AWS Summit San Francisco
Join us in person April 20 – 21
Hear the latest updates from AWS experts, builders, customers, and partners.
Come prepared with your laptop and a willingness to learn.
Ask the Expert
Visit Ask the Expert to meet with AWS technical experts.
AWS Training and Certification
Get equipped with the knowledge it takes to move your company and career forward.
Front-end Web and Mobile
Modern Applications – Containers & Serverless
Networking & Global Infrastructure
Swami Sivasubramanian, Vice President of Data, Analytics, and Machine Learning Services, Amazon Web Services
Can't join in person?
The keynote will also be available via livestream at 9:00AM – 10:30AM on April 21, 2022. Please note that breakout sessions and other general sessions will only be available in-person.
Featured customer speakers
Executive Vice President
Day One | Wednesday, April 20, 2022
What to expect
Who should attend
7:30AM PDT: Registration open
7:30AM – 9:00AM PDT: Breakfast at Expo
7:30AM – 5:30PM PDT: Expo & activities
9:00AM – 4:45PM PDT: Sessions
9:00AM – 5:00PM PDT: Interactive content
4:30PM – 5:30PM PDT: Networking reception
Day Two | Thursday, April 21, 2022
What to expect
Come develop the skills needed to build, deploy, and operate your infrastructure and applications. Join us to connect, collaborate, and deep dive into the cloud computing technology with a variety of breakout sessions and interactive content.
Who should attend
Day Two is ideal for technologists already running workloads on AWS.
7:00AM PDT: Registration open
7:00AM – 9:00AM PDT: Breakfast at expo
7:00AM – 4:00PM PDT: Expo & activities
9:00AM – 10:30AM PDT: Keynote
11:30AM – 5:00PM PDT: Sessions
11:30AM – 5:30PM PDT: Interactive content
* Space is limited. To ensure the best attendee experience possible, access to the event or specific event activities such as keynote, breakout sessions, labs, meals, receptions, and lounges may be limited due to capacity restrictions.
Vice President, Data, Analytics, and Machine Learning at Amazon Web Services
Swami Sivasubramanian is Vice President of Data, Analytics, and Machine Learning at Amazon Web Services. His team’s mission is to put the power of databases, analytics, and machine learning capabilities in the hands of every business, including developers, data scientists, and business users. Swami and his team innovate across multiple areas, from databases (e.g., Amazon RDS, Aurora to NoSQL databases like DynamoDB, ElastiCache, MemoryDB and Neptune), to analytics (e.g., Redshift, EMR, Athena, QuickSight, Lakeformation, Glue, OpenSearch), to machine learning (e.g., frameworks and infrastructure, Amazon SageMaker) and AI services (e.g., Transcribe, Translate, Textract, Rekognition, Personalize). His team also works to deliver needle-moving capabilities in data and ML for specific verticals, use cases, and initiatives like Health AI (e.g., HealthLake, Comprehend Medical, Transcribe Medical), Industrial (e.g., Lookout for Equipment, Lookout for Metrics, Lookout for Vision, Panorama), Contact Center AI (e.g., Contact Lens with Amazon Connect), Financial services (e.g., FinSpace, Amazon Managed Blockchain), and Enterprise Search (Kendra).
Previously, Swami managed AWS’s NoSQL and big data services. He managed the engineering, product management, and operations for AWS database services that are the foundational building blocks for AWS: DynamoDB, Amazon ElastiCache (in-memory engines), Amazon SNS, and Amazon QuickSight (to name a few). Swami has also been part of the teams that built different parts of AWS services including Amazon S3, Amazon CloudFront, Amazon RDS, Amazon SQS - Amazon's Paxos based consensus service, etc. Swami has been awarded more than 250 patents, has authored 40 referred scientific papers and journals, and participates in several academic circles and conferences.
Swami enjoys spending time with his family (wife, 6-year-old daughter, and puppy), hiking around the Pacific Northwest, and various other outdoor activities. Personally, he enjoys reading nonfiction books and research articles on machine learning, distributed systems, and other major computing areas.