My Journey in Engineering and Innovation

A PDF version of my CV is available here.

Education

• M.S. in Computer Engineering, Columbia University, New York, NY (Aug 2023 - Dec 2024)
  GPA: 3.6/4.0
  Relevant Courses: Algorithms, Cloud Computing, Formal Verifications, Blockchain, Database, Computer Networks, Embedded Systems, Hardware Security, Modeling and Performance, Reinforcement Learning, Content Delivery Networks

• B.S. in Electrical and Computer Engineering, Ohio State University, Columbus, OH (Aug 2018 – Dec 2022)
  GPA: 3.5/4.0, Honors: Cum Laude
  Dean’s List: SP 2020, AU 2020, SP 2021, AU 2021, SP 2022, and AU 2022 Relevant Courses: Operating System, Computer Architecture, Advanced Digital Design, Software Development & Design

Work& Teaching Experience

• Teaching Assistant
  • Introduction to Digital Logic, Ohio State University
  • Jan 2022 – May 2022

Skills

• Programming Languages: C, C++, C#, Assembly, Java, Python, Promela, SystemVerilog, VHDL, HTML
• Software Proficiency:
  • Database Management: DataGrip, MySQL
  • Embedded Development: ArduinoIDE, Xilinx
  • Scientific Computing: MATLAB
  • IDEs: Eclipse, Visual Studio
  • Code Management: Git, GitHub
  • Operating Systems: Windows, Linux
  • AI & Machine Learning: PyTorch, TenserFlow
  • Containerization & Virtualization: Docker, Kubernetes, QEMU, KVM
  • Cloud Computing: AWS, Azure, FaaS
  • CAD: Solidworks
  • Script & Network Monitoring: Wireshark, Bash
  • Security & Debugging: GDB, SMT solver

Research and Project Experience

Blockchain-based Content Distribution Verification Mechanism

Columbia University Aug 2024 – Dec 2024

• Designed and implemented a blockchain-based content distribution verification mechanism with Python, which integrates blockchain and Merkle Tree technologies to ensure data integrity and security in a content delivery network (CDN)
• Developed a decentralized solution utilizing Proof of Work (PoW) and Merkle Trees for real-time data validation and tamper detection, ensuring the reliability of content delivered across distributed nodes
• Simulated a CDN network that successfully verified and distributed content, incorporating blockchain for trust and Merkle Trees for efficient data integrity checks, demonstrating robust handling of data tampering and repair

Reinforcement Learning - Emotion Propagation

Columbia University Aug 2024 – Dec 2024

• Developed EmotionWorld 2D environment and optimized emotion propagation using Python and Deep Q-Network (DQN) reinforcement learning, simulating emotion diffusion in social networks
• Leveraged DQN and graph theory to model emotion propagation dynamics, incorporating personalized emotion parameters (e.g., spread rate, duration, and radius) and utilizing experience replay and target Q-networks to train agents for optimal emotion spreading
• Visualized the emotion propagation process in real-time with Pygame, fine-tuned the model through hyperparameter adjustments, and enhanced performance and stability through Epsilon exploration-exploitation strategies

ARM TrustZone Streaming Client Project (Hardware Security)

Columbia University Jan 2024 – Aug 2024

• Designed and implemented a secure streaming media client using C++ based on ARM TrustZone (TZ) technology to ensure the confidentiality of video content
• Developed a Rich Application (RA) to receive encrypted video streams from the server and pass them to the Trusted Application (TA) for decryption
• Created the TA application to securely store the private key and provide video decryption functionality, leveraging the OP-TEE framework to simulate the communication between TEE and Rich Execution Environment

Formal Verification (CDN Proxy System)

Columbia University Aug 2023 – Dec 2023

• Utilized Promela language and SPIN model checker to perform formal verification of a CDN proxy system, ensuring the security and stability of multithreaded concurrent communication
• Validated the system’s safety properties (e.g., preventing deadlocks, ensuring mutual exclusion, avoiding message corruption) and liveness properties (e.g., message retransmission), enhancing system reliability and fault tolerance
• Designed and verified a proxy system handling multiple concurrent client requests, addressing DNS load balancing and thread synchronization issues, and used SPIN for state-space exploration to detect and resolve potential deadlocks and resource conflicts, improving system efficiency and error detection

Build an Online Job Search Platform

Columbia University Aug 2023 – Dec 2023

• Crafted an intuitive user interface with customizable features through the AWS Management Console with a group
• Leveraged Amazon’s Simple Storage Service (S3) as the primary storage mechanism for all application data and Python as the implementation language, ensuring high security, real-time updates, and efficient data management
• Adopted a modular approach by designing and deploying different modular using AWS microservices

GAN - Adding Noise to Discriminator

Ohio State University Jan 2022 – Dec 2022

• Developed an automated fuzzing system to enhance image quality by dynamically adding noise to the discriminator and implementing a feedback mechanism to adjust noise based on model performance, optimizing the training process
• Created training and testing datasets in Python with defined epochs and learning rates for both the generator and discriminator
• Monitored and analyzed loss trends to evaluate the impact of noise on the discriminator’s ability to improve generated image quality

Anti-Racist: Air Quality Analysis and Awareness Project

Ohio State University Aug 2022 – Dec 2022

• Collected particulate matter data across 14 zip code regions in Columbus, OH using GP2Y1010AU0F and KEYESTUDIO PM2.5 sensors
• Analyzed air quality disparities between affluent, predominantly white neighborhoods and underserved, racially diverse communities
• Built an interactive website to visualize collected data, explain project findings, and provide resources for community-led studies

Smart Cane (Assistive Technology)

Cornell University June 2022 – July 2022

• Developed and integrated a Robot Operating System (ROS) embedded system using Raspberry Pi to control ultrasonic sensors, vibration motors, and cameras for real-time navigation and obstacle detection for blind users
• Implemented A* path planning and PID control algorithms using Python to optimize movement and ensure precise navigation
• Programmed in Python to process sensor data, control actuators, and manage haptic feedback for user guidance

Contact Information

• Email: yizhiw2024@gmail.com
• LinkedIn: Yizhi Wang