Hello! I'm Yongchen Qian. Currently mastering the intricacies of Software Engineering at Carnegie Mellon University's Silicon Valley campus, I hold a Bachelor of Science in Computer Science from Emory University. As a full-stack software engineer, I seamlessly blend the worlds of front-end and back-end development, and I'm keenly exploring internship and full-time opportunities to further sharpen my skills and contribute to innovative teams. When I'm not immersed in code or solving software challenges, you can find me on the soccer field or deep in the world of PC building, where precision and performance matter just as much. Looking forward to connecting and collaborating!
Collected approximately 900,000 media items from Instagram and Facebook. Utilized OpenCV, TensorFlow, and ImageAI to create datasets that analyze representation and biases from the top 100 brands over the past decade.View Details
Developed detailed datasets targeting the gaming industry for automated machine learning and multimodal classification. I produced ten benchmark result sets using single-modality models like GBM, MLP, RoBERTa, Electra, Vit, and SWIN, and multi-modality models with AutoGluon and AutoMM. A related paper has been submitted for review to EMNLP 2023.View Details
Under the mentorship of Dr. Davide Fossati from Emory University between Jan to Jun 2022, I utilized OpenCV for live camera input analysis in Java and Python. This feature was integrated with QTest, Emory CS's testing system. I also crafted a Java program using the OpenCV library that identifies faces, notifying the user if no face is detected in the camera feed.
Under the guidance of Dr. Fan Zhang from MIT between Jul to Sep 2021, I gained expertise in Docker and its associated management tools, including Kubernetes and HELM. I deployed web applications, integrated with a MySQL database, to log IP addresses and access times using Kubernetes. Additionally, I familiarized myself with the Kubernetes management tool operator and its Operator Lifecycle Management.
Collaborated with a 7-member team to develop an online platform featuring a variety of poker and card games using Unity. The game supports both single-player and multiplayer modes. We incorporated a MySQL database on GCP to facilitate user registration, login, and manage inventories including emojis, backgrounds, cards, and music.View Details
House sale price prediction using machine learning algorithms: decision tree, linear regression, kNN, kMeans.View Details
Credit to Easy Tutorials