Abhignana Mihir
I am currently working at Okta as a senior software engineer. Prior to that, I worked at Salesforce as an MTS. I worked for sales cloud as a full-stack engineer. I am a hybrid engineer and my day-to-day work includes 70-75% of development and 25-30 % of automation and testing. I have a paper published in Image processing and Machine learning. I have previously worked at Synopsys as a full-time R&D engineer ||.
Feel free to reach out at akand002@ucr.edu, if you have anything interesting for me.
Competencies: C, C++, Java, Matlab,Hadoop, Lucene,Simba,appium, git, html, css, spark, JUnit.
REVIEWS FROM CLIENTS
Currently working on Data hub which creates a big data pipeline for transferring data instantly.
Currently working on Data hub which creates a big data pipeline for transferring data instantly.
Developed a SocketTester and EchoServer for checking the Sentry logs which is similar to Samsung Knox. Tested and Automated the Androi...
Developed a SocketTester and EchoServer for checking the Sentry logs which is similar to Samsung Knox. Tested and Automated the Android End to End Native Tunnel using NextGen Framework.
A fascinating issue in a digital forensic investigation is that given a digital video, would it be conceivable to recognize the camera...
A fascinating issue in a digital forensic investigation is that given a digital video, would it be conceivable to recognize the camera model which was utilized to get the video. In the paper we take a simplified form of this issue by attempting to recognize recordings caught by a predetermined number of camera models. We propose various features which could be utilized by a classifier to distinguish the source camera of a video. We likewise give exploratory results and show sensible exactness in recognizing video for three distinctive camera models utilizing the proposed features. We have additionally attempted to improvise the time complexity for feature extraction using parallel processing.