Hina Gandahi of Cisco Systems

In this talk, we will explore the core components of Apache Spark and examine what makes it a powerful and efficient engine for large-scale data processing. We'll discuss how Spark achieves performance through in-memory computing, DAG execution, and parallelism, while also highlighting common challenges related to scalability and resource optimization in big data environments. Finally, we'll introduce how AI techniques—such as intelligent workload management and adaptive query optimization—can be leveraged to enhance performance and efficiency in Spark-based architectures.

Biography:

Hina Gandahi is a skilled software engineer with deep expertise in building scalable, high-performance systems for cloud and data-intensive applications. Currently a Senior Software Engineer at Cisco Systems, she leads the design and development of risk-based vulnerability management software, driving critical initiatives like transforming monolithic services into microservices and enhancing application performance and memory efficiency. Previously at VMware, Hina played a key role in building cost-effective data pipelines, high-throughput services, and policy enforcement engines that significantly improved performance and security for enterprise cloud platforms. Her work with big data technologies such as Spark and Kafka, along with her contributions to cloud cost optimization and CIS policy compliance, earned her multiple internal awards for excellence. Hina holds a Master’s in Information Systems from Northeastern University and a Bachelor’s in Computer Science from Jaypee University of IT in India. Passionate about innovation and continuous improvement, Hina brings a thoughtful and data-driven approach to solving complex engineering challenges across the cloud and cybersecurity landscape.

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