Statement of Purpose

The statement of purpose is part of the online application. The statement of purpose is very important and is given careful consideration in the selection process. Be concise and specific in preparing your statement: give information that will aid the selection committee in evaluating your potential for completing a graduate program of study at UCSD.

Please include your name and the department to which you are applying at the top of your statement.

For directions on completing the statement of purpose check the following websites: General Statement of Purpose Guidelines

Your statement of purpose should be no more than 2500 words.

---

这是我目前的sop，请帮我完善和补充其中的一些内容：

In an era where technology is rapidly evolving, my passion lies at the intersection of AI and system development. I'm excited to dive deeper into this field with the Master of Science in Computer Engineering program at the University of California, San Diego, which aligns perfectly with my ambition to develop impactful AI-driven products.

My decision to pursue further education in computer science comes from my strong academic background established during my undergraduate studies at Northeastern University. There, I achieved a GPA of 3.955 and ranked 5th out of 396 in the Software Engineering major. My efforts were recognized with awards like the National Scholarship, Merit Student Scholarship, and Outstanding Student Pacesetter. Among various courses I have completed, Big Data Technology, Introduction to Recommendation System, and Fundamentals of Virtual Reality Technology were particularly influential for me. These classes sparked my interest in advanced software applications and their potential to enhance technology and solve complex problems.

During my internship at JD.com, one of the largest Fortune 500 technology giants in China, I contributed to the Yanxi AI Development and Computing Platform and the AI Pilot Marketing Platform. For the Yanxi platform, I refactored the resource management service to improve efficiency and scalability. By using the Observer Pattern and asynchronous computing, I enhanced the peak performance of resource recalculation speed by 20 times. Moreover, I refactored the activity page AI auto-generation service for the AI Pilot Marketing platform. I organized the functions with the Strategy Pattern to generate each content floor with AIGC and LLM services effectively. Collaborating with machine learning engineers, UI/UX designers, and marketers, I helped design service options and workflows, sharpening my AI software skills and deepening my grasp of user-centered design. This experience allows me to see the transformative impact of AIGC in the real technology industry.

In "Trace Note," a project that won the National Second Prize, ranking fourth in the AR track among 2,287 teams in the 2022 Apple Mobile Application Innovation Contest, I led the development of an AR social platform. This platform allows users to place virtual notes in real-world scenes, enabling experience sharing and token earning. Key features included utilizing ARWorldMap and Tencent Cloud Object Storage to store the AR content, implementing Aspect-Oriented Programming for user authentication, using Redis for distributed session management, using Redis Geo for high-speed trace queries and distance-based sorting, and employing RabbitMQ for asynchronous order creation and timeout-based order cancellation.

For the "Juejin" project at the ByteDance Youth Camp, which won the First Prize, I developed a personalized social recommendation system using the TrustSVD algorithm. This system, integrated into a Timeline Feed, effectively tackled information overload and the cold start problem in recommendation systems. I developed 5 microservices with Spring Cloud and utilized Spring Scheduler for data recalculations, ensuring precise recommendations and enhancing user experience, while maintaining system security and efficient data management.

These projects demonstrate my leadership in developing innovative applications and my ability to implement complex technical solutions in real-world scenarios.

Additionally, my work on the Bioinformatics Data Visualization Platform for TIMEDB at the City University of Hong Kong was pivotal. I contributed to the development of this platform, ensuring data quality and usability, and enhancing user interaction with responsive Vue-based interfaces. My work was recognized in a publication in "Nuclear Acid Research".

Looking ahead, I aim to start my career at a pioneering company like Google or Meta, renowned for their cutting-edge AI products. I want to be actively engaged in the lifecycle of AI-driven products and gain essential industry insights. In the long term, I aspire to establish my own AI-focused startup, dedicating myself to redefining daily workflows and improving life quality with innovative AI solutions.

UCSD's MSCS program is an ideal match for me, providing the perfect platform to realize these ambitions. With its distinguished faculty, advanced research, and comprehensive CS curriculum, it offers an unparalleled opportunity for me to expand my knowledge and contribute to the AI application field. I am particularly excited about courses such as Advanced Topics in Software Engineering, Distributed Computing and Systems, and Deep Generative Models, where I can gain deeper insight into software engineering techniques, the system design of large distributed software systems, and the principle of generative models.

In short, my experience, backed by solid academics and real-world practice, fits well with my plans. I'm eager to join the MSCS program at UCSD, where I can grow my passion for AI, work on innovative applications, and keep learning. I am confident that this program will play a pivotal role in helping me achieve my aspiration of making a meaningful impact through AI applications.

帮我完善我ByteDance Youth Camp和Mobile Application Innovation Contest的详细项目描述：

Trace Note - Team Leader, National Second Prize of 2022 Apple Mobile Application Innovation Contest
Developed an AR social platform that allows users to place notes in nearby scenes to share experiences and earn tokens through consecutive check-

ins for personalized items.

Implemented Aspect-Oriented Programming (AOP) to validate user login status and permissions using annotations. Utilized Redis for distributed session management, effectively resolving login synchronization challenges across clusters.

Utilized the Template Pattern to create a versatile cache tool class, effectively addressing cache-related issues such as cache avalanche, cache penetration, and cache breakdown.

Employed Redis Geo to store nearby traces and utilized Geo Search commands for high-speed trace queries and distance-based sorting.

Implemented user following and mutual following features using Redis Set data structure, ensuring data persistence with Redis AOF. Used Lua scripts to perform inventory pre-checks for accessories, preventing overselling and enabling one order per person. Employed RabbitMQ for asynchronous order creation and timeout-based order cancellation.

Juejin - Team Leader, First Prize of the 4th ByteDance Youth Camp
Implemented a personalized social recommendation system using the TrustSVD recommendation algorithm.

Utilized TrustSVD to create an intelligent recommendation system combined with a Timeline Feed, effectively mitigating information overload and addressing the cold start problem in recommendation systems.

Employed Spring Scheduler for daily recalculations of TrustSVD recommendation data, ensuring precise recommendations, enhancing user experiences, and employing Redisson distributed locks for a single execution of scheduled tasks in the cluster.

Centralized user picture storage with Tencent Cloud Object Storage (COS) and implemented security measures such as size limits and suffix verification to prevent file upload vulnerabilities, bolstering system security.

Managed recommender configuration objects using the Double-Check Locking singleton pattern for resource optimization, reducing the overhead of object creation, and facilitating centralized maintenance.

Established standardized data return classes and global exception handling for consistent data transmission and exception management.

帮我整合我的TIMEDB研究经历：

Bioinformatics Data Visualization Platform for TIMEDB - City University of Hong Kong Aug 2021 - Nov 2022 Contributed to the development of a bioinformatics data visualization platform, using the OViz framework to create diverse bioinformatics charts for the TIMEDB website. More details about the TIMEDB project can be found on the TIMEDB website. Conducted data structuring, cleaning, and analysis, ensuring data quality and usability. Developed user-friendly interfaces using Vue, enhancing data accessibility and user interaction. Published contributions in "Nuclear Acid Research" (IF: 19.160/Q1). Details at https://academic.oup.com/nar/advance- article/doi/10.1093/nar/gkac1006/6833242.

Deep Learning and Applications
Electrical and Computer Engineering