Hi! 👋 I am a research assistant at MMLab, Nanyang Technological University, advised by Prof.
My research interest lies in generalizable and data-efficient machine learning frameworks for high-level visual recognition 👀 or reasoning 🤔. I develop data collection pipelines, representations, and models for interactive or assistive AI systems.
Previously, I worked with Prof. Alan Yuille and Dr. Zongwei Zhou at Johns Hopkins University, on self-supervised
learning and human-in-the-loop machine learning. Before that, I also spent great time at ByteDance, Alibaba, NUS, and A*STAR Singapore. I obtained my Bachelor’s degree in Information Engineering & Media from Nanyang
Making Your First Choice: To Address Cold Start Problem in Vision Active Learning
NeurIPS Workshop on Human in the Loop Learning, 2022
Multi-task Graph Convolutional Neural Network for Calcification Morphology and Distribution Analysis in Mammograms
Melissa Min-Szu Yao,
Wing P. Chan,
Tech report, 2021
Baconian: A Unified Open-source Framework for Model-Based Reinforcement Learning
Tech report, 2020
CSVAL: Benchmarking Initial Queries in Vision Active Learning, NeurIPS'22 workshop.
OpenPSG: A Dataset and Benchmark for Panoptic Scene Graph Generation (PSG), ECCV'22. [🤗 Hugging Face Demo]
Baconian: Model-based Reinforcement Learning Framework. [Demo]
Reviewer for The Visual Computer, IET Computer Vision, ICML 2022 Workshop.
I host virtual office hours for anyone who wants to share thoughts on CV/ML research, reading (either scientific or not), or any other topics of interest. Please schedule via my calendar.
Last update: Jan 2023      Template