About Me

Hi, I’m Boqi (Bobby) Zhu, a Master’s student in Computer Science at UC San Diego with a background in Data Science (B.S., UCSD).

My experience spans data analytics, data science, software engineering, and teaching. I’ve delivered policy and business analytics projects, applied data science to healthcare challenges through predictive modeling, and built backend services as a Software Engineering Intern. In addition, I’ve served as a Teaching Assistant for data science and cognitive science courses, helping students strengthen both technical and analytical skills.

I enjoy designing reliable data systems, uncovering insights that guide real-world decisions, and supporting others in their learning journey. Let’s connect!

Skills

Experience

Education

  • Data Analyst
    SQL, Data Cleaning, Data visualization, BI Tools
  • Data Engineer
    ETL Development, Big Data Technologies
  • Machine Learning Engineer
    Machine Learning Frameworks, Deep Learning, Model Deployment
  • Backend Developer
    Server-Side Development, APIs, Databases, Cloud & Containerization, Testing Frameworks
  • Frontend Developer
    HTML, CSS, JavaScript, React, Git
  • 2025.08-Current
    Software Engineer Intern At VTC
  • 2023.01-2025.03
    Teaching Assistant at Halıcıoğlu Data Science Institute
  • 2024.06-2024.08
    Data Analyst Intern At California Policy Lab
  • 2023.06-2024.06
    ML Engineer Intern At Scripps Research
  • 2023.07-2024.01
    Data Scientist Intern At IMD Business School
  • 2025.09 - 2027.05 (tentative)
    M.S. Computer Science at UC San Diego
  • 2021.09 - 2025.03
    B.S. Data Science at UC San Diego
    Minor in Business Economics

My Projects

Scalable ML Inference System on AWS

SepsisDetect is an AI-driven pipeline that integrates chest X-ray images and patient metadata, using ResNet and CatBoost models to predict sepsis risk within hours of admission.

Food Delivery Backend System

A scalable Java-based backend for a food delivery platform. This system supports core business logic such as user management, order processing, menu item handling, and real-time order notifications.

Latent Classes of Sepsis Patients

This study analyzed over 36,000 EHRs to perform latent class analysis, identifying patient subgroups based on clinical patterns and assessing their associated sepsis risks.

ML Pipeline for Image Extraction & predictive models of Cardiac disease

This project utilizes a large-scale MRI image dataset to extract key imaging features using CNN model and applies these features to predictive models for diagnosing cardiac disease.

Future Readiness Score

This project utilized sentiment analysis of company news and machine learning models to help organizations assess their readiness for future business challenges and trends.

FinEmotionFusion

FinEmotionFusion is an emotion detection system designed for financial phone calls, leveraging early fusion of audio and text modalities to enhance accuracy and context-awareness.

Resume

Boqi (Bobby) Zhu

San Diego, CA, 92122, United States

bobbyzhu.work@gmail.com | linkedin.com/in/bobby-zhu | github.com/Bobby-Zhu

Education

University of California San Diego

M.S. in Computer Science (GPA: 4.0/4.0)

Sept 2025 – May 2027 (expected)

University of California San Diego

B.S. in Data Science (GPA: 3.9/4.0) | Minor: Business Economics

Sept 2021 – Mar 2025

  • Coursework: Software Engineering Principles, Algorithm Design, Machine Learning, Database, Deep Learning, Data Visualization

Experience

Software Engineer Intern

VTC, San Diego, CA

Aug 2025 – Present

  • Built a DistanceService (Ruby) with PostgreSQL (JSONB) + Redis to serve millions of daily lookups for Dial-A-Ride scheduling, using composite indexes and caching for low-latency performance.
  • Designed a modular architecture (Storage, Provider adapters) enabling extensible providers without modifying core logic.
  • Developed 40+ unit tests with stubs and mocks to validate database interactions, provider adapters, and failure handling.

Data Analyst Intern

California Policy Lab, Los Angeles, CA

Jun 2024 – Aug 2024

  • Automated retrieval and transformation of 800 GB of consumer credit panel data using SQL Server and R scripts.
  • Developed a Difference-in-Differences regression model in R to estimate the long-term impact of natural disaster compensation on victim credit performance.
  • Implemented ML methods, including Random Forest, based on literature review to identify the most suitable model for the research use case.

ML Engineer Intern

Scripps Research, San Diego, CA

Jun 2023 – Jun 2024

  • Transformed 80 GB of cardiac imaging data on an HPC cluster using 6 shell scripts for distributed processing.
  • Developed a custom ML pipeline, fine-tuned a CNN for feature extraction, and trained an XGBoost classifier to predict cardiac disease, achieving 82% accuracy and 0.77 AUC.
  • Validated the data pipeline with 20+ Pytest unit tests, ensuring reliability and reproducibility.

Data Scientist Intern

IMD Business Institute, Remote

Jul 2023 – Jan 2024

  • Engineered a Business Analytics Index by applying sentiment analysis to corporate news using a fine-tuned BERT model.
  • Automated news and stock data aggregation by integrating 4 external APIs with Python, reducing processing time by 20%.
  • Designed interactive dashboards with Plotly to visualize KPIs and predictive trends for cross-functional teams.

Research

Data-Driven Suicide Prevention Initiative (PRISM)

With Dr. Danks & Dr. Wayne

Sep 2023 – Dec 2024

  • Designed a modularized data integration pipeline to automate ETL processes for 500+ files.
  • Led explainable AI efforts using Random Forest and SHAP values to identify key features from UMAP embeddings of suicide data.

Teaching Experience

Undergraduate Teaching Assistant

Halıcıoğlu Data Science Institute, San Diego, CA

Jan 2023 – Mar 2025

  • Tutored 6 data science courses (~150 students/class), supporting instruction in Python, Java, data structures, and PostgreSQL.
  • Designed demo ETL pipelines with AWS S3, Lambda, RDS, and Grafana to teach scalable data workflows.

Projects

Food Delivery Backend System

Spring Boot, MyBatis, Redis, WebSocket, Nginx

Jan 2024 – Apr 2024

  • Developed and deployed 70+ RESTful API endpoints supporting user, order, and menu management in a scalable food delivery system.
  • Implemented JWT-based authentication and integrated Redis with Spring Cache to accelerate access to frequently used data.
  • Enabled real-time order alerts via WebSocket and configured Nginx as a reverse proxy for seamless multi-service communication.

Scalable ML Inference System on AWS

AWS ECS, ECR, Lambda, SageMaker, EventBridge, GitHub Actions

Oct 2023 – Dec 2023

  • Deployed a CNN model backend with Flask on AWS ECS and an Application Load Balancer for scalable inference.
  • Automated ECS updates using AWS Lambda and EventBridge triggers on S3 changes.
  • Provisioned SageMaker compute resources with the ML team, optimizing performance and cost for training on 40 GB of data.
  • Led deployment of an internal documentation site hosted on AWS, with automated CI/CD via GitHub Actions.

Microblogging Web App

Ruby on Rails, PostgreSQL, TailwindCSS, Docker

Mar 2023 – Jun 2023

  • Built a Twitter-style microblogging app with authentication, email activation, feed aggregation, and follow/unfollow features.
  • Wrote 30+ unit and integration tests with Minitest to validate authentication, model validations, and user interactions.
  • Containerized the development environment with Docker and DevContainer, reducing setup time to under five minutes.

Skills

  • Programming & Tools: Python, Java, Ruby, SQL, R, Bash, JavaScript (React), HTML, CSS, GitHub, Docker
  • Data & ML: Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, XGBoost, Spark, PostgreSQL, MySQL, Tableau, Power BI
  • AWS Cloud: S3, ECS, Lambda, SageMaker, Redshift, EC2, Glue, RDS, DynamoDB, CloudWatch, IAM

Contact Me

bobbyzhu.work@gmail.com

858-291-3844

Download CV