Zhengxu Yan
About Me
I'm currently a senior at UC Berkeley, majoring in Computer Science and Data Science. I have a keen interest in Machine Learning and enjoy staying updated with the latest developments in technology and software. In my free time, I enjoy playing soccer, video games (especially League of Legends), and badminton.
Berkeley, CA
Publications
- Yan, Z., Dube, V., Heselton, J., Johnson, K., Yan, C., Jones, V., Blaskewicz Boron, J., & Shade, M. (2024). Understanding older people's voice interactions with smart voice assistants: a new modified rule-based natural language processing model with human input. Frontiers in digital health, 6, 1329910. https://doi.org/10.3389/fdgth.2024.1329910
- Jones, V. K., Yan, C., Shade, M. Y., Boron, J. B., Yan, Z., Heselton, H. J., Johnson, K., & Dube, V. (2024). Reducing Loneliness and Improving Social Support among Older Adults through Different Modalities of Personal Voice Assistants. Geriatrics (Basel, Switzerland), 9(2), 22. https://doi.org/10.3390/geriatrics9020022
Working Papers
DiT-Serving: Infinitely Long Video Generation Engine with Brick Attention Enhancing Throughput via Continuous Batching
- Integrated Brick Attention into Diffusion Transformer (DiT) models to enable near-infinite video generation, supported by continuous batching to achieve increased throughput.
- Under the guidance of PhD candidate Michael Luo, advised by Dr. Ion Stoica, Prof. of Computer Science, I led the integration of Brick Attention with DiT models, enhancing the system's capacity for extended video generation, and implemented continuous batching techniques that significantly improved system throughput. The manuscript is in preparation for review.
Adaptive Operations Management in Buildings: A Reinforcement Learning Approach for Operational Adaptability in Healthcare Facilities
- Introduced a Reinforcement Learning-based framework to enable adaptive and integrated operations management in healthcare facilities, optimizing spatial, social, and operational performance through coordinated resource sharing.
- Supervised by Dr. Yehuda Kalay and Dr. Davide Schaumann, I utilized deep reinforcement learning (RL) and simulation to develop a smart building management system for the Cardiac Catheterization Lab at St. Bernardine Medical Center.
Work Experience
Teaching Assistant for Large Language Model Agents (CS 194-196)
August 2024 - PresentDepartment of Electrical Engineering and Computer Sciences at UC Berkeley
- Coordinated course logistics, managed lecture recordings, enhanced assignment materials, and provided academic support by addressing student inquiries.
- Assisted in organizing and coordinating the LLM Agents Hackathon, hosted by Berkeley RDI in conjunction with the LLM Agents MOOC, designed to foster innovation, expand the AI agent community, and advance LLM agent technology.
Research Assistant
February 2024 - PresentUC Berkeley Sky Computing Lab
- Competitively selected through UC Berkeley EECS Diversifying Access to Research in Engineering (DARE) and Sky Summer Undergraduate Programs to join the DiT-Serving Project as a research assistant.
- Led a team of 5 research assistants in integrating Ring Attention and Brick Attention into Diffusion Transformer (DiT) models, pioneering scalable video generation techniques.
- Directed continuous batching strategies to optimize system throughput, enhancing performance efficiency across video processing requests.
Research Assistant
February 2024 - PresentUC Berkeley College of Environmental Design
- Competitively selected to join the Smart Hospital Project through UC Berkeley Undergraduate Research Apprentice Program.
- Led a team of 3 research assistants in the development and implementation of a deep reinforcement learning-based smart building management system for the Cardiac Catheterization Lab at St. Bernardine Medical Center.
Machine Learning (ML) Engineer Lead
January 2024 - PresentUC Berkeley School of Public Health
- Selected as lead computer scientist for Rapid Reviews: Infectious Diseases via the UC Berkeley CDSS Discovery Program.
- Independently leveraged a fine-tuned Large Language Model (LLM) to efficiently categorize and identify preprints within the RR\ID domain.
- Led a team of 3 UC Berkeley CS students in utilizing LLM APIs to analyze and provide insights on medical preprints.
- Directed a team of 5 UC Berkeley CS students in engineering scripts to automate the collection of medical preprints.
- Collaborated with the Dean of the UC Berkeley School of Public Health and researchers from UCSF to develop automated systems for academic review.
Research Assistant
April 2023 – September 2023University of Nebraska
- Collaborated with gerontology and nursing researchers to develop a natural language processing (NLP) model designed to automate the processing of speech-to-text data from user interactions with AI-enabled smart voice assistants.
Backend Engineer Lead
October 2022 – December 2022Coffee Tea, Inc.
- Led a team of 3 UC Berkeley computer science students in backend development for a social platform.
- Directed the design and development of backend REST APIs using FastAPI, Poetry, Alembic, and PostgreSQL.
Projects
Machine Learning
Multi-Agent LLM Trading System
August 2024 – PresentPython, Pytorch, Tensorflow, AutoGen
- Developed a multi-agent trading system integrating LLMs with specialized agents for multimodal data processing.
IM2SPAIN Project
January 2024 – May 2024Python
- Employed nearest neighbors (k-NN) to predict geographic coordinates based on CLIP embeddings of geo-tagged images from Flickr.
MNIST Competition
January 2024 – May 2024Python, Pytorch
- Engaged in the Kaggle MNIST classification challenge, leveraging various machine learning techniques including LDA, QDA, Logistic Regression, MLP, SVM, and CNN.
Language Identification RNN
August 2023 – December 2023Python, Tensorflow
- Engineered an RNN to identify word languages, achieving over 81% test set accuracy.
Systems Programming and Software Development
Pintos Operating System
January 2023 – May 2023C, Rust
- Led the development of a comprehensive Pintos operating system, focusing on systems programming, memory allocation, resource management, file systems, networking, and security.
Secure Client Application
January 2023 – May 2023Golang
- Developed a secure client Golang application incorporating cryptographic primitives for authentication and file management.
Gitlet Version Control System
January 2021 – May 2022Java
- Created "Gitlet," a Git-like Version Control System, to streamline tracking and management of code changes across projects.
Education
University of California, Berkeley
Expected Graduation: May 2025Bachelor of Arts in Computer Science and Data Science
GPA: 3.94/4.00, Dean's List, Honors to Date
Coursework:
Principles & Techniques of Data Science (Data C8/C100), Computer Programs (CS 61A), Data Structures (CS 61B), Machine Structures (CS 61C), Discrete Math and Probability (CS 70), Optimization Models (EECS 127), Probability for Data Science (Data C140), Computer Security (CS 161), Operating Systems (CS 162), Efficient Algorithm (CS 170), Computer Vision (CS 180), Artificial Intelligence (CS 188), Machine Learning (CS 189), LLM Agents (CS 194-196).
Brownell Talbot School
2017 - 2021GPA: 4.13/4.00
- Nebraska Class C State Championship team, Jan 2021
- University of Nebraska-Omaha Summer Scholars Program, Aug 2020
- Vex Robotics National rank 19 in Skills challenge, Jan 2020
- Vex Robotics Global rank 44 Programmer, Jan 2020
- Nebraska Math Competition State Finals, 19th place, Jan 2020
- VEX Tournament Champions in multiple robotics tournaments
- Excellence Award in Elkhorn HS VRC & Heartland Regional Robotics Championship
- University of Nebraska-Lincoln Engineering Summer Research Program, Scholarship winner