Kung-hsiang Huang
Research Scientist at Salesforce
Los Angeles, California, United States
Summary
🤩
Rockstar🎓
Top SchoolKung-hsiang Huang is a research scientist at Salesforce AI Research with nine years of experience blending rigorous NLP research and practical ML engineering. His academic work on agentic, trustworthy, and multimodal AI has led to publications at NAACL, ACL, EACL and COLING following a PhD at UIUC under Prof. Heng Ji, and he was awarded the Amazon Science Ph.D. Fellowship. He focuses on fact-checking, faithfulness, and factual error correction while also shipping applied models—his GitHub shows hands-on work building CNN/LSTM/GRU pipelines for cryptocurrency price prediction and improving input data processing. A former co-founder and CTO of Rosetta.ai with internships at AWS and Salesforce, he pairs entrepreneurial product experience with research depth to make AI more trustworthy. Based in Los Angeles, he is driven by the mission to reduce misinformation through robust, deployable AI systems.
10 years of coding experience
8 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of Southern CaliforniaExchange program, Computer Science, Exchange program, Computer Science at Georgia Institute of TechnologyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Illinois Urbana-ChampaignHong Kong University of Science and Technology (HKUST)
English, Chinese
Github Skills (21)
fasterrcnn10
gru10
python10
machine-learning10
data-preprocessing10
mask-rcnn10
keras10
tensorflow210
lstm10
deep-learning10
tensorflow10
faster-rcnn10
evaluation9
bitcoins9
bitcoin9
Programming languages (3)
Github contributions (5)
khuangaf/CryptocurrencyPrediction
Sep 2017 - Jun 2019
Predict Cryptocurrency Price with Deep Learning
Role in this project:
Data Scientist & ML Engineer
Data Scientist & ML EngineerContributions:29 commits, 23 pushes, 5 comments in 1 year 9 months
Contributions summary:Kung-hsiang primarily focused on building and refining deep learning models for cryptocurrency price prediction. Their contributions include implementing and optimizing Convolutional Neural Networks (CNNs), Long Short-Term Memory networks (LSTMs), and Gated Recurrent Units (GRUs) within the project. They also restructured the input data processing pipeline and performed experiments to improve model performance with regularization techniques. Several commit messages also indicate they have been working on plotting and evaluating model results.
pythondeep-learningmachine-learningpredictcryptocurrency
rosetta-ai/rosetta_recsys2019
Jul 2019 - Dec 2019
RosettaAI Solution for the ACM Recsys Challenge 2019
Contributions:40 commits, 1 PR, 34 pushes in 5 months
deep-learningacmrecsysmachine-learning
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