Events

IEEE Computer Society San Francisco Bay Area Chapter Virtual Tech Talk

The San Francisco Bay Area Chapter of the IEEE Computer Society invites you to our free and open
Virtual Tech Talks. No IEEE membership is required.

Event Page:

Register on Eventbrite

Speaker:

Jyotheeswara Reddy Gottam

Title: The Triple Threat: Transforming Enterprise Quality Engineering Practices with Generative AI, Predictive Analytics, and Self-Healing Automation

Abstract

Modern software teams face mounting pressure to release high-quality applications faster while managing increasing system complexity and continuous delivery expectations within modern CI/CD pipelines. Traditional testing approaches often struggle to keep pace with rapid code changes, expanding regression suites, and the rising cost of maintaining automation frameworks. These challenges frequently lead to delayed releases, increased testing costs, and defects escaping into production.

This presentation explores how the “Triple Threat” of AI-driven testing technologies—generative AI for test script creation, machine learning-based predictive defect analytics, and self-healing automation frameworks—is transforming enterprise quality engineering practices.

First, generative AI accelerates test development by automatically generating test cases, scripts, and data from requirements, user stories, or code changes, significantly reducing manual scripting effort. Second, predictive defect analytics powered by machine learning analyzes historical defect patterns, code churn, and previous test outcomes to identify high-risk components and prioritize testing efforts where failures are most likely to occur. Third, self-healing automation frameworks intelligently adapt to UI or API changes, minimizing brittle test failures and reducing the costly maintenance typically associated with large automated test suites.

When deployed together, these technologies reinforce one another: generative AI expands test coverage, predictive analytics focuses testing on the most critical risk areas, and self-healing automation ensures test suites remain resilient despite frequent application updates. Applied across API testing, functional testing, integration testing, and end-to-end testing, this integrated approach enables organizations to modernize their testing strategy while improving reliability.

The combined impact allows enterprises to reduce testing costs by up to 40%, accelerate release cycles by 30%, and improve defect detection rates by over 50%, demonstrating how AI-driven testing can deliver measurable improvements in both quality and delivery speed across enterprise software systems.

Biography

Jyotheeswara Reddy Gottam is a Software Engineering Leader with over a decade of experience in the retail and e-commerce industry. Currently a Senior Software Engineer at Walmart Global Tech, he leads end-to-end testing strategies for high-traffic marketplace platforms, driving scalability, reliability, and performance for systems handling millions of daily transactions.

He specializes in Gen AI, machine learning, AI agents, RAG, test automation, performance engineering, and CI/CD enablement. Throughout his career, he has architected scalable automation frameworks, significantly reduced regression cycles, improved release velocity, and ensured platform stability during peak traffic events. He has also led cross-functional initiatives across payments, inventory, personalization, and mobile platforms.

Speaker(s): Jyotheeswara Reddy Gottam

Virtual Event Link:

https://events.vtools.ieee.org/m/548913

30th CASIS Workshop at LLNL

We are thrilled to host LLNL’s 30th Center for Advanced Signal and Image Sciences (CASIS) Workshop.
The workshop returns with a full two-day, in-person schedule on Wednesday and Thursday, June 24–25, 2026.

We encourage a broad range of technical topics at the workshop. Because the workshop is non-archival apart from original work, we are also considering intermediate results from ongoing efforts as well as recently published work for presentation as a talk and/or poster.

The goal of the workshop is to provide a platform for the exchange of ideas and networking with peers across disciplines to foster collaboration and build community.
Please submit your abstract by Friday, May 15, 2026. Authors will be notified of review decisions one week later, on May 22, 2026.

In addition to the regular presentation track, the workshop will feature parallel tutorials, hands-on mini workshops, and a dedicated student track introducing career opportunities at LLNL.

The workshop will be held in person at the
University of California Livermore Collaboration Center
and requires pre-registration by June 18, 2026. As this is a full two-day workshop, coffee and snacks will be provided during morning and afternoon breaks, and lunch will be provided on both days.
As part of the 30th anniversary celebration, a Happy Hour will follow the regular program on Wednesday, June 24, 2026.

Workshop Website:

https://engineering.llnl.gov/centers/casis/workshops

Technical Tracks

• AI / Machine Learning — Phan Nguyen, Kowshik Thopalli
• National Ignition Facility — Eugene Kur, Christopher Miller
• Non-Destructive Evaluation — Seemeen Karimi, Harry Martz
• Quantum Sensing & Quantum Computing — Kristi Beck
• Remote Sensing, Non-Invasive Imaging & Inverse Problems — Sean Lehman, Viacheslav Li
• Robotics & Automation — Aldair Gongora, Abhik Sarkar
• Student Track: All Topics (Poster Only) — Ted Bauman, Min Priest

Become part of this great experience and submit your talk proposal at

https://engineering.llnl.gov/centers/casis/workshops
.

Check out

last year’s event highlights

to see what to expect.

The no-fee CASIS Workshop is sponsored by the
Lawrence Livermore National Laboratory Engineering Directorate
and held at the
University of California Livermore Collaboration Center.
It is organized by the
Center for Advanced Signal and Image Sciences (CASIS),
and is a joint meeting with the local chapters of the
IEEE Signal Processing Society
and
IEEE Computer Society San Francisco Bay Area Chapter,
with support from
IEEE Region 6, East Bay Section.

Co-sponsored by: Lawrence Livermore National Laboratory - Center for Advanced Signal and Image Sciences

Location:
Building 661, L-794
University of California Livermore Collaboration Center
7000 East Ave
Livermore, California 94550
United States