Kung-hsiang Huang
Member Of Technical Staff, Amazon AGI SF Lab
Los Angeles, California, United States
Summary
🤩
Rockstar🎓
Top SchoolKung-hsiang Huang is a research-focused software engineer with a decade of experience building and evaluating large-scale AI systems, currently a Member of Technical Staff at Amazon AGI SF Lab. He transitioned from senior research roles at Salesforce AI Research and a PhD at UIUC, where his work spanned LLM/VLM post-training, agent development, environment simulation, reasoning, and alignment across top venues. His background blends deep academic rigor with applied engineering—examples include cryptocurrency price prediction models and production-minded contributions as a startup CTO and co-founder. He is comfortable moving between research papers and reproducible code, having shipped experiments that span CNNs, LSTMs/GRUs, and RL/SFT methods. Based in Los Angeles, he brings a global academic pedigree (HKUST, USC, Georgia Tech exchange) and hands-on product experience that help bridge novel research and deployable systems. A less obvious strength is his track record of rapidly shifting between roles and domains, showing an ability to produce high-impact results in both fast-paced industry labs and academic settings.
10 years of coding experience
10 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 (19)
gru10
python10
machine-learning10
data-preprocessing10
mask-rcnn10
keras10
lstm10
deep-learning10
tensorflow10
faster-rcnn10
evaluation9
bitcoins9
bitcoin9
eval9
cryptocurrency9
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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