Research / 研究

The research of our lab focuses on Operations Research and Information Science. We are particularly interested in the mathematical modeling and algorithm design in the field of optimization and decision, logistics and financial technologies, bioinformatics and computational biology.
我们实验室的主要研究方向为运筹学与信息科学,特别的我们关注优化与决策、物流与金融科技、生物信息学与计算生物学等相关领域中的数学建模与算法设计。

Currently, we focus on the following topics:
目前我们的研究内容包括:

Blockchain technology / 区块链技术

Blockchain is an open, distributed ledger technology that can record transactions efficiently and in a trackable, verifiable and permanent way, and has wide applications in many fields such as financial industry and agriculture. We aim to develop novel mathematical models and algorithms for improving the efficiency and performance of blockchain.
区块链是一种开放的分布式账本数据库技术,具有去中心化、追踪溯源、公开透明、防篡改伪造等特性,在金融业、农业等多个领域有着广泛的应用前景。 我们致力于发展新的数学模型与算法以提高区块链的效率与性能。

Logistics and supply chain management / 物流与供应链管理

Logistics and supply chain management is one of the major research areas in operations research. In China, the application of operations research methods in real industry is lagging behind the theoretical studies. We are particularly interested in the real problem emerged in the industry. We aim to promote the application of operations research methods and improve the efficiency of the logistics and supply chain management in China by cooperating with the logistics company such as COSCO Shipping and JD Logistics.
物流与供应链管理是运筹学的一个主要研究领域。在中国,运筹学方法在业界的应用远远落后于理论研究。我们特别关注来自于业界的实际问题,通过与一些主要物流公司如中远、京东物流等合作,致力于推动运筹学方法的实际应用和提升物流行业的效率。

Network comparison / 网络比较

There are many networks in the real world including a large amount of biological networks generated by high-throughput experimental techniques. It is important to analyze the similarity and dissimilarity between two or more networks. We aim to develop efficient computational methods for network comparison, including network querying, pairwise network alignment, and multiple network alignment.
现实世界中存在着各种网络,例如高通量生物实验技术产生了大量的生物分子网络。分析两个或者多个网络的相似性和差异性具有非常重要的理论意义和应用价值。我们致力于发展高效的计算方法用于处理各种类型的网络比较,包括网络查询、网络比对、多网络比对等。

Biomarker identification / 生物标记物识别

Biomarker play an important role in the clinical diagnosis and therapy and the basic scientific research of complex diseases. We aim to develop the computational models and high performance algorithms for the biomarker identification in heterogeneous complex diseases.
生物标记物在临床诊断医疗和基础医学研究中都具有非常重要的作用。我们致力于发展新的计算模型和高性能算法,解决高异质性复杂疾病数据中的生物标记物识别问题。