Vidhya Suresh

Vidhya Suresh

Senior Software Engineer at Atlassian

    Vidhya Suresh is a distinguished software engineer and a compelling technology speaker, known for her expertise in a wide range of programming languages and web technologies. With a rich academic background, including a Master of Science in Computer Science from North Carolina State University and a Bachelor of Computer Engineering from the University of Mumbai, Vidhya has carved a niche for herself in the tech industry. In her professional journey, Vidhya has made significant contributions to companies such as PayPal Inc and Atlassian Inc, where she developed scalable REST services and optimized performance through asynchronous data processing. Her work in improving transaction processing times and developing innovative payment orchestration solutions has been pivotal. As a speaker, Vidhya shares her insights and experiences, focusing on the impact of new technologies in developing user-centric products. Her presentations not only showcase her technical expertise but also inspire innovation and excellence in software development within the tech community.

    All Sessions by Vidhya Suresh

    Day 3 04/25/2024
    3:00 pm - 3:30 pm

    Leveraging Predictive Models and Data Science to Optimize Information Retrieval Systems

    <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> </span>

    This presentation explores how data science and predictive modeling optimize the performance and scalability of information retrieval (IR) systems. We'll examine the impact of query analysis, document ranking, and result aggregation on user satisfaction. Our research demonstrates that techniques like keyword extraction, intent analysis, and custom deep ranking models can reduce irrelevant results by up to 26% while decreasing computing costs by more than 39%. We'll address the challenges of scaling IR systems to handle massive datasets and high query volumes, highlighting how predictive models streamline resource-intensive processes. Finally, we'll present optimization strategies leveraging distributed computing, multi-stage caching, and predictive ranking models to enhance throughput, reduce latency, and minimize computational overhead. This presentation offers valuable insights for those interested in the intersection of data science and information retrieval.

    Day 3 04/25/2024
    3:00 pm - 3:30 pm

    Leveraging Predictive Models and Data Science to Optimize Information Retrieval Systems

    <span class="etn-schedule-location"> <span class="firstfocus">Machine Learning</span> </span>

    This presentation explores how data science and predictive modeling optimize the performance and scalability of information retrieval (IR) systems. We'll examine the impact of query analysis, document ranking, and result aggregation on user satisfaction. Our research demonstrates that techniques like keyword extraction, intent analysis, and custom deep ranking models can reduce irrelevant results by up to 26% while decreasing computing costs by more than 39%. We'll address the challenges of scaling IR systems to handle massive datasets and high query volumes, highlighting how predictive models streamline resource-intensive processes. Finally, we'll present optimization strategies leveraging distributed computing, multi-stage caching, and predictive ranking models to enhance throughput, reduce latency, and minimize computational overhead. This presentation offers valuable insights for those interested in the intersection of data science and information retrieval.

    Open Data Science

     

     

     

    Open Data Science
    One Broadway
    Cambridge, MA 02142
    info@odsc.com

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