Formerly Vitesco Technologies, merged with Schaeffler in October 2024.Project Cybersecurity and Privacy Manager (PCPM) in Cybersecurity and Privacy Management (CPM) Team

Company merged with Schaeffler in October 2024.Project Security and Privacy Manager (PSPM) in Security and Privacy Management (SPM) Team

94806 Privacy in the Digital Age

Product Security Assurance (PSA) Team• Assisted in the development of privacy security lifecycle management measures; Output data privacy technical solutions and promoted their implementation.• Designed and improved the privacy review and approval process using the NIST privacy framework to reduce privacy risks throughout the product lifecycle.• Conducted reviews to identify and address privacy exposures in product development. Outlined the privacy policy of the new product and created a template.• Managed the receiving process of data collection requests, assessed privacy risks, facilitated the review and approval process.• Developed privacy threshold analysis (PTA) and privacy impact assessment (PIA) processes and built relevant documents and templates.• Prepared training materials to explain and compare GDPR and CCPA/CPRA requirements.• Influenced and built relationships with team members and ensured that all products, services, and projects were designed with data privacy protection in mind.

Cross-border E-commerce Borrow-sell Platform• Built a storage system with MySQL and MyBatis on Alibaba Cloud RDS & OSS from local storage for non-structural data. Utilized Redis as the high-speed cache and successfully improved loading speed of static resources and reduced system load.• Constructed microservices based on Spring Boot and Spring Cloud framework for user and product information management, and configured deployment automation using Jenkins and Docker.• Achieved load balancing, fault tolerance, etc. using Spring Cloud. Established gateway with Spring Security and connect with Oauth2 authentication server to verify token as well.• Built the front-end with Vue.js and Axios guard, and utilized RESTful API to communicate it with the back-end.

Vehicle Motion GenerationAdvised by Prof. Masayoshi Tomizuka and Postdoctor Liting Sun• Utilized Imitation Learning and Reinforce Learning techniques to predict and simulate vehicles driving behaviors on roads with the data collected by MSC Lab.• Reproduced the paper: ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst; Utilized Generative Adversarial Imitation Learning (GAIL) to simulate vehicles driving behaviors.

Project Title: Computer Vision for High Throughput Plant Phenotyping of Maize PlantsAdvised by Prof. Edgar Lobaton abd Ph.D. Candidate Nathan Starliper.• Adopted image processing techniques and computer vision algorithms such as YOLO-v3 and Fast-RCNN to perform full plant phenotyping of maize plants for the purpose of monitoring crop health, growth stage, and water stress.• Processed raw plants image data and extracted leaf tips and collars features of plants from images and utilized them to determine various topological properties of plants that could contribute insight into the health of plants.

Animal Image Detection and Classification SystemAdvised by Prof. Shuangshuang Li.• Built an animal detection and classification system based on CNN to detect and classify mutilple animal types when an animal image was input to the system.• Implemented python web crawler to collect around 50,000 animal pictures as dataset.• Led a team of 5 to establish an animal detection, classification and search system based on deep CNN to detect and classify animal types on the input images to the system, accuracy up to 96%.• Australian Innovation Patent issued.