Bite-Size Science: The Art of Machine Learning with Kishansingh Rajput

Take a break for lunch and nourish your brain with the latest in scientific discussions, presented by experts at Jefferson Lab. The second season of the lab’s summer series, Bite-Size Science, is now underway. The Bite-Size Science lunchtime lecture series features half-hour, live-streamed presentations on lab-related science, engineering and technology topics and presented by leaders in their fields. The presentations are tailored to non-scientists and are brief, free, and feature a chat feature for Q&A with the presenters.

Synopsis:
We are living in the digital era surrounded by smart devices producing data each moment. Deriving insights and learning from large sets of data requires advanced techniques, such as Machine Learning. In this talk, we will discuss the basics of machine learning, growing research in the field, the different types of machine learning and a few examples of its applications to improve the experimental infrastructure at the lab.

About the Speaker:
Kishansingh Rajput graduated with Bachelor of Computer Engineering from Gujarat Technological University, Ahmedabad, India, followed by MS in Computer Science from University of Houston, Texas. He has joined the lab in 2020 as a staff computer scientist and resident AI/ML expert. He has helped develop data quality monitoring system with ML, uncertainty aware ML-based anomaly detection for SNS accelerator, both of which are currently deployed and crushing the numbers. He is currently leading a LDRD project to develop a ML based system to simultaneously optimize the heat load and fault rates in CEBAF operation. He is also co-leading “Mathematics and Algorithm Development” task-force on a 5 year project to develop a ML-based inverse problem solver for nuclear femtography in collaboration with Theory division at JLab and Theory/Computational science division at Argonne National Lab.