yunjia zhang

I am currently pursuing my BS in Computer and Electrical Engineering at Carnegie Mellon University, with a minor in Computer Science, expecting to graduate in May 2025. I have passed the Fundamentals of Engineering (FE) exam and earned my Engineer in Training (EIT) certification. My passion lies in applying deep learning techniques and building scalable software solutions for real-world problems.

Over the past few years, I've gained extensive experience in software engineering, working with diverse technologies across academia and industry. During my internship at Hisense, I contributed to training AI models, optimizing hyperparameters, and enhancing performance, achieving successful model deployments. My research at Duke University's FuNCtions Lab focused on developing deep learning-based systems, which led to a publication at Mobicom 2024.

In addition to my technical expertise, I have developed software tools and simulations, contributed over 2,000 lines of code in Python and MATLAB, and have strong skills in languages like C, Java, and Verilog. I'm proficient in Linux environments and enjoy working on projects involving multi-threaded web proxies, game design, and AI-based systems.

I'm always open to exploring new opportunities where I can contribute my knowledge in engineering, software construction, and software development to impactful projects. Feel free to reach out if you're interested in discussing potential collaborations or opportunities!
 

I am a skilled Software Engineer and Research Assistant with a strong background in deep learning, signal processing, and software development. At Duke University’s FuNCtions Lab, I contributed to a deep learning system using ResNet architecture to decode Wi-Fi PHY layer properties from sub-Nyquist sampled signals, resulting in a publication at Mobicom 2024. Previously, I worked at Hisense on AI model development for the Higpt 1.0 project, focusing on dataset preparation and model optimization. At Carnegie Mellon’s Human-Computer Interaction Lab, I developed a simulation tool for actuator design, with findings published at CHI 2023.

Carnegie Mellon University

• Bachelor of Science in Computer and Electrical Engineering, Minor in Computer Science
• Expected Graduation: May 2025
• Cumulative GPA: 3.53/4.00
• Passed the Fundamentals of Engineering (FE) exam for Engineer in Training (EIT), 10/2024