Zhuji 诸暨 - Beijing 北京 - Heidelberg 海德堡 - New York 纽约 - San Francisco 旧金山
Xinghua Lou, Ph.D. 楼兴华,博士
Xinghua Lou, Ph.D., is Head of Commercialization at Vicarious AI responsible for strategic planning and customer development. Previously Xinghua is a veteran machine learning researcher and practitioner. He has published in many top-tier venues such as Science, NIPS, ICML, CVPR, MIT Press, and has won the best paper award in 2012 Machine Learning for Medical Imaging. Xinghua received his Ph.D. from Universität Heidelberg (Heidelberg, Germany) and M.Sc./B.Sc. from Tsinghua University (Beijing, China). Xinghua's current interest is applications of artificial intelligence in industrial robotics and other areas of industrial automation.
楼兴华,毕业于德国海德堡大学(博士)和北京清华大学(本硕)。目前担任硅谷人工智能创业公司Vicarious AI的商业化总监,负责公司的战略规划和客户拓展。之前耕耘于机器学习和图像处理领域,进行核心算法创新和应用,专注于小数据学习和结构化数据预测,在国际顶级会议中发表众多论文(包括Science《科学》、NIPS、ICML、CVPR、MIT Press等),曾经获得2012年Machine Learning for Medical Imaging会议最佳论文。目前主要关注领域是人工智能在工业机器人和其他工业自动化领域中的应用。
Field 领域
Artificial Intelligence & Big Data Analytics 人工智能与大数据分析
Expertise 专长
Model and Algorithm R&D 模型与算法研发 Technology Transfer & Deployment 技术转换与部署 Market Research & Strategic Planning 市场研究与战略计划
Publications 论文发表
More than 30 papers in top-tier venues: NIPS, ICML, CVPR, MIT Press, Bioinformatics, IEEE-TMI, etc. 超过30篇论文,包括顶级会议和杂志:NIPS、ICML、CVPR、IEEE-TMI、MIT Press、Bioinformatics等等。
D George, W Lehrach, K Kansky, M Lázaro-Gredilla, CC Laan, B Marthi, X Lou, et al. "A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs." Science 358, no. 6368 (2017).
K Kansky, T Silver, DA Mély, M Eldawy, M Lázaro-Gredilla, X Lou, et al. "Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics.", In ICML (2017).
X Lou, K Kansky, W Lehrach, CC Laan, B Marthi, D Phoenix, and D George. "Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data." In NIPS (2016).
D Chakraborty, M Malik, Q Ke, M Rosenberg, X Lou. "Query transformation for natural language queries", US20170075985A1 (2015)
X Lou, M Kloft, G Raetsch, FA Hamprecht. "Chapter 12: Structured Learning from Cheap Data.", In Advanced Structured Prediction (2014).
X Lou, M Kang, P Xenopoulos, S Munoz-Descalzo, and A-K Hadjantonakis. "A rapid and efficient 2D/3D nuclear segmentation method for analysis of early mouse embryo and stem cell image data." Stem Cell Reports, 2, no. 3 (2014): 382-397.
X Lou, M Schiegg, FA Hamprecht. "Active structured learning for cell tracking: algorithm, framework, and usability.", IEEE Transactions on Medical Imaging, 33 (4), 849-860 (2014).
X Lou, FA Hamprecht. "Structured learning from partial annotations.", In ICML (2012).
X Lou, FA Hamprecht. "Learning to segment dense cell nuclei with shape prior.", In CVPR (2012).
X Lou, FA Hamprecht. "Structured Learning for Cell Tracking.", In NIPS (2011).
X. Lou, M Kirchner, B Renard, et al. "Deuteration distribution estimation with improved sequence coverage for HX/MS experiments.", Bioinformatics, 26(12), pp.1535-1541 (2010).
X Lou, S Liu, H Su, HC Young. "Method, interaction method and apparatus for visualizing hierarchy data with angular chart.", US Patent App. 12/044,232 (2008).