Hanxun Huang
Postdoctoral Research Fellow In Generative AI
Melbourne, Victoria, Australia
Summary
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Rockstar🎓
Top SchoolHanxun Huang is a Postdoctoral Research Fellow in Generative AI at the University of Melbourne with 11 years of experience bridging robust machine learning research and practical teaching. He earned his PhD and MSc from Melbourne after a BS in Computer Science from Purdue, and his recent work sits at the intersection of generative models and AI safety within an ARC Centre of Excellence for Automated Decision-Making and Society. Hanxun has taught a broad range of courses from declarative programming to statistical machine learning, reflecting a talent for translating advanced research into accessible instruction. He focuses on robustness and pattern recognition in ML—bringing a rigorous, safety-aware perspective to generative AI development—and often pairs theoretical work with hands-on implementations.
11 years of coding experience
Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Purdue UniversityThe University of MelbourneBeijing No. 80 High School
English, Chinese
Stackoverflow
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Github Skills (56)
loss-functions10
python10
machine-learning10
numpy10
deep-learning10
gpu10
neural-network10
tensor10
gpu-acceleration10
pytorch9
defense9
autograd9
cross-entropy9
robustness8
bert8
Programming languages (4)
Github contributions (5)
HanxunH/Active-Passive-Losses
Feb 2020 - Jul 2020
[ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels
Contributions:9 commits, 9 pushes, 4 comments in 5 months
deep-learningloss-functionsicml-2020label-noisepytorch
HanxunH/CognitiveDistillation
Jan 2023 - Feb 2023
[ICLR2023] Distilling Cognitive Backdoor Patterns within an Image
Contributions:13 commits, 17 pushes, 1 branch in 11 days
iclr2023pytorchbackdoor-attacksbackdoor-defensedeep-learning
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