Sen Zhang is a machine learning engineer and CS PhD from the University of Sydney with nine years of experience bridging computer vision, SLAM, bioinformatics, and foundation-model alignment. His academic work produced ECCV, ICRA and IJCV publications on learning-based visual odometry and information-theoretic SLAM, while his postdoc and industry roles shifted to RLHF and aligning large language and diffusion models to human values. At TikTok and during a remote AGI startup engagement he built RLHF backbones and novel algorithms addressing reward hacking, overoptimization, and AI self-training for real-world robustness. He combines strong theory (information bottleneck, high-dimensional statistics) with hands-on systems skills (C++, Python, PyTorch) and a track record of deploying research into production settings. Unusually, his background spans medical imaging, genetic interaction testing and robotics, giving him a rare cross-domain lens for practical AI problems. He is based in Sydney and focused on AI methods that deliver measurable real-world impact.
9 years of coding experience
2 years of employment as a software developer
The University of Sydney
Bachelor's degree, Biomedical Engineering, Bachelor's degree, Biomedical Engineering at Tsinghua University
Hong Kong University of Science and Technology (HKUST)
Contributions:2 commits, 1 push, 1 branch in 7 months
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