Zeyuan Xu is a master's student in electrical and computer engineering at Carnegie Mellon University with a 3.6 GPA. He received his bachelor's degree in electrical and computer engineering from Ohio State University with a 3.8 GPA and a minor in computer and information science. His experience includes internships at Amazon Web Services and as a research assistant at Ohio State University. He has strong programming skills in Java, C, Python and engineering tools like Django, MATLAB, Arduino and Apache Spark. His projects include building distributed computing systems on AWS, developing a distributed file caching system, and creating a dynamic storage allocator and smart home trash can. He has published research on perovskite solar cells.

1. Zeyuan Xu
zeyuanx@andrew.cmu.edu | linkedin.com/in/zeyuanxu1995 | (614) 886-6864
EDUCATION
Carnegie Mellon University Pittsburgh, PA
Master of Science, Electrical and Computer Engineering December 2019
GPA: 3.6/4.0, Coursework: Storage System (Fall 2019, 15-746), Distributed Systems (15-640, Spring 2019),
Advanced Cloud Computing (15-719, Spring 2019), Web Application Development (17-637, Spring 2019)
The Ohio State University Columbus, OH
Bachelor of Science, Electrical and Computer Engineering May 2018
GPA: 3.8/4.0, Minor: Computer and Information Science, Graduated with Research Distinction Honor
SKILLS
Programming Languages: Advanced - Java, C; Intermediate – Python; Basic - JavaScript, Go, C++
Engineering Tools & Technology: Advanced - Django, MATLAB; Intermediate - Arduino, Apache Spark
EXPERIENCE
Amazon Web Services – AWS Lex Science Team Seattle, WA
Software Engineer Intern May 2019 – August 2019
• Designed and built an audio collection framework from scratch for spoken and IVR scenario on AWS Connect,
with scalable support of up to 1,000 simultaneous conversation collections, to satisfy heavy use over Amazon AI Team
• Established a completed phone call pipeline on AWS Connect that supports user verification, human/human and
human/bot conversation, and conversation audio capturing, parsing, and preprocessing in the real-time with <1s delay
• Devised a WebApp interface leveraging Django to manage the framework pipeline, users and data collection progress
The Ohio State University – NARS Laboratory Columbus, OH
Research Assistant September 2016 - May 2018
• Conducted research on characterization and optimization of Perovskite Solar Cell guided by Prof. Lei Cao
• Constructed in-situ experiment environment from scratch to characterize solar cell samples under radiation
• Developed tools utilizing Java, VBA, MATLAB to conduct data modeling, simulation and graphing
SELECTED PROJECTS
ETL Processing on AWS with Apache Spark
Carnegie Mellon University, Spring 2019 Keywords: Cloud Computing, Map-Reduce, Python
• Developed a distributed computing program to preprocess corpus crawled from the Internet for ML model training
• Launched Apache Spark + HDFS clusters on AWS EC2 to compute datasets on parallel utilizing map-reduce method
• Optimized performance by improving memory utilization and parallel efficiency to finally make the program able to
process 150GB datasets stored in HDFS using 16 slave instances with 5G RAM within 30 minutes
Distributed File-Caching System
Carnegie Mellon University, Spring 2019 Keywords: Distributed Systems, RPC, Caching, Java, C
• Implemented an interposition library for client to operate remote procedure call (RPC: open, read, write, close, etc.)
• Developed a file-caching proxy that maintains an LRU cache to keep track of RPC requested files from one or more
concurrent clients and uses an RMI class to fetch and update files on the server at a whole-file granularity
• Applied open-close semantics protocol to ensure concurrent clients read and modify files without interference
Dynamic Storage Allocator
Carnegie Mellon University, Fall 2018 Keywords: Computer Systems, Memory Management, C
• Realized a general-purpose dynamic storage allocator for C by implementing a self-defined “Malloc” library
• Applied segregated explicit lists (data structure) and first-fit block search (algorithm) for space management in heap
to achieve better performance (~35000 KOPS) and smaller memory utilizations (56.3%)
• Optimized space utilization to 74.1% by eliminating footer in allocated blocks and handling small-size block
Smart Home Trash Can
Ohio State University, Spring 2018 Keywords: Cloud Computing, Capstone, Arduino, Python
• Constructed a smart trash can using configured Arduino, servo motor, IR break beam sensor, capable of
following certain voice commands, detecting trash can level, and informing trash can state to users.
• Developed on AWS Platform with AWS Lambda API and Python to register a “thing” on AWS IoT as the smart
trash can device and built the Alexa skill to respond to certain voice command within 3 seconds
PUBLICATION
• Organohalide Lead Perovskite Solar Cell: More Stable than Glass under Gamma-Ray Radiation
Shuang Yang1
, Zeyuan Xu1
, Xue Sha2
, Kandlakunta Praneeth3
, Jinsong Huang*, Lei Cao*, ADV MATERIALS