Heinrich Jiang

Heinrich Jiang is a machine-learning researcher and the Chief Scientist at StoryGold, a venture-backed startup building foundation models for parametric CAD and 3D reasoning. He studied mathematics at Princeton University (A.B., 2015, summa cum laude) and represented Canada at the 2011 International Mathematical Olympiad, winning a Bronze medal. He joined Google as a software engineer in July 2016 and became a Research Scientist there in January 2018, publishing on AI fairness, classifier trust, clustering and optimization. Before Google he worked as a trader at KCG Holdings, an electronic market-making firm, and held internships reportedly at Jump Trading and Facebook. His research papers include 'To Trust Or Not To Trust A Classifier' and 'Identifying and Correcting Label Bias in Machine Learning'.

Notes5

• Quant employment verification: CONFIRMED - held a full-time Trader role at KCG Holdings, Inc. (2015-06 to 2016-06) and reported internships at Jump Trading, LLC and Facebook. KCG Holdings was an electronic market-making / high-frequency trading firm (merger of Knight Capital and GETCO, acquired by Virtu Financial in 2017), so it qualifies as quantitative finance; Jump Trading is a proprietary HFT firm and qualifies, but its role is listed as an internship, not full-time; Facebook is not a quant-finance employer. Identity is supported as the same Princeton / IMO-2011 Heinrich Jiang who later worked at Google Research. Caveat: the KCG and Jump/Facebook history comes from LinkedIn-derived index/aggregator data, not yet an independent primary page.Sep 2026
• Authored/co-authored widely cited ML papers including 'To Trust Or Not To Trust A Classifier' (arXiv 2018, 700+ citations), 'Identifying and Correcting Label Bias in Machine Learning' (arXiv 2019, 500+ citations), and 'Learning the Truth From Only One Side of the Story' (2020).May 2018
• Google Scholar shows ~3,681 total citations for his work, confirming substantial research impact in ML fairness/clustering.Sep 2026