Daniel Mathew

Daniel Mathew has worked in various roles in the field of computer-vision/deep learning software engineering and data science. In 2021, they worked as a Computer-vision/Deep Learning Software Engineer at XYKEN, LLC, where they implemented a novel RGB based Depth Estimation CNN and improved the accuracy of a 1-class SVM solution for anomaly detection of semiconductor wafers. In 2020, they worked as a Data Science Internship at ON Semiconductor, where they developed an envelope algorithm to generate inlier envelopes on Wafer Factory Time series to detect the outlier wafers. In 2018, they worked as an AI Software Engineer at Exponential Digital Solutions, where they developed a check recognition system with text extraction features and a face recognition system. Daniel also worked as a Machine Learning Engineer at White Oval Technologies Pvt. Ltd., where they developed a license plate recognition system leveraging the OpenALPR framework. Additionally, they worked as a Research Intern at VSSC - Indian Space Research Organization and as an AI and Advanced Analytics Intern at EY in 2017.

Daniel Mathew has a diverse educational background. Daniel graduated from St Thomas Residential School in 2014 with an ICSE degree. Daniel then attended National Institute of Technology Calicut, where they obtained a Bachelor of Technology in Computer Science and Engineering, and a Bachelor of Technology in Computer Science, both in 2018. In 2019, they began their Master of Science in Computer Science at Arizona State University, which they are currently completing. Daniel has also obtained certifications from Coursera in Core Database Concepts, Machine Learning, and Distributed Database Systems, and an ISC Board Exam from CISCE.