研究方向
1. 数据挖掘与网络安全 Data Mining and Network Securit
主要研究“知识发现与数据挖掘”,重点面向大数据分析与挖掘技术的挑战和应用需求,研发基于云计算和超级计算的并行数据挖掘算法、系统及平台。开展互联网、智能电网、电信等大数据领域应用,以及网络安全技术创新、人才培养和产业化发展。
Research on knowledge discovery and data mining, focusing on the challenges and application requirements of large data analysis and mining technology, and develops parallel data mining algorithms, systems and platforms based on cloud computing and supercomputing. We will develop applications in such data fields as the Internet, smart grid and telecommunications, as well as technological innovation in network security, personnel training and industrial development.
2. 区块链+人工智能 Blockchain+AI
作为目前最火热、最具吸引力的两大信息技术——区块链与人工智能正在深刻地改变人们工作和生活的方式。区块链与人工智能相融共生、互惠互利,人工智能技术(个体智能)为区块链提供诸如共识算法优化、节点智能负载均衡、风险识别等各项支持;区块链为下一代人工智能(群体智能)提供智能合约、去中心化数据存储与共享、安全认证等关键基础设施。区块链与人工智能的融合发展,将携手拉开“万事互联”智能社会的帷幕。
As the two most popular and attractive information technologies, blockchain and artificial intelligence are profoundly changing the way people work and live. Blockchain and artificial intelligence are mutually beneficial and interrelated. Artificial intelligence technology (Individual Intelligence) provides support for blockchain such as consensus algorithms optimization, node intelligent load balancing, risk identification, etc. Blockchain provides key infrastructure for next generation artificial intelligence(Swarm Intelligence), such as intelligent contract, decentralized data storage and sharing, and security authentication. The integration and development of blockchain and artificial intelligence will open the curtain of "Everything Interconnected" intelligent society.
3. 未来智能网络与移动边缘计算 Future Intelligent Internet and Mobile Edge Computing
随着物联网、自动驾驶、人工智能等应用的快速发展,移动互联网面临着可共享多媒体数据流量爆炸式增长、计算密集与延迟敏感型应用并存所带来的新挑战。内容中心网络(CCN)是一种数据与位置解耦并以内容分发为中心的未来互联网架构,试图解决以主机(IP)为中心的互联网在内容分发、移动性、智能化、安全性等方面面临的挑战。
With the rapid development of applications such as Internet of Things, autonomous driving, and artificial intelligence, the mobile Internet faces new challenges brought about by the explosive growth of shared multimedia data traffic, computation-intensive and delay-sensitive applications. Content-Centric Networking (CCN) is a data and location decoupled content-centric future internet architecture design, trying to solve the challenge of host-centric IP-based Internet in content distribution, mobility, network intelligence, security, etc.
4. 自然语言处理 Natural Language Processing
自然语言处理是人工智能的一个重要分支,旨在完成以自然语言为载体的非结构化信息为对象的各类信息处理任务,拥有广阔的发展前景。主要研究方向包括自然语言理解与推理、信息抽取、智能问答、机器翻译、自动文摘、文本分类、文本生成等。目前已在ACL、SIGIR、AAAI、IJCAI等知名国际期刊和学术会议上发表60余篇学术论文。
Natural language processing (NLP) is an important field in artificial intelligence (AI), which aims to analyze the natural language in both written and spoken forms by applying AI techniques. Under the broad application prospects, the importance of NLP after the breakthrough of the underlying technology is self-evident. Our main research interests include natural language understanding and reasoning, information extraction, question answering, machine translation, text summarization, text classification, text generation. In recent years, we have published more than 60 academic papers on top-tier international journals and academic conferences such as ACL, SIGIR, AAAI, IJCAI, etc.
