Design Algorithms for Realistically DifficultBio-medical Problems


主讲人:龚新奇 中国人民大学副教授 博士生导师




主讲人介绍:龚新奇,中国人民大学数学科学研究院数学智能应用课题组长,副教授、博士生导师,中国人民大学数学学院学位委员会委员、师德建设与监督委员会委员,清华大学北京生物学高精尖创新中心合作研究员Co-PI,哈佛大学访问学者,IBM公司访问学者,中国计算机学会高级会员、生物信息学专业委员会员。已发表论文51篇,被引1823次,H指数21,包括Nature/Science/PNAS/Bioinformatics/IEEE-ACM TCBB等期刊。主持科研项目8个,独立负责总经费220万元,包括国家自然科学基金面上项目、国家自然科学基金重点集成项目子课题、国家重点实验室开放课题等。

内容介绍:The intersection among mathematics, information and biology has becoming more interesting and important. Many studies in this direction have led to developments of theories, methods and applications. But the fast advancing of nowadays forefront information technology and biology knowledge, have triggered two obviously emerging phenomena, tremendous brand-new data accessible by new kinds of computations, randomly meaningless results by in-correct intersections. Here I will present some of our recent results in developing and distinguishing efficiently intelligent approaches and applications for computational molecular biology and medical problems, such as protein structure-function-interaction prediction and pancreas cancer CT image analysis using algorithms like Fast Fourier Transform, Monte Carlo, and deep learning, and some new designed physical and geometrical features.

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