About Me

Hello! I’m Junxi (Eric) Li, a passionate Computer Science and Mathematics student at the University of California, San Diego (UCSD). With a minor in Cognitive Science specializing in Machine Learning and AI, I’m deeply fascinated by the intersection of artificial intelligence, software engineering, and problem-solving.

Schedule 📅

My calendar is embedded below. All events are tentative and subject to change.

Academic Journey & AI Passion

My academic journey reflects my commitment to excellence, maintaining a perfect 4.0 GPA while pursuing a challenging dual major. I’ve excelled in advanced coursework spanning Object-Oriented Programming, Data Structures & Algorithms, Computer Systems, and Deep Learning. My completion of Stanford’s Online Deep Learning specialization with a perfect score (100/100) further demonstrates my dedication to mastering AI technologies.

Professional Experience & Projects

My professional experience spans across cutting-edge AI and software development roles. At Afanti.ai, I developed multi-agent systems that leverage Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to enhance AI-powered education. This work not only improved problem-solving accuracy but also made AI explanations more comprehensible and human-centric.

At Zilliz, I’m currently working on innovative solutions that bridge the gap between semantic search and community knowledge sharing. My work involves developing automated pipelines that enhance the accessibility and quality of technical information, demonstrating my ability to apply AI technologies to real-world challenges.

Research & Innovation

As an Undergraduate Researcher at UCSD’s SuperComputer Center, I’m exploring the frontiers of network security and anomaly detection. My work with Papermill and Apache Spark showcases my ability to handle large-scale data processing and analysis. I’m particularly proud of my contributions to an anomaly detection paper that combines BGP data analysis with flow tuple processing.

Looking Forward

I’m constantly seeking opportunities to push the boundaries of what’s possible with AI and software engineering. Whether it’s developing more intuitive user interfaces at Mercury Health or creating sophisticated game engines, I approach each project with enthusiasm and a growth mindset.

My goal is to contribute to the advancement of AI technology while making it more accessible and beneficial to society. I’m particularly interested in:

Large Language Models and their applications
Multi-agent AI systems
Semantic search and information retrieval
Machine learning for security and anomaly detection

I’m always eager to collaborate on innovative projects and learn from fellow technology enthusiasts. Feel free to reach out if you’d like to connect or discuss potential collaborations!

Education

University of California at San Diego

Major: Computer Science & Math
Minor: Cognitive Science-Specification in ML & AI
GPA: 4.0/4.0
Period: Sep 2022 - Current

Relevant Coursework

OOP and programming skills with Java (A+)
Data Structure & Algorithm (A+)
Computer & System (A+)
Stats & Probability (A+)
Theory of Computability (A+)
Linear Algebra (A)
Deeplearning (A+)

Stanford Online & Deeplearning.ai

Passing Score: 100/100
Period: Jun 2023 - Sep 2023
Skills: Build and Train Neural Networks, linear & logistic regression, K-means clustering, and decision tree.

Technical Skills

Programming Languages

Advanced: Python, Java, Javascript, CSS, HTML
Intermediate: C/C++

Tools & Technologies

Advanced: Linux, Django, Angular, Git, Opencv, Docker, Vim, Numpy, Pytorch, Langchain, LangGraph
Intermediate: Tensorflow, redis, Shell/Bash, React, Pandas, Apache Spark

Professional Experience

Software Engineer Intern at Zilliz (Sep 2024 - Current)

Led development of an automated pipeline to extract and rephrase QAs from GitHub discussion page and post on StackOverflow
Spearheaded integration of Milvus with Semantic-route and other open-source projects
Enhanced system functionality and optimized performance for advanced semantic search capabilities in RAG applications

Machine Learning Engineer at Afanti.ai (May 2024 - Oct 2024)

Developed multi-agent system for AI-powered student assistance
Created workflow for automated problem extraction and solution generation
Built AI agents using LangGraph and RAG for improved problem-solving accuracy
Designed and optimized similarity scoring algorithm achieving 90% accuracy

View Full Resume