uncover the right prospect based on their profile, company demographics, technographic and intent data. In this talk, Stjepan and Dejan discus...

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)


At DoorDash, our mission extends beyond food delivery, embracing a wide range of product verticals including groceries, convenience, and retail. This expansion demands sophisticated machine learning ...

11:30 AM - 12:05 PM

Building a Notification System: How Miro Optimizes Timing and Channels

Tarek Mehrez, Engineering Manager (Miro)


In-app notifications and emails are integral for fostering collaboration, streamlining workflows and keeping projects on track in a distributed work environment. As Miro’s user base and number of pro...

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)


Search platforms powers sales, marketing, and talent search as well as entity resolution, recommendations, and AI at ZoomInfo for 10s of 1000s of B2B customers. Search is also one of the principal wa...

12:35 PM - 1:35 PM

Lunch & Birds of a Feather


Birds of a feather are informal lunchtime discussions focused on specific topics, providing engineers a collaborative, open environment to contribute their knowledge, ask questions and share best p...

1:35 PM - 2:10 PM

Vector Search and the FAISS Library

Matthijs Douze, Research Scientist, FAIR (Meta)


FAISS is a library for approximate nearest neighbor search (ANN), providing indexing methods that are used to search, cluster, compress and transform vector embeddings at scale. Over the years, it ha...

2:10 PM

How Uber Eats Built a Recommendation System Using Two Tower Embeddings

Bo Ling, Staff Software Engineer in AI/ML (Uber)


Uber created two tower embeddings to power recommendations for its Uber Eats platform across hundreds of millions of stores in under 100s of milliseconds. The two tower embedding required infrastruct...

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)


Recommendation systems help users discover products, foster engagement and grow their connections on platforms. This panel discusses trends in recommendation systems around making the entire stack re...

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.

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