Carnegie Mellon Univerisity                                                                                                                                                                                    Pittsburgh, PA

Master of Science in Mobile and IoT Engineering                                                                                                                                            Aug 2021 - Present

Taken Courses 

• 15-513 Introduction of Computer Systems

• 15-746 Storage Systems

• 15-618 Parallel Computer Architecture and Programming

• 15-640 Distributed System

• 14-741 Introduction to Information Security

• 14-740 Computer Networks                 

• 14-642 Introduction to Embedded Systems

• 14-848 Cloud Infrastructure

Proceeding Courses

• 15-645 Database Systems

• 6.824   Distributed Systems

• 6.828   Operating Systems                                        

Raft                   Dec 2022 - Feb 2023

• Ongoing

Kernel   Sep 2022 - Nov 2022

• development of a bootloader and other components

• implementation of interfaces, MMIO, and a sensor-driven application

• implementation of interrupt-based functionality, user-space programs, and system calls

• implementation of context switching and task management, rate-monotonic scheduling, priority-ceiling protocol, isolation, and synchronization

MapReduce                                                                                                                                                                                              Sep 2022 - Nov 2022

• Implemented MapReduce with peer-to-peer file transfer from scratch.

• Provides fault tolerance, concurrency, and safe file transfer functionality.

Two-Phase Commit                                                                                                                                                                            Apr 2022 - May 2022

• Designed a Two-Phase Commit protocol by using write-ahead logging that can tolerate message delay, message loss, node failures, and cascading failures during recovery.

Auto Scaling                                                                                                                                                                                  Mar 2022 - Apr 2022

• Thoroughly analyze the time for different operations, utilize system properties, and identify bottlenecks in a distributed system by using metrics like arrival rate, queue length, and response time to make scaling decisions.

• Design identification system, sampling system, auto-scaling system, cool-down system, smart-drop system, and cache system to improve system performance and handle special cases.

Distributed File System                                                                                                                                                                        Feb 2022 - Mar 2022

• Designed and implemented a check-on-use cache consistency protocol at whole file granularity, while maintaining one-copy semantic.

• Utilized Java RMI and Java threading to handle multiple concurrent clients robustly and ensured open-close session semantics on concurrent file access.

• Used LRU to manage a fixed-size cache containing variable-sized files and support open, close, read, write, sleek, and unlink system calls.

RPC-Based File System                                                                                                                                                                     Jan 2022 - Feb 2022

• Designed serialization protocol and implemented distributed file system that supports some basic syscalls and multiple concurrent clients.

Hybrid File System                                                                                                                                                                                 Oct 2021 - Dec 2021

• Designed hybrid file system with FUSE to support 20+ syscalls using local SSD and AWS S3 for persistent storage.

• Implemented deduplication (Rabin Fingerprinting), client caching, file system snapshot and crash recovery.

Flash Translation Layer                                                                                                                                                                           Sept 2021 - Oct 2021

• Developed a fully functional FTL for SSD in C++ supporting read/write address translation and garbage collection using improved cost-benefit analysis with deviation from average erases as additional parameters from scratch.

• Implemented wear-leveling mechanism by data blocks remapping, which drops erase times by 1/3 and write amplification by 1/2, and data migration by data temperature, which supports full-range wear leveling.

Dynamic Memory Allocator                                                                                                                                                                     May 2021 - Aug 2021

• Implemented a fast and efficient dynamic memory allocator by small blocks and segregated free lists, which realized important memory operations including malloc, free, realloc, etc from scratch.

• Achieved 74.3% memory utilization and 11803 Kops/sec throughput. 

NVIDIA                                                                                                                                                                                                               May 2022 - Aug 2022

Position: Software Engineer Intern - Map Engine       Santa Clara, CA, US

• Worked on a project in an autonomous-vehicle data pipeline called track-selection. It consumes updated road data, runs complicated algorithms, and generates a new regional map, which requires lots of computing resources.

• Re-architected the track-selection workflow preventing clusters from getting stuck due to resource limitations by moving Flink workers out of the loop and combining Flink as a Job Scheduler and AWS as computing units.

• Dockerized the track-selection module by using a multi-stage build, and integrating it into the CICD pipeline.

• Implemented a job scheduler client, which schedules tasks and enables a retry mechanism with scaling up, when failures happen.

Machine Learning Application in Disaster Risk Assessment                                                                                                                      Feb 2020 - Jun 2020

Thesis (supervised by Prof. Leng)                                                                                                                                                                                 Chengdu, CN

• Researched on predicting mud-rock flow disaster through data mining on disaster dataset

• Implemented disaster data labeling by applying K-means algorithm

• Integrated the multi-class SVM and BRF neural network model. Used Gaussian kernel function on both modules to implement the prediction model and applied a genetic algorithm for hyper-parameter tuning to optimize for the highest prediction accuracy.

• Achieved prediction accuracy of 83.98% on real-world data set. Achieved higher model performance and accuracy than ordinary SVM model or BRF neural network alone.

An Improved SMT-Based Scheduling for Overloaded Real-Time Systems                                                                                             May 2018 - May 2019

Research Assistant (supervised by Prof. Liao )                                                                                                                                                             Chengdu, CN

Vice President, Student Union, School of Cyber Security                                                                                                                           Feb 2018 - Feb 2019

Programming Language & Platform: Java, C/C++, SQL, JavaScrip, MongoDB, PostgreSQL, CUDA, ISPC, OpenMP