Te-Lin Wu (吳德霖)
PhD Student
University of California, Los Angeles
Email: telinwu [at] cs (dot) ucla (dot) edu
Google Scholar / LinkedIn / Github
I am open to 2024 industry job opportunities!
If you think I might be a good fit for your team/group, I'm delighted to chat!
I am a final year PhD student at UCLA PlusLab advised by Nanyun (Violet) Peng,
where my research focuses on multimodal models across NLP and computer vision.
I have also worked with Joseph J. Lim on reinforcement learning and vision for robotics topics.
Prior to PhD, I obtained my M.S. at Stanford University where I was advised by Silvio Savarese,
and I did my undergrad at National Tsing-Hua University (國立清華大學).
Over the summers, I've been lucky to work as research interns in several wonderful groups, including
Google Research, Meta Reality Labs, Amazon AI, and Adobe Research.
COM2SENSE: A Commonsense Reasoning Benchmark with Complementary Sentences
A dataset for complementary commonsense reasoning collected via a model-in-the-loop gamified session.
MELINDA: A Multimodal Dataset for Biomedical Experiment Method Classification
A dataset for multimodal biomedical method classification.
LAMPRET: Layout-Aware Multimodal PreTraining for Document Understanding
ViGIL Workshop, NAACL 2021 /
Paper
A pre-training paradigm to exploit document layout to learn a document representation.
Program Guided Agent
ICLR 2020
A framework to programmatically control an RL-trained agent.
Demo2Vec: Reasoning Object Affordances from Online Videos
CVPR 2018
Learning to infer object affordance with a video demonstration of how to interact with objects.
Feedback Networks
CVPR 2017
A study of feedback mechanism of convolutional neural networks.