Alex Huang

Hello! I’m Wei-Chun, also known as Alex, and I currently work as a Machine Learning Engineer. My passion lies in affective computing and the applications of deep learning. I have extensive experience in areas such as Computer Vision and Recommendation Systems.

I earned a Bachelor’s degree in Computer Science from UW-Madison, where I was fortunate to work under the guidance of Prof. Yin Li and Prof. Tim Rogers . I was also honored to receive the 2024 Hilldale Research Fellowship for my Senior Thesis.

Email / CV / Scholar / LinkedIn / Github

Publications

	A Data-driven Approach to Facial Expression Recognition Wei-Chun Huang Senior Thesis (In Progress) Using Transformer based VaDE model to cluster facial expressions extracted using a 3D face reconstruction model (EMOCA).
	Uniting theory and data: The promise and challenge of creating an honest model of facial expression Sophie Wohltjen, Y. Ivette Colon, Zihao Zhu, Karina Miller, Wei-Chun Huang, Bilge Mutlu, Yin Li, Paula Niedenthal1 Cognition and Emotion (In Press) Discuss the resources that are available to help researchers build a more ecologically valid model of facial expressions.
	Measuring large group synchrony and social connection with Machine Learning and Computer Vision Michelle Marji, Siddharth Suresh, Wei-Chun Huang, Alexis Liu, Karina Miller, Joshua Jackson, Christian Andresen, Corey Pompey, Paula Niedenthal Affective Science (In Press) Track and measure synchrony and spatial configurations of large groups using Faster R-CNN.
	Categories vs Semantic Features: What shape the similarities people discern in photographs of objects? Siddharth Suresh, Wei-Chun Huang, Kushin Mukherjee, Timothy Rogers ICLR Workshop, 2024 paper Discovered that model trained to produce category labels and model trained to generate semantic features learned very different representational geometries throughout the network.
	Conceptual structure coheres in human cognition but not in Large Language Models Siddharth Suresh, Kushin Mukherjee, Xizheng Yu, Wei-Chun Huang, Lisa Padua, Timothy Rogers EMNLP, 2023 paper Compared how Large Language Models such as FLAN and GPT structure concepts relative to human cognition.

Other Projects

Below are some of the non-research projects I’ve worked on. Feel free to take a look!

	3D Facial Feature Extraction repo Extract 3D Facial Features from videos and images using SOTA 3D face reconstruction model - EMOCA .
	Video Feature Extraction repo This directory contains the code to extract features from video datasets using mainstream vision models such as Slowfast, i3d, c3d, CLIP, etc.

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