Nisarg Antony
About Nisarg Antony
Nisarg Antony is a Machine Learning Engineer at InfoVision Inc. in Richardson, Texas, with a Master's degree in Computer Science from the University of North Carolina at Charlotte and a Bachelor's degree in Computer Engineering from Gujarat Technological University.
Work at InfoVision
Nisarg Antony has been employed at InfoVision Inc. as a Machine Learning Engineer since 2019. He works in Richardson, Texas, United States, contributing to various projects that leverage machine learning techniques. His role involves implementing advanced algorithms and frameworks to enhance the company's capabilities in real-time data processing and analysis.
Education and Expertise
Nisarg Antony holds a Master's degree in Computer Science from the University of North Carolina at Charlotte, where he studied from 2017 to 2018. He also earned a Bachelor's degree in Computer Engineering from Gujarat Technological University, Ahmedabad, from 2012 to 2016. His academic background provides a strong foundation in computer science principles and machine learning applications.
Technical Skills and Projects
Nisarg has utilized pose detection frameworks such as OpenPose and PoseNet to tackle occlusion issues in real-time human pose detection. He has developed APIs using Flask and Django, emphasizing reliability, security, and speed. Additionally, he implemented an automated object detection pipeline that optimizes GPU resource sharing among multiple YOLO instances.
Automation and Infrastructure Management
Nisarg has automated environment build and provisioning processes using tools like Docker, Kubernetes, and Azure Container Instances (ACI). He has also leveraged Apache Kafka to establish highly available and resilient message queues for stream processing, enhancing the efficiency of data handling in various applications.
Machine Learning Applications
In his work, Nisarg has developed fraud detection models utilizing random forest classification and ensemble learning methods. These models are designed for real-time analysis of customer transactions, contributing to enhanced security and risk management in financial operations.