Jiaxin (Jason) Li

JPMorgan Chase

Identity & Authentication Data Platform

• IADP supports customer real-time verification of demographic data and ensures seamless, secure authentication across various systems.
• Contributed to the design, development, testing, and deployment of a comprehensive infrastructure, API, database, and messaging that supports real-time customer demographic verification and proactive change notifications.
• Led a large-scale customer big-data migration, realizing the extraction, transformation, and loading (ETL) of 1.2 billion customer demographic records across multiple datasets, utilizing Apache Spark on Amazon EMR to efficiently process massive data volumes in a distributed environment, and optimizing performance and scalability for handling complex transformations and aggregations in real time.
• Developed a high-performance Apache Kafka messaging service to enable real-time data streaming with features like message reconciliation, replay, and store-forward for guaranteed delivery, integrating end-to-end encryption to secure data in transit and at rest, along with robust error-handling and retry mechanisms to ensure reliability in case of failures.
• Architected a scalable and modular cloud solution, using Terraform to automate AWS service provisioning (EKS, S3, Lambda), establishing best practices for cloud resource management, resulting in a streamlined, error-reduced infrastructure setup through pattern design, modular configuration, and automated deployments.

Microsoft

Azure Chaos Studio

• Azure Chaos Studio helps to improve application resilience with controlled fault injection and chaos engineering.
• Played a key role in the development of C# (.NET) web APIs and OS-native software for faults injection, life-cycle management, and telemetry monitoring system.
• Designed and developed the time change fault injection mechanism for Azure Virtual Machines on both Linux and Windows Server, simulating critical failure scenarios by altering the system time, disabling time synchronization, and corrupting critical program time registries to test the system's resilience.
• Spearheaded the development of an automatic orphan fault agent detection and cleanup service, leveraging Azure Service Fabric, Cosmos DB, and Azure Storage, improving overall service health reliability (SLA) and reducing 80% of the manual intervention required by on-call engineers.
• Contributed to the creation and refinement of Azure technology specifications and How-to documentation for both internal teams and external users, working closely with product managers and engineers to deliver detailed, user-friendly content that effectively guided users in using and managing Azure services.

The Michaels Stores

Full Stack Development – Michaels.com eCommerce (Feb. 2021 – Aug. 2022)

• Participated in the design, development, improvement, testing, and deployment of the large-scale Java Spring Boot backend microservices and React frontend UI, enhancing the entire online shopping experience for millions of users.

Third-party Service Integration (Nov. 2021 – Aug. 2022)

• Implemented a robust global third-party API gateway and management service, integrating PayPal (payment), Affirm (financing), Attentive (text), Fusion92 (offer), Tibco (loyalty), and SheerID (ID validation). Streamlined API usage, authentication, authorization, rate limiting, and metric analysis.
• Led the development of the data retrieving APIs and data uploading/syncing up pipelines for 3rd-party service data access.
• Introduced cache system to store the frequently accessed data and avoid long query. Greatly reduced the average API data retrieving time from 1000ms to 10ms.

Shopping Cart Development (Feb. 2021 – Oct. 2021)

• Designed, developed, tested, and deployed of the shopping cart system and RESTful APIs using Java, Spring Boot including initialize shopping cart, add/remove product, change quantity, inventory check, etc.
• Worked with the front-end team to discuss API design such as HTTP method, request/response format, and error handling, etc. Optimized the structure of request and response (params/JSON), reduced the amount of transmitted data, and achieved faster API access.
• Incorporated Kafka as message broker and data buffer for decoupling checkout and shopping cart microservices. Implemented shopping cart cache with Redis which increases performance and reduce response time by 92%.
• Cooperated with the DB team to migrate item table from MySQL to MongoDB using primary-secondary mechanism. Constructed the new shopping cart table schema and index strategy. Managed to merge the separated shopping cart tables (course products, project products, and SKU products) into one standalone table by normalizing the optional tables and extracting the same entities. Reduced the average long query times by 50% (from 3x to 1.5x).
• In charge of: using (TDD) Junit and Mockito to keep unit tests light and non-invasive, using SonarLint for code style check, writing swagger API doc, conducting the CI/CD pipeline from dev to QA, and integrating Datadog for API monitoring.

iOS Mobile Development (Aug. 2020 – Feb. 2021)

• Worked in a 16-person mobile development team, contributing to design, development, testing and delivery of the new Michaels app, participating in the startup of the iOS team, and collaborating on the selection of mobile development frameworks (hybrid vs native, Storyboard vs Swift UI), iOS programming languages (Swift, Objective-C), coding styles, code structure patterns, version-control flow, third-party libraries, and the CI/CD pipeline.
• Led the development of the "In-Store Scan & Go" feature from scratch, implementing GPS, Wi-Fi SSID, Bluetooth beacon, and Geofence to enhance in-store detection speed. Researched, compared, and integrated barcode formats and scanning solutions (Apple Vision, Google MLKit), significantly improving scanning and item retrieval speeds.
• Contributed critical, shared components to multiple features of the mobile app, including a reusable UI component library, global data transformation, presentation, cache, persistence, and network communication libraries, improving overall app modularity and efficiency.
• Collaborated closely with the backend team on API design and contracts and worked with the UI/UX team to integrate the app’s user interface and prototype, ensuring a seamless and engaging user experience.

Environmental Oil Spill Monitoring

A real-time water quality monitoring system by image recognition

Assessing Environmental Oil Spill Based on Fluorescence Images of Water Samples and Deep Learning (Journal of Environmental Informatics) DP Liu, Ming Liu, GY Sun, ZQ Zhou, DL Wang, Fei He, JX Li, JC Xie, R Gettler, E Brunson, J Steevens, D Xu

• Trained a deep learning model using Keras and TensorFlow to evaluate pollution levels by analyzing the fluorescence brightness of water sample images. Achieved a 90% reduction in image evaluation time by localizing the deep learning model to Apple’s CoreML.
• Worked on a team of 3 members to develop an iOS app for real-time oil spill analysis. Provided essential functions such as researcher administration, sample image capturing and preprocessing, precise or fast image evaluation, and history data presentation, optimizing data retrieval and presentation with deep-customized UI rendering, multi-threading, and multi-level caching.
• Worked on a team of 4 members to develop Python Flask service (machine learning system) and Java SpringBoot service (RESTful APIs) based on Google Cloud providing functions including 1. user authentication (OAuth) 2. sample image evaluations with computer vision, deep learning model (TensorFlow, Keras) 3. data persistence and retrieval 4. customized keywords vector search 5. customized offload analysis and recommendation based on researcher's profile, history data, and other key features.

Lite OS File System

Hands-on exFAT Linux-like File System

Code Repo

• Closely modeled the original Unix Filesystem and the Unix Fast Filesystem.
• Designed the file system layout and data structure of inode, bitmap, block store, primary/secondary/... directory, and file descrpitor.
• Implemeted the file sytem formatting, mounting, and unmounting functions as a block storage.
• Implemented the creation of files and directories, the opening and closing of files, and the enumeration of directorie.
• Implemented the reading and writing of data to a file, the seeking of file descriptors, and the deletion of files as well as empty directories.
• Implemented the moving files and directories as well as the creation of hardlinks.
• For the file system layout, please see the document.

pokemon Classification

Mobile App for Pokemon Classification

Code Repo

• Created a Convolutional Neural Network using Keras & TF to recognize Pokemons.
• Used Bing Image Search API to generate the Pokemon datadest.
• Converted the Keras model to CoreML model and integrated to mobile app.

Mizzou Scheduler

Calender-like App helps people to schedule ther daily activities

Code Repo

• Helped Mizzou student get their class schedule, grade, GPA with one click instead of complex operation at Mizzou official website.
• Integrated Myzou system API to automatically import student courses, GPA and other information.
• Designed algorithms to help students automatically arrange their courses, assignments, custom projects and other activities.