Resume

Education

• M.S. in Computer and Information Science/System Engineering, University of Pennsylvania
• B.S. in Electrical Engineering, South China University of Technology

Work experience

• Summer 2023: Backend Software Engineer Intern
  • Company: Shepherd Money Company
  • Location: Fremont, CA, USA
  • Duties includes:
    • Engineered financial management backend system via Java Spring Boot and MySQL/MongoDB with RESTful APIs, incorporating Redis/SQL optimization to enhance response efficiency to ∼38ms.
    • Integrated Spring Security and OAuth2.0 protocol for JWT management, fortifying backend security and protecting the entire backend from invalid requests.
    • Developed API aggregator service including API key management and data aggregation via Cookie, Crumb and Scheduler from multiple financial APIs, ensuring the maintenance of real-time updates on financial data.
    • Managed CI/CD pipelines utilizing Gitlab CI and Docker to fast update and deploy at Linux with Netdata Monitor, achieving high availability and scalability.
    • Executed Unit/Integration test using Mockito and JUnit, with Gradle script for code quality check, ensuring code base’s readability and maintainability. Participated in 30+ Issue/code review and discussions.
• Spring 2023: Software Engineer Intern
  • Company: DataLynn Inc.
  • Location: NYC, NY, USA
  • Duties included:
    • Collaborated in a Agile team of six to develop Data Science Education Platform on Google Cloud Platform with JavaScript NodeJS and MongoDB/GCS, utilizing Redis to slash fetching time by ∼ 92%, enhancing users’ accessibility of large educational content.
    • Implemented and tested the Payment Service with Stripe and Webhook to ensure the safety of subscriptions and one-time payments, leading to increased user satisfaction and engagement.
    • Constructed the Global Search feature to provide efficient search capabilities with ElasticSearch, ensuring real-time search functionality, and significantly improving the platform’s navigability and user experience.
• Summer 2022: Research Assistant
  • Lab: GRASP, University of Pennsylvania
  • Duties included:
    • Read Computer Vision and Spiking Neural Network related paper.
    • Built the Spiking Neural Network using PyTorch Lava framework.
• Spring 2021: Research Assistant
  • Lab: South China University of Technology
  • Duties included:
    • Read Computer Vision and Object Detection related paper.
    • Built the Mask-RCNN object detection model by PyTorch.
• Summer 2020: Research Assistant
  • Lab: South China Unviersity of Technology
  • Duties included:
    • Designed a new type of electrically controllable metamaterial structure with better utility than existing structures.
    • The application invention patent granted on application number being 202011196946.1.

Technical Skills

Backend Development

• Languages:
  • Java, C/C++, JavaScript, Python, Golang, SQL, Shell, HTML/CSS
• Frameworks and Test Library:
  • Spring Boot, Node.js, Express.js, React.js, Flask, Material-UI, TailWind CSS
  • JUnit, Jest, Mockito, Supertest, Cypress
• Database and Storage:
  • MySQL, MongoDB, Redis, AWS (EC2, RDS, S3), Google Cloud Storage(GCS), ElasticSearch
• Tool and Cloud Platform:
  • Git, Docker, Github Action, GitLab CI, Netdata Monitor, AWS EC2, Google Cloud Platform(GCP)
• Technologies and Protocols:
  • RESTful APIs, OAuth2.0, JWT, TCP/IP, UDP, Multiplex I/O, Event-driven architecture, Multi-thread architecture

Machine Learning

• Languages and Libraries:
  • Python(NumPy, Pandas, Scikit-Learn, TensorFlow, PyTorch, Lava)
• Algorithm and Techniques:
  • Supervisied Learning(Regression/Classification), Unsupervised Learning(Clustering, Dimension Reduction)
  • Deep Learning(CNNs, RNNs)
  • Neural Language Processing(NLP)(Encoder-decoder, Transformer)
  • Reinforcement Learning(Q-learning, Q*)
  • Generative Neural Network (Generative adversarial network, Diffusion model)
• Data Handling and Processing:
  • Data Cleaning, Feature Engineering, Data Visualization(Matplotlib, Seaborn)
  • Big Data processing(Hadoop, Spark)
• Model Evaluation and Delopyment:
  • Model Evaluation Metrics(Recall/Precision, F1-Score)
  • Model Deployment(Docker)