Young Scientists

Prof. Bin Guo

Affiliation

Northwestern Polytechnical University

Title

From Crowd Sensing to Crowd Computing—Harnessing the Power of the Crowd

Abstract

Mobile Crowd Sensing (MCS), as a new sensing paradigm that harnesses the power of the crowd, has become a promising research field in recent years. Numerous studies have been done on the research challenges such as optimized worker selection, incentive mechanisms, efficient data transmission, crowd data quality/trust, novel MCS applications, and so on. In this talk, we will discuss about the recent development and future directions of MCS. In particular, we will talk about Crowd Computing, the aggregation and fusion of heterogeneous crowd-contributed data for comprehensive urban sensing. We will report the recent progress of our group towards this promising research area.

Short Bio

Dr. Bin Guo is a professor with Northwestern Polytechnical University, China. He received his Ph.D. degree in computer science from Keio University, Tokyo, Japan, in 2009. His current research interests include Ubiquitous Computing, Mobile Crowd Sensing, and Urban Computing. He has published over 100 papers in refereed journals and conference proceedings such as IEEE Comm. Surveys and Tutorials, ACM Computing Surveys, IEEE TMC, IEEE THMS, IEEE TITS, IEEE Pervasive Computing, UbiComp, PerCom, etc. He has served as an associate editor of IEEE Communications Magazine, IEEE Trans. on Human-Machine-Systems, ACM IMWUT, IEEE IT Professional, and so on. He is the program chair of IEEE CPSCom’16 and UIC’13, the general co-chair of UIC’15 (CCF-ranked conference) and IEEE IoP’17. He has also served as TPC member for a number of CCF-ranked conferences, such as UbiComp, PerCom, GlobeCom, WWW, HyperText, ICC, etc. He is a senior member of IEEE and CCF. He received the support from the National Youth Talent Support Program (Ten Thousand People Plan) in 2016.

 
Dr. Yuanyi Chen

Affiliation

Zhejiang University City College

Title

Towards Truly Ubiquitous Indoor Localization via Multi-modal sensing and Crowdsourcing

Abstract

Indoor localization can facilitate numerous location-based services (e.g., indoor navigation, indoor POI recommendation and mobile advertising) in the era of mobile computing, attracting extensive research effort over recent decades. Despite more than a decade of research, indoor localization systems are not yet pervasive indoors as they are tailored to specific deployments. In this talk, I will discuss about the recent development and future directions of ubiquitous indoor localization, such as automatic indoor floorplan construction via multi-modal sensing on smartphones and signature map construction leveraging crowd-sourcing.

Short Bio

Dr. Yuanyi Chen is a distinguished research fellow with Zhejiang University City College, China. He received his Ph.D. degree in computer science from Shanghai Jiao Tong University, China, in 2017. From September 2014 to September 2015, he was a jointly-supervised PhD candidate at Hong Kong Polytechnic University. His research interests are in the field of Internet of Things with emphasis on modeling the cyber-physical objects and their contextual relationships, designing a framework including system architecture and major functional components with networking and computing mechanisms, algorithms, and middleware support, for finding, storing and searching the information about IoT objects. He’s published some papers in refereed journals and conference proceedings in these areas, such as IEEE Trans. on Service Computing, Science China Information Sciences, Personal and Ubiquitous Computing, PerCom and UIC (Best Paper Awards).

 
 
Dr. Yong Li

Affiliation

Tsinghua University

Title

Cross-domain Mobile Users’ Behavior Modelling and Prediction

Abstract

By focusing on characterizing the mobile traffic, web and information usage traces based on large-scale and long-duration mobile big data, which is collected from the commercial mobile operator with more than 10 thousand base stations and 6.5 million users spanning over some months, we qualitatively visualize and quantitatively characterize the spatio-temporal human behaviors in the physical-cyber space in terms of mobility, traffic consumption, social activity, etc. Based on these fundamental findings and credible models, we further investigate how to utilize these important insights to deal with problems encountered with the current mobile networks, urban management, and robust cyber-physical systems.

Short Bio

Dr. Yong Li is the Associate Professor of the Department of Electronic Engineering, Tsinghua University. He received the B.S. degree from Huazhong University of Science and Technology in 2007, and the M.S. and the Ph.D. degrees in Electrical Engineering from Tsinghua University, in 2009 and 2012, respectively. During 2012 and 2013, he was a Visiting Research Associate with Telekom Innovation Laboratories and Hong Kong University of Science and Technology respectively. During 2013 to 2014, he was a Visiting Scientist with the University of Miami.

Dr. Li has served as General Chair, TPC Chair, TPC Member for several international workshops and conferences, and he is on the editorial board of four IEEE/ACM journals. His papers have total citations more than 4000. Among them, ten are ESI Highly Cited Papers in Computer Science, and four receive conference Best Paper (run-up) Awards. He received IEEE 2016 ComSoc Asia-Pacific Outstanding Young Researchers and Young Talent Program of China Association for Science and Technology.

 
Prof. Weili Han

Affiliation

Fudan University

Title

数据驱动的用户口令恢复理论模型研究

Abstract

口令恢复理论模型研究是当前信息安全领域的热点研究方向。鉴于用户口令通常关联了重要文件或核心账户的访问权限,因而对于网络犯罪调查取证等实际业务而言,能够快速恢复被严密保护的口令具有十分重要的应用价值。此外,口令恢复理论模型的研究也进一步推动了口令保护技术的不断完善,最为典型的应用就是在用户生成口令阶段的强度度量方法及工具。韩伟力博士将介绍当前利用数据驱动优化用户口令恢复的几种方法,对比各自方法的优缺点,给出韩伟力博士带领的研究小组在这些方面做出一些前沿工作,并展望当前互联网用户身份认证方法的一些挑战以及可能的应对思路。

Short Bio

韩伟力教授,博导,软件学院副院长,中国计算机学会杰出会员,中国电子学会信息安全专家委员会副主任委员,上海计算机学会信息安全专委会秘书。研究方向:数据系统安全、访问控制、大数据试验场。近几年在USENIX Security, ACM SACMAT, ASIACCS, IEEE TDSC, IEEE TIFS, IEEE TPDS, Computers & Security等权威会议期刊发表系列学术论文,承办访问控制领域旗舰会议ACM SACMAT 2016。现为《International Journal of Communication Systems》(SCI期刊)、《网络与信息安全学报》、《信息安全学报》编委成员。

 
Dr. Ling Chen

Affiliation

Zhejiang University

Title

Mobile and Wearable Device-based User Context Recognition

Abstract

Mobile and wearable device-based user context recognition is one of the most significant and valuable issues of pervasive computing. Recognizing user context (e.g., activities and places) can facilitate numerous user-centric applications, e.g., healthcare, skills assessment, industrial assistant, and location-based services. In this talk, I will discuss about the recent development and future directions of user context recognition. In particular, I will talk about human activity recognition and semantic place recognition, e.g., classifier ensemble based multimodal activity recognition and cost-sensitive semi-supervised personalized semantic place label recognition.

Short Bio

Dr. Ling Chen is an associate professor in the College of Computer Science and Technology, Zhejiang University. He received the B.S. and the Ph.D. degrees from Zhejiang University in 1999 and 2004, respectively. From January 2006 to July 2007, he performed postdoctoral research in the University of Nottingham, UK. His current research interests include ubiquitous computing, human activity recognition, location-aware computing, database, etc. He published more than 70 academic papers in journals and conferences such as TMC, TCYB, TMM, TITS, TBME, PR, UbiComp, AAAI, MM, PerCom, etc. He has served as the chairman of conferences, e.g., GPC, NCM, and DMAMH. He has also served as the TPC member of conferences, e.g., ACCV, CASA, NetGames, CUTE, and CCF Bigdata. He is a member of CCF Pervasive Computing Committee.

 
Wei Cao

Affiliation

Alibaba

Title

POLARDB: The Next Generation Cloud-Native Relational Database

Abstract

POLARDB is a cloud-native database service of shared storage architecture, decoupling storage from compute to let each half be scalable independently. POLARDB is 6 times faster than the public MySQL releases because the critical path inside database kernel is optimized significantly based on state of art NVM storage and RDMA network techniques, the capacity of POLARDB can be extended to as large as 100 TB since the storage layer can be scaled out and replicated to a cluster of machines with extremely high IO throughput, and the cost of POLARDB is far more lower than traditional database mirroring solutions since multiple POLARDB replicas can share the same data file copy on the shared storage.

Short Bio

Wei Cao is a Senior Staff Engineer in Alibaba. He is the head of Alibaba Cloud Database Department. He obtained his Bachelor from Peking University in 2006, and Master from Peking University in 2009.He is a member of China Computer Federation Technical Committee on Databases. He published some papers about cloud databases in refereed journals and conference proceedings such as VLDB, SIGMOD and TSC.

 
Dr. Lan Zhang

Affiliation

University of Science and Technology of China

Title

跨域大数据的理解、保护和交易

Abstract

物联网的飞速发展,带来了各类型数据的爆炸性增长,对跨域感知及计算技术提出了巨大需求和挑战。来自不同数据域、应用域、物理域和管理域的数据蕴含了丰富的信息,若充分利用将带来难以估量的价值,然而这些数据也包含大量隐私,对数据价值和隐私的考虑严重阻碍了不同应用域和管理域之间的开放共享。要实现有效、安全、可信的跨域感知和计算,亟需对跨域感知数据的深度融合理解和安全隐私保护的理论和技术,以及建立在理解和保护基础上的可信开放共享机制,这三者相互支撑,需多管齐下。深入理解、开放共享与隐私保护之间的内在的矛盾进一步增大了这一课题的挑战。

Short Bio

张兰,中国科学技术大学计算机学院特任研究员。2007年毕业于清华大学软件学院,获学士学位。2014年毕业于清华大学计算机科学与技术系,获博士学位。2014年-2016年于清华大学软件学院做博士后。2016年到中国科学技术大学计算机学院担任特任研究员。2015获得 CCF优秀博士学位论文奖(全国共10人)和ACM中国优秀博士论文奖(全国共2人)。主要从事隐私保护,移动计算和大数据相关研究工作,在相关领域的国际知名会议期刊发表论文37篇,(其中第一作者论文17篇,通讯作者论文9篇),包括4篇ACM MobiCom,以及多篇UbiComp, IEEE INFOCOM,IEEE TMC,IEEE TPDS等。申请美国发明专利3项,中国发明专利20余项。担任IEEE INFCOM 2019, IEEE INFCOM 2018,IEEE MASS 2018, IEEE ICC 2017, IEEE MASS 2017, MSN 2016, IEEE IPCCC 2016, IEEE DCOSS 2015等会议的程序委员会成员。