Shreyas Shastry
About Shreyas Shastry
Shreyas Shastry is an AI/ML Image and Signal Processing Engineer currently employed at Fluke Corporation, where he has worked since 2021. He holds a Master of Science in Electrical Engineering from The University of Texas at Dallas and has experience in embedded DSP programming, iOS development, and machine learning techniques for audio and medical image processing.
Work at Fluke Corporation
Shreyas Shastry currently serves as an AI/ML Image and Signal Processing Engineer at Fluke Corporation, a position he has held since 2021. His role involves the application of artificial intelligence and machine learning techniques to image and signal processing tasks. Prior to this, he worked as an AI/ML Image and Signal Processing Software Intern at Fluke Corporation for four months in 2021. His contributions during this internship laid the groundwork for his current position, focusing on innovative solutions in the field.
Education and Expertise
Shreyas Shastry holds a Master of Science in Electrical Engineering from The University of Texas at Dallas, where he studied from 2018 to 2020. He also earned a Bachelor of Engineering in Electrical, Electronics and Communications Engineering from the National Institute of Engineering, Mysore, from 2014 to 2018. His educational background has equipped him with expertise in embedded DSP programming using Objective-C, iOS development, and embedded systems.
Background and Early Experience
Before his current role at Fluke Corporation, Shreyas Shastry gained valuable experience as a Data Analyst Intern at Cloudix Inc. from 2020 to 2021 in the Dallas-Fort Worth Metroplex. This position allowed him to develop analytical skills and gain insights into data processing. His early career also includes significant project experience in adaptive filtering of audio signals and the application of deep learning techniques for audio signal de-noising.
Technical Skills and Projects
Shreyas Shastry possesses a range of technical skills, including proficiency in designing and implementing filters in both fixed and floating-point formats. He has experience with conventional and machine learning techniques for image processing, particularly in the context of medical images and datasets. Additionally, he has worked on cloud-based machine learning solutions for speech processing, demonstrating his versatility in the field of AI and signal processing.