Building Compliance Monitoring Platform (CMON) which is an automated data-driven detection system. It enables us to continuously stay compliant with rules set through Legal, Security, Trust, and Data at LinkedIn.

Building Data Compliance and management systems.-> Help build LinkedIn’s data ecosystem consists of online and offline distributed platforms. Uses Kafka, Espresso, Hadoop, and MySQL to process data at a large scale. To ensure we are handling data responsibly, I work on utilizing the Compliance Monitoring (CMON) Platform to scan all of our systems for issues. -> The CMON platform leverages an end-to-end pipeline across our systems which detects violations and surfaces insights, metrics, and tickets. It also provides a unified view across metadata attached to people, schemas, data sets, owners, purge policies, access patterns/controls, and member PII and settings so that all system behaviors operate as expected.-> CMON approach is a unique effort to operationalize unprecedented visibility into how the LinkedIn ecosystem operates. Integration with the CMON platform is a mandatory component of all engineering efforts on the horizon which serves to improve the craftsmanship of our products. Since launch, we are proud to have surfaced and resolved issues that required attention, and as we improve our detection models we will be able to dry-run scenarios and forecast violations enabling teams to be well-informed and prevent issues.

Experience in leading team from project proposals to project deploymentsKnowledge on machine learning algorithms and deep learning with large scale analytics and cyber security➢Implement ML algorithm and TensorFlow for feature points detection and real-time video stitching by SIFT image registration algorithm and Gaussian Elimination algorithm➢ Implement obstacle detection with deep learning using SSD (Single Shot Multibox Detector)➢ Computer vision - detect real-time feature points, stitching real-time videos, and detect obstacles based on received data (GPS, Lidar, Accelerometer, Ultrasound, Proximity, and Optical Encoder)➢Interacting frequently with sales department for feedback and further improvement➢Developing an automated guided vehicle system using LPC1769, NVIDIA Jetson, RF module, and LPCXpresso software tool

I was responsible for teaching microprocessor architecture and assembly language, design of peripheral blocks and their interfaces to the microprocessor, and designing projects using standard integrated circuit packages.

Research on the development of LPC/Nvidia GPU interface systems for dumping detection systemResearch on the data analysis and data transmission through UART, PWM, GPIO, ExINT, RTC, SPI and ADC interfaces to provide the most creative, impactful technologies to disrupt industries and transform lifestyles, so too can San José become a global leader for civic innovation.