Accelerating Application Security and Machine Learning with Cloud IAM
IEEE CS SD Invited Seminar Series 2025 - Lectures 1 and 2 (Virtual)
Our inaugural talk of the 2025 Invited Seminar Series comprises of two back to back talks covering a few interesting topics revolving around cloud computing including user access control, authentication and authorization, deploying machine learning models and accelerating ML workflow on the cloud platforms.
Date and Time
Location
Hosts
Registration
- Date: 28 Jan 2025
- Time: 05:30 PM to 06:30 PM
- All times are (UTC-08:00) Pacific Time (US & Canada)
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- Co-sponsored by Media Partner: Open Research Institute (ORI)
- Starts 06 January 2025 12:00 AM
- Ends 28 January 2025 06:00 PM
- All times are (UTC-08:00) Pacific Time (US & Canada)
- No Admission Charge
Speakers
Saidaiah Yachuri of Amazon Web Services
Application Security using IAM
Application security using IAM (Identity and Access Management) refers to the practice of managing user access to applications by verifying their identity and granting them only the necessary permissions to interact with specific parts of the application, effectively controlling who can access what data and functionalities within the system, thus enhancing application security by preventing unauthorized access.
Biography:
Saidaiah Yechuri is a software engineer and security expert currently contributing to the AWS Identity and Access Management (IAM) team at Amazon Web Services. Before joining AWS, Saidaiah spent nearly a decade at Dish Network and Spectrum, where he developed software solutions for video streaming and media domains, contributing to innovative features and enhancing user experiences in the entertainment industry.
Address:United States
Kunal Sekhri of Google
Accelerating Machine Learning with Cloud Platforms: From Research to Production
Machine Learning (ML) has revolutionized industries, but deploying models into production can be complex. Cloud platforms offer powerful tools to streamline this process, from model training and deployment to monitoring and optimization. This talk will delve into best practices for accelerating ML workflows on cloud platforms, covering topics such as:
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Model Serving: Efficiently deploying ML models as APIs or real-time services.
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Software Engineering Best Practices: Writing clean, maintainable, and scalable ML code.
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Rollout Strategies: Safely and effectively deploying ML models to production.
Through practical advice, this talk will empower attendees to build and deploy robust ML solutions that deliver real business value.
Biography:
Kunal Sekhri is a Software Engineer with 9+ years of experience building high-performance and scalable distributed systems. He has a track record of leading teams, collaborating across departments like Product and Marketing, and consistently delivering exceptional software products. His interest lies in building products to address users' pain points from better reliable systems to more intuitive experiences. Kunal is currently leading the team at Google Cloud for improving the discovery of Google Cloud Products and services. It involves building a better search stack, streamlining customer user journeys on cloud.google.com for personas like AI enthusiasts, developers, startups etc. Kunal work involves working with marketer, user researchers, product managers and software engineers to improve the experience for Google Cloud customers by 10x. Kunal’s goal is to make AI adoption on cloud seamless for enterprises, developers, and students to unlock their capabilities to do more.
Address:United States
Agenda
- Invited talk from Saidaiah Yechuri, SDE at Amazon Web Services(25 mins)
- Invited talk from Kunal Sekri , Senior SW Engg. at Google (25 mins)
- Q/A Session (10 mins)
- 1st and 2nd lectures of the 2025 Invited Seminar Series (Virtual) organized by IEEE Computer Society San Diego Chapter. Previous lectures: 2023 and 2024 invited seminar series.