As a passionate Machine Learning Engineer and Software Engineer, I blend a deep understanding of computer science with specialized skills in machine learning to create innovative solutions. With a Master's in Electrical Engineering from the University of Southern California and a Computer Science undergraduate degree from UC Irvine, I have a solid foundation in both theoretical and practical aspects of this dynamic field.
My professional journey includes impactful experiences like my internship at Qianxun Spatial Intelligence Inc. in Shanghai, where I developed web-based tools for image annotation and contributed to advanced 3D city reconstruction projects. At the California Plug Load Research Center, I honed my skills in energy efficiency improvement through smart home technology, integrating Amazon Alexa into our systems for enhanced user interaction.
In the realm of research, I have participated in the MICCAI 2020 RibFrac Challenge, where our team's AI model for rib fracture detection and classification ranked in the top thirty globally. Furthermore, my leadership in the Minecraft Mini-Game AI Design project showcases my ability to innovate and apply machine learning in diverse environments.
I am proficient in various programming languages, including C/C++, Python, Java, and JavaScript, and am well-versed in tools and libraries like PyTorch, Keras, AWS Sagemaker, and Docker. Beyond technical skills, my experience in project management, team leadership, and mentoring underscores my all-rounded capabilities in this field.
I am always looking for opportunities to apply my skills in machine learning and software engineering to new and challenging problems. Feel free to connect with me to explore potential collaborations or just to exchange ideas in the realm of technology and innovation.
Developed a web-based offline tool for annotating street view imagery, enabling precise labeling of lane features. Contributed to a building/structure segmentation model using point cloud data, advancing 3D city reconstruction efforts. Led the development of the PypptRoadSign Python library for automated construction of SVG road signs.
As a Data Analytics Intern in Guangzhou, I was responsible for crawling and managing daily stock transaction information, storing data into the company's research institute database. My role also included querying transaction data for specific dates or intervals and presenting it in tabular or visual formats to assist with analysis.
Worked on a team developing a system to monitor household appliance energy usage, improving efficiency by 20%. Led the Amazon Alexa integration with the monitoring system, leveraging Amazon AWS services to develop, test, and collect data for the VUI and GUI.
Coached 30-50 students per semester in foundational programming and lab assignments. Assisted in syllabus construction, development of learning materials, and course website construction.
Pursuing a Master's in Electrical Engineering with a focus on Convex Optimization, Advanced Deep Learning Systems, Cloud Computing, and Distributed Systems. My coursework and projects are centered around Hardware IoT and Remote Direct Memory Access, preparing me to address complex challenges in the field of Electrical Engineering and Machine Learning.
Graduated with a Bachelor's degree in Computer Science, complemented by a minor in Data Science. I delved into Software Engineering theory, Algorithms and Data Structures, Database Principles and Applications, Machine Learning, and Data Mining. My education here laid a strong foundation for my technical skills and analytical thinking.
Coursistant is an innovative AI-driven platform designed to transform educational interactions. Tailored for specific academic fields, it offers customizable Q&A environments, making it perfect for students and experts alike. The platform ensures that all inquiries receive accurate and current responses by allowing educators to easily update and manage content. This tool not only enhances learning but also supports complex research needs, positioning it as an essential educational technology in both classroom settings and professional research environments.
View ProjectThe PypptRoadSign Library Project is a pioneering Python library developed to leverage the Microsoft PowerPoint Python interface for automated construction of SVG road signs. This innovative tool integrates seamlessly into team workflows, enabling members to effortlessly transform spatial data from text and entity detection networks into precise SVG road sign representations.
View ProjectAs the Course Project Leader from Sep 2019 to Dec 2019, I led the development of an innovative AI player in Minecraft, utilizing the Malmo Python library. This AI was adept at dodging fireballs and earning credits, showcasing advanced capabilities in a dynamic gaming environment. A significant part of the project involved setting up a specialized training environment for the AI, where the Deep Q-Learning algorithm was employed to facilitate effective learning. By leveraging GPU Acceleration, we were able to expedite the training process significantly, enabling the AI to attain essential intelligence and react intelligently within the game's context.
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