1. Developed a Low-Power Smart Doorbell with ARM Cortex-M4 and ESP32S3 MCUs, featuring video streaming, remote access, and audio communication, enhancing warehouse security with low cost.2. Engineered robust control systems for multiple peripherals using FreeRTOS, boosting system responsiveness and reliability by 20% under high-load conditions.3. Optimized video streaming over WiFi networks by implementing efficient UDP/IP protocols and DMA, reducing latency by 30%.4. Deployed a lightweight ML model for audio event recognition, enabling power-efficient, conditional system wake-up based on environmental sounds.

1. Developed a low-power, continuous health monitoring device using AD8232 and ESP32.2. Designed and printed custom PCBs using Altium, reducing the device weight by 50%.3. Implemented I2C, Bluetooth-LE, and WiFi to transmit data to PC/cloud for machine learning applications.

1. Designed and built a Python-based GUI tool for decoding, viewing, and filtering CT machine log files, enhancing log readability and boosting reader efficiency by 40%.2. Developed XR content using Blender & PTC SW, resulting in an 80% increase in service training efficiency.3. Implemented a VR meeting platform to facilitate cross-department virtual design review, reducing the reliance on physical prototyping, leading to a 70% cost saving.4. Enabled remote AR-guided support to simplify onsite machine repairs, empowering new service members to address complex issues without years of experience.5. Rebuilt the department website for effective communication of results, innovative ideas, and XR project status.

1. Developed a gait tracking system using STM32 to assess one's dementia risk, facilitating early intervention.2. Optimized the HAL library for double buffering, enhancing USB data rates between STM32 and Android.3. Developed a cloud-integrated app using Java and Flutter to seamlessly receive and upload data from MCU.4. Generated 7 gait models utilizing machine learning on AWS.

Help students understand key concepts in multiple courses including Microprocessor Systems, C++ Programming, and Data Structures.

1. Developed an intranet version control system using GitLab to secure code and safeguard branches.2. Established a CI-CD platform using GitLab Runner and Docker Containers, enhancing development pipelines for over 30 users in 3 departments.3. Designed a lightweight Linux container using DockerFile for training self-driving neural networks, reducing setup time by 40% and file size by 50%.4. Developed Shell Scripts to streamline self-driving algorithm tests, achieving a 20% increase in efficiency.5. Authored comprehensive logs and documentation for the above projects to make them accessible for colleagues and users.