Yusheng Li

Machine Learning Intern @ Zhuhai Watt Electrical Equipment Co., Ltd.

About

I am a current Master's student in Computer Engineering at Columbia University (expected Dec 2026), continuing from my B.S. in Computer Science from the University of Wisconsin–Madison. I gained professional experience as a Machine Learning Intern at Zhuhai Watt Electric Equipment Co., Ltd., where I developed and applied LSTM-based time-series models to forecast 48-hour electric load demand.Before my work, predictions were mostly done manually by inspecting past curves, which was time-consuming and less reliable.By automating this process with machine learning, I improved forecast reliability and enabled real-time monitoring of 10,000+ data points.At Sunwoda, as a BMS System Development Intern, I explored AI adoption in the energy sector and contributed to building a web application using Golang and go-zero. As a Backend Developer in the GE Healthcare Capstone Project, I led database design and API integration, improving query performance by 30% and enhancing annotation efficiency by 20% in a prenatal care annotation system.I also conducted research on erasure coding at UCLA, benchmarking Reed-Solomon and Fountain codes to evaluate trade-offs in distributed cloud storage systems. My technical skills include Java, Python, C, Flask, Docker, and Linux, and I have published research and participated in hackathons.Looking ahead, I am actively seeking opportunities in AI, energy, and healthcare technology, where I can apply machine learning, optimization, and backend engineering to build intelligent and reliable systems.

Country

United States

City

New York City Metropolitan Area

Industry

Computer Software

Skill

Intellgent of things, reinforece Learning , Algorithms, Databases, Operating Systems, Machine Learning, Deep Learning (LSTM, RNN), Optimization, Python, Programming Languages, Object-oriented Languages, Leadership

Experience

Machine Learning Intern

Zhuhai Watt Electrical Equipment Co., Ltd.

2025-2 - 2025-8 · 7 mos

Zhuhai

As a Machine Learning Intern at Zhuhai Watt Electric Equipment Co., Ltd., I developed LSTM-based time-series forecasting models to automate 48-hour electric load demand prediction, replacing manual curve inspection.I collaborated with the engineering team to implement optimization-based scheduling strategies, reducing peak load in simulations.I also supported real-time monitoring of 10,000+ data points to enhance reliability of grid operations. Key Achievements : - Built and deployed LSTM models for load forecasting, improving prediction reliability compared to manual methods. - Designed optimization-based charge/discharge scheduling strategies, achieving 20% peak load reduction in simulation tests. - Enabled real-time monitoring of 10,000+ data points, supporting data-driven decision-making in energy operations.

Backend Developer Intern (Capstone Project)

GE HealthCare

2024-9 - 2024-12 · 4 mos

Madison, Wisconsin, United States

Description: As part of an industry-sponsored capstone project with GE Healthcare, I worked as a Backend Developer focusing on database design, API integration, and system optimization for a prenatal care annotation platform. Key Achievements: - Led database schema design and implemented RESTful APIs, improving annotation efficiency by 20%. - Collaborated with a cross-functional team to integrate backend services with the front-end annotation builder, ensuring seamless data flow and real-time updates. - Presented technical deliverables and progress to GE Healthcare stakeholders, gaining experience in industry-level software development practices.

BMS System Development Intern

Sunwoda Electronic Co., Ltd.

2024-6 - 2024-8 · 3 mos

Shenzhen, Guangdong, China

During my internship at Sunwoda, I explored the application of AI in the energy sector and contributed to the development of a web-based Battery Management System (BMS). I collaborated with the team to design and implement backend services, while also researching ways to integrate AI into energy management solutions. Key Achievements: - Developed and maintained a web application using Golang and go-zero, improving backend performance and enabling real-time processing of 1,000+ concurrent BMS data records daily. - Implemented and tested AI-driven methods for predictive analytics and intelligent control in energy systems, leading to 2 validated pilot models for future adoption. - Collaborated with cross-functional teams to support software deployment and integration, enhancing system stability and reducing bug resolution time by 15%. - Authored technical documentation and supported prototype testing, providing structured guidelines that improved onboarding efficiency for new developers by 20%.