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Wednesday, October 18 • 11:15 - 12:00
Panel Discussion - Unlocking Efficiency: Exploring ML Models for Software Testing

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Description: In an era where technology permeates every aspect of our lives, the demand for robust and efficient software has never been greater. Machine Learning (ML) has emerged as a powerful tool for enhancing software testing processes, promising to revolutionize the way we ensure software quality and reliability.
Join us for an engaging panel discussion as we delve into the fascinating world of ML models for software testing. Our distinguished panel of experts, each a luminary in their respective fields, will shed light on the cutting-edge applications, challenges, and advantages of integrating ML into the testing ecosystem.
Key Discussion Points:
  1. AI and ML in Software Testing: Explore the role of Artificial Intelligence (AI) and Machine Learning (ML) in reshaping traditional testing methodologies.
  2. Test Automation: Discuss how ML models are transforming test automation, making it more adaptive, efficient, and accurate.
  3. Predictive Analysis: Learn about ML's capacity to predict potential defects, vulnerabilities, and performance bottlenecks.
  4. Optimizing Test Coverage: Discover how ML helps in optimizing test coverage and identifying high-impact test cases.
  5. Data-Driven Testing: Explore the significance of data-driven testing and how ML harnesses big data to drive testing strategies.
  6. Challenges and Pitfalls: Examine the challenges and potential pitfalls associated with integrating ML into software testing processes.
  7. Real-World Applications: Hear real-world examples of organizations leveraging ML models for enhanced software testing.
  8. Future Trends: Gain insights into the future trends and possibilities of ML in the context of software testing.
Who Should Attend:
  • Software Testers
  • Quality Assurance Professionals
  • Data Scientists
  • AI/ML Enthusiasts
  • Tech Leaders and Decision-Makers
Join us for this enlightening panel discussion where you'll have the opportunity to interact with our panelists, ask questions, and gain a deeper understanding of how ML models are shaping the future of software testing. Whether you're a seasoned professional or just beginning your journey in this field, this discussion promises to provide valuable insights into the exciting intersection of machine learning and software quality assurance.

avatar for Preethi Ramesh

Preethi Ramesh

Associate Director of Data Science & Analytics, Takeda
Preethi is an accomplished professional with a distinguished background in the field of AI/ML, holding Bachelor's and Master's degrees in Computer Science, complemented by a second Master's degree in Business Administration. With over 13 years of hands-on experience, Preethi has skillfully... Read More →
avatar for Tariq King

Tariq King

Chief Scientist, test.ai
Tariq King is a recognized thought-leader in software testing and quality engineering. He is currently the Chief Scientist at test.ai, where he leads research and development of their core platform for AI-driven test automation. Tariq has over fifteen years' professional experience in the software industry, and has formerly held positions including Head of Quality, Director of Quality Engineering, Manager of Sof... Read More →
avatar for Nikolay Advolodkin

Nikolay Advolodkin

Sr Developer Advocate, Sauce Labs
Nikolay Advolodkin is a distinguished software development and test automation expert, acclaimed international speaker, and AI explorer, currently serving as a Principal Developer Advocate at Sauce Labs and Founder of UltimateQA. With an unquenchable thirst for technology and a deep-seated... Read More →
avatar for Scott Aziz

Scott Aziz

CTO, AgileAI Labs

Wednesday October 18, 2023 11:15 - 12:00 EDT