Thomas Y. Chen

（陈予涛）

I am an incoming first-year undergraduate student and Egleston Scholar at Columbia University in the Fu Foundation School of Engineering and Applied Science. Before Columbia, I was a high school student at the Academy for Mathematics, Science, and Engineering. I'm interested in computer vision, machine learning, and AI ethics. If you are interested in these things as well, let's chat!

chen.thomas [at] columbia.edu / Google Scholar / CV / Github / Linkedin

Research

My CS journey all started with Ethan Weber at MIT CSAIL (Torralba Computer Vision Lab) and Summer STEM Institute. Previously, I worked in Dr. Haimin Wang's group at the New Jersey Institute of Technology (NJIT) Center for Solar Terrestrial Research with then-PhD student Jiasheng Wang.

	Progress and challenges in glacial lake outburst flood research (2017-2021): a research community perspective Adam Emmer, Simon K Allen, Mark Carey, Holger Frey, Christian Huggel, Oliver Korup, Martin Mergili, Ashim Sattar, Georg Veh, Thomas Y Chen, Simon J Cook, Mariana Correas-Gonzalez, Soumik Das, Alejandro Diaz Moreno, Fabian Drenkhan, Melanie Fischer, Walter W. Immerzeel, Eñaut Izagirre, Ramesh Chandra Joshi, Ioannis Kougkoulos, Riamsara Kuyakanon Knapp, Dongfeng Li, Ulfat Majeed, Stephanie Matti, Holly Moulton, Faezeh Nick, Valentine Piroton, Irfan Rashid, Masoom Reza, Anderson Ribeiro de Figueiredo, Christian Riveros, Finu Shrestha, Milan Shrestha, Jakob Steiner, Noah Walker-Crawford, Joanne L. Wood, Jacob C. Yde Natural Hazards and Earth System Sciences (Preprint), 2022 Paper
	Multi-Temporal Deep Learning-based Social Media Analysis for Disaster Relief Thomas Y Chen MobiSys, 2022 Paper / Poster
	Interpretability in Convolutional Neural Networks for Building Damage Classification in Satellite Imagery Thomas Y Chen NeurIPS Tackling Climate Change with Machine Learning Workshop, 2020 (Spotlight Oral Presentation) Paper / arXiv / Video
	MonarchNet: Differentiating Monarch Butterflies from Butterflies Species with Similar Phenotypes Thomas Y Chen NeurIPS AI for Earth Sciences Workshop, 2020 Paper / arXiv / Abstract / Poster
	PreDefense: Defending Underserved AI Students and Researchers from Predatory Conferences Thomas Y Chen Proceedings of Machine Learning Research, 2021 Paper / arXiv

Selected Talks

	Deploying AI for Climate Adaptation: A Spotlight on Disaster Management Thomas Y Chen Open Data Science Conference, April 2022
	Scaling up AI for Confronting Climate Change Thomas Y Chen ML Conference Berlin, December 2021
	Mitigating Dataset Biases for Inclusive, Deployable, and Accessible Artificial Intelligence Technologies Thomas Y Chen SIGGRAPH, August 2021
	Deep Learning with Python for Natural Disaster Relief from Satellite Imagery Thomas Y Chen SciPy, July 2021
	Convolutional Neural Networks for Damage Assessment and Disaster Relief Thomas Y Chen Machine Learning Week Europe, June 2021
	Application-based Deep Learning with PyTorch Thomas Y Chen Open Data Science Conference, April 2021
	AI and Sustainable Energy Thomas Y Chen Applied Machine Learning Days, April 2021
	Unsupervised Category-Specific Mesh Reconstruction: A Future ML Opportunity Thomas Y Chen ML Conference Munich, April 2021
	Deep learning-based remote sensing for infrastructure damage assessment Thomas Y Chen European Network for Earth System Modeling (Workshop on New Opportunities for ML and AI in Weather and Climate Modelling), March 2021
	Interpretable Deep Learning Models for Humanitarian Disaster Relief Thomas Y Chen AAAI Spring Symposium: Leveraging Systems Engineering to Realize Synergistic AI/ML Capabilities, March 2021

Experience

Software Development Intern at Conatix

Misc

A few of my other interests from past to present:

Debate:
Languages: Check out translated versions of my site in 中文 and español.
Food:
Travel:

Source code from Jon Barron's website.