Hang Wu is a machine learning specialist at Perplexity, focusing on LLM post-training and reward hacking. A Ph. D. graduate from Georgia Institute of Technology, his expertise is in reinforcement learning, which he previously applied at scale as a Staff Research Scientist at ByteDance to enhance user personalization systems.
He has a consistent track record of applying machine learning to solve complex problems, from improving video compression speed at Google to enhancing medical image segmentation at Intuitive Surgical.
Unique fact: He describes his career focus on optimizing complex systems with the phrase, "different rewards, same hacking. "
Read the full overview →They are likely to ask many questions and look heavily for supporting information. They can sound friendly and charming but can quickly change gears to become inquisitive and probing. They are generally good communicators and can be hard to convince.
Calculativeness (C) reflects the degree to which a person is likely to be cautious, systematic and analytical. Those scoring high tend to emphasise quality and accuracy.
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