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Junzhou Huang
H指数:75
被引数:2.4万
个人简介
Serves as the Dr. David and Cindy Kung Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington. Primary research interests include machine learning, computer vision, medical image analysis, and bioinformatics. Notable achievements include the NSF CAREER Award, Google TensorFlow Model Garden Award, and Microsoft Accelerate Foundation Models Research Award. The scholar won the 1st place in the Contact and Distance Prediction Challenge at CASP14 in December 2020. Research focuses on developing efficient algorithms with theoretical guarantees for large-scale data problems.
教育背景
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工作经历
暂无内容
荣誉奖项
- NSF CAREER Award｜NSF
- Google TensorFlow Model Garden Award｜Google
- Microsoft Accelerate Foundation Models Research Award｜Microsoft
- Best Paper Awards (MICCAI'10, FIMH'11, STMI'12 and MICCAI'15)
- Best Paper Nominations (MICCAI'11 and MICCAI'14)
- 6th place in the 3D Structure Prediction Challenge（2020）
- 1st place in the Contact and Distance Prediction Challenge（2020）｜CASP14
以组织病理学为中心的空间组学的计算演化：整合、映射和基础模型
基于标签消歧的协作式实例级和袋级多实例学习方法用于全切片图像分析
Medical Image Analysis
IF11.8
解析T细胞受体-抗原配对的微小序列差异
Nature Communications
IF15.7
基于文本引导的多实例学习用于通过步态视频分析进行脊柱侧凸筛查
HAGE：基于空间转录组学的层次对齐基因增强病理表示学习
结直肠癌全切片图像的多模态分析
npj Digital Medicine
IF15.1
基于统一弱监督深度学习模型的Pancancer结果预测
通过深度学习分析肿瘤中B细胞库的抗原结合亲和力，可预测免疫检查点抑制剂治疗结局
Nature Cancer
IF28.5
回复: 单细胞基础模型的更深入评估
几何深度学习方法及其在三维结构药物设计中的应用
DRUG DISCOVERY TODAY
IF7.5
用于多中心乳腺组织病理学图像中有丝分裂检测的可推广且鲁棒的深度学习算法
MEDICAL IMAGE ANALYSIS
IF11.8
通过基于相关性的交叉训练合并nucleus数据集
MEDICAL IMAGE ANALYSIS
IF11.8
DeepNoise: 基于深度学习对荧光显微镜图像进行分类的信号和噪声解纠缠
