Xiang Lian  (PhD, HKUST, 2009)

Associate Professor


Department of Computer Science


Kent State University


Office:   Room 264


              Mathematics and Computer Science Building (MSB)


              1300 Lefton Esplanade


              Kent, OH 44242-0001, USA


Phone:  (+1) 330-672-9063


Email: xlian@kent.edu


[Publications ( DBLP, Full List )] [Curriculum Vitae]


[Biography] [Research Interests] [Teaching] [Publications] [Professional Services] [Grants and Awards] [Group Members] [Projects] [Links]

Biography  


I obtained my Bachelor's degree from the Department of Computer Science and Technology , Nanjing University in June 2003. I obtained my PhD degree at the Department of Computer Science and Engineering, Hong Kong University of Science and Technology [HKUST], under the supervision of Dr. Lei Chen , in August, 2009. After that, I worked as a post-doctoral fellow at the Department of Computer Science and Engineering, Hong Kong University of Science and Technology [HKUST]. In 2010-2011, I was also a research assistant professor at the HKUST Fok Ying Tung Graduate School. In 2011-2016, I worked as an assistant professor at the Department of Computer Science, University of Texas Rio Grande Valley [UTRGV, Edinburg Campus] (former name: University of Texas - Pan American [UTPA]). In 2016-2021, I worked as an assistant professor at the Department of Computer Science, Kent State University [KSU]. Starting from September 2021, I am an associate professor at the Department of Computer Science, Kent State University [KSU].

I am directing the Big Data Science Lab [MSB 253, phone: (+1) 330-672-9123], Department of Computer Science, Kent State University.

Here are links to some of my professional websites: [DBLP], [Google Scholar], [LinkedIn View Xiang Lian's profile on LinkedIn], [ACM Author Profile], [ResearchGate], [Semantic Scholar], [Scopus], [Web of Science™], and [ORCID iD iconORCID].

My Curriculum Vitae is here , and my homepage is here .

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Research Interests


My main research interest is in databases. In particular, I am interested in query processing over:

  • Probabilistic, Inconsistent, and Uncertain Databases
    • In real applications such as location-based services (LBS), RFID/sensor networks, data extraction/integration, and medical data analysis, the underlying data are inherently imprecise and uncertain, due to various reasons such as imperfect nature of sensing devices, inaccuracy of information extraction methods, unreliability of data sources, and/or privacy preserving. Therefore, these application data can be modeled by probabilistic and uncertain data. Compared with certain data, uncertain data are those tuples/objects associated with probabilistic confidences that are either independent or with arbitrary correlations. Moreover, in some applications such as data extraction/integration, the extracted/integrated (probabilistic) data may violate some integrity constraints (e.g., functional dependencies) and thus be inconsistent. Due to the data uncertainty and inconsistency, it is challenging to efficiently and accurately organize and answer various probabilistic queries over such probabilistic/inconsistent/uncertain data.

  • Uncertain and Certain Graph Databases
    • Uncertain and certain graph databases have been widely used in many real applications such as the Semantic Web (e.g., workflows and XML/RDF graphs), social networks, scientific databases (e.g., chemical compound databases, biological graphs like protein-to-protein interaction networks and gene regulatory networks, etc.), and transportation systems (e.g., road networks). There are many interesting research topics on efficient query answering in uncertain/certain graph databases, such as keyword search queries over (probabilistic) RDF graphs, route planning over road networks with uncertain traffic conditions, and variants of subgraph matching over (probabilistic) RDF graphs, biological graphs, or social networks. While the manipulation over complex graph structures itself is quite costly, the query processing over probabilistic graphs is more challenging (since more constraints such as labels (keywords), probabilities, and correlations are involved).

  • Streaming Time Series
    • The streaming time series have many real applications such as financial stock data analysis, sensory data analysis, trajectory data analysis, multimedia (audio or video) databases, and so on. In this direction, it is interesting to study the efficient and accurate detection/prediction of critical events (corresponding to some query patterns), such as the falling/rising of stocks, fire events, or behaviors of mobile users' trajectories, over streaming time-series.

  • Spatio-Temporal Databases
    • The spatio-temporal databases have real-world applications such as geographical information systems (GIS), multimedia databases, and location-based services (LBS). It is quite important and useful to study various spatial queries (such as range queries, k-nearest neighbor queries, and reverse k-nearest neighbor queries over static/moving spatial objects) in different scenarios such as high-dimensional spaces, subspaces, metric spaces, and data streams. In order to tackle these problems, it is challenging to design effective pruning methods specific for spatial query types to reduce the query search space, and propose the optimized indexing and query processing approaches to efficiently retrieve spatial query answers.

  • Spatial Crowdsourcing
    • A spatial crowdsourcing platform provides an opportunity for users (task requesters) to utilize the power of humans to acomplish some complex or time-consuming spatial tasks (e.g., checking whether a supermarket has a specific product, or whether or not a restaurant far away from a user is open). Existing spatial crowdsourcing systems include Waze, Gigwalk, TaskRabbit, gMission, and so on. Given a number of workers and a number of spatial tasks, a typical spatial crowdsourcing problem is to assign moving workers to do spatial tasks so that some constraints (e.g., task deadlines, maximum budget, task quality, etc.) are satisfied or some criteria are optimized (e.g., the total budget is minimized, or the number of completed tasks is maximized). The task assignments in the spatial crowdsourcing problem can be considered as an optimization problem, which is usually NP-hard and intractable. Therefore, it is challenging to design approximation, near-optimal algorithms to efficiently assign workers with spatial tasks with good quality.

  • Incomplete Data Management
    • In many real applications like sensor data monitoring, intrusion detection in IP networks, social networks, Web data analysis, and so on, the collected/extracted data often contain missing attributes, due to various reasons such as network traffic congestions, hardware/network failures, incomplete profiles not entered by users, or the inaccuracy of the data extraction. While existing data analysis tools often assume that the underlying data are complete, they usually cannot effectively and accurately handle incomplete data. Therefore, incomplete data management is rather important and useful in practice. Interesting research problems include the design of accurate data imputation techniques, and efficient data processing algorithms to perform online data imputation and query processing at the same time.

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Teaching   [Full Course List, Academic Calendar]

  Instructor for:

    Spring 2023:

  • CS 69099, Capstone Project – Data Science, F, 9:55am ~ 11:50am.
    Location: Henderson Hall, Room 108
    (Virtual) office hour: By Email Appointment Only (preferably 10:00am - 12:00pm, MW; xlian@kent.edu).
    TA: TBD

  • CS 89098, Research.
    (Virtual) office hour: By Appointment.

  • CS 89299, Dissertation II.
    (Virtual) office hour: By Appointment.

    Fall 2022:

  • CS 63015 & CS 73015, Data Mining Techniques (Online).
    Location: Canvas; https://canvas.kent.edu/.

  • CS 63018 & CS 73018, Probabilistic Data Management, MW, 2:15pm ~ 3:30pm.
    Location: Smith Hall (SMH), Room 111.

  • CS 89299, Dissertation II.
  Course Archives ...

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Selected Publications  [Full Publication List (By Year), DBLP, Google Scholar]

   Book and Book Chapter:
     More ...

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   Probabilistic and Uncertain Databases:
  • Xiang Lian and Lei Chen. Reverse Skyline Search in Uncertain Databases. In ACM Transactions on Database Systems (TODS), 35(1), 2010.
  • Xiang Lian and Lei Chen. Shooting Top-k Stars in Uncertain Databases. In Very Large Data Bases Journal (VLDBJ), 20(6), pages 819-840, 2011.
  • Xiang Lian and Lei Chen. Probabilistic Inverse Ranking Queries in Uncertain Databases. In Very Large Data Bases Journal (VLDBJ), 20(1), pages 107-127, 2011.
  • Xiang Lian and Lei Chen. Efficient Processing of Probabilistic Reverse Nearest Neighbor Queries over Uncertain Data. In Very Large Data Bases Journal (VLDBJ), 18(3), pages 787-808, 2009. [Google Scholar Citations: 117]
  • Xiang Lian and Lei Chen. Similarity Join Processing on Uncertain Data Streams. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 23(11), pages 1718-1734, 2011.
  • Xiang Lian, Lei Chen, and Shaoxu Song. Consistent Query Answers in Inconsistent Probabilistic Databases. In Proceedings of the ACM Conference on the Management of Data (SIGMOD'10), pages 303-314, Indianapolis, Indiana, USA, Jun. 6-11, 2010.
  • Xiang Lian and Lei Chen. Monochromatic and Bichromatic Reverse Skyline Search over Uncertain Databases. In Proceedings of the ACM Conference on the Management of Data (SIGMOD'08), pages 213-226, Vancouver, Canada, Jun. 9-12, 2008. [Google Scholar Citations: 285]
  • Xiang Lian and Lei Chen. Set Similarity Join on Probabilistic Data. In Proceedings of the Very Large Data Bases Conference (PVLDB'10), 3(1), pages 650-659, Singapore, Sept. 13-17, 2010.
  • Xiang Lian and Lei Chen. A Generic Framework for Handling Uncertain Data with Local Correlations. In Proceedings of the Very Large Data Bases Conference (PVLDB'10), 4(1), pages 12-21, 2010.
  • Xiang Lian and Lei Chen. Probabilistic Inverse Ranking Queries over Uncertain Data (Best Paper Award). In Proceedings of the International Conference on Database Systems for Advanced Applications (DASFAA'09), pages 35-50, Brisbane, Australia, Apr. 21-23, 2009.
  • Xiang Lian and Lei Chen. Efficient Pattern Matching over Uncertain Data Streams (The HKIE Outstanding Paper Award). In the HKIE Transactions, Hong Kong Institution of Engineers (HKIE), 16(4), pages 9-18, Hong Kong, China, 2009.
  • Xiang Lian and Lei Chen. Efficient Processing of Probabilistic Group Subspace Skyline Queries in Uncertain Databases. In Information Systems (IS), 38(3), pages 265-285, 2013.
  • Xiang Lian and Lei Chen. Probabilistic Top-k Dominating Queries in Uncertain Databases. In Information Sciences (ISCI), 226, pages 23-46, 2013.
  • Xiang Lian and Lei Chen. Probabilistic Ranked Queries in Uncertain Databases . In Proceedings of the International Conference on Extending Database Technology (EDBT'08), pages 511-522, Nantes, France, Mar. 25-30, 2008. [Google Scholar Citations: 113]
  • Xiang Lian and Lei Chen. Causality and Responsibility: Probabilistic Queries Revisited in Uncertain Databases. In Proceedings of the ACM Conference on Information and Knowledge Management, (CIKM'13), pages 349-358, San Francisco, CA, USA, Oct. 27 - Nov. 1, 2013.
     More ...

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   Uncertain and Certain Graph Databases:
  • [New!] Ye Yuan, Xiang Lian, Lei Chen, Guoren Wang, Jeffrey Xu Yu, Yishu Wang, and Yuliang Ma. GCache: Neighborhood-Guided Graph Caching in a Distributed Environment. In IEEE Transactions on Parallel and Distributed Systems (TPDS), doi: 10.1109/TPDS.2019.2915300, 2019.
  • [New!] Ye Yuan, Xiang Lian, Guoren Wang, Yuliang Ma, and Yishu Wang. Constrained Shortest Path Query in a Large Time Dependent Graph. In Proceedings of the Very Large Data Bases Conference (PVLDB'19), Los Angeles, California, USA, August 26-30, 2019.
  • Xiang Lian and Dongchul Kim. Efficient Ad-Hoc Graph Inference and Matching in Biological Databases. In Proceedings of the ACM Conference on the Management of Data (SIGMOD'17), pages 359-373, Chicago, Illinois, USA, May 14 - 19, 2017.
  • Ye Yuan, Xiang Lian, Lei Chen, Jeffrey Xu Yu, Guoren Wang, and Yongjiao Sun. Keyword Search over Distributed Graphs with Compressed Signature. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 29(6), pages 1212-1225, 2017.
  • Xiang Lian, Lei Chen, and Guoren Wang. Quality-Aware Subgraph Matching Over Inconsistent Probabilistic Graph Databases. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(6), pages 1560 - 1574, 2016.
  • Weiguo Zheng, Xiang Lian, Lei Zou, Liang Hong, and Dongyan Zhao. Online Subgraph Skyline Analysis Over Knowledge Graphs. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(7), pages 1805 - 1819, 2016.
  • Ye Yuan, Xiang Lian, Lei Chen, Yongjiao Sun, and Guoren Wang. RSkNN: kNN Search on Road Networks by Incorporating Social Influence. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(6), pages 1575 - 1588, 2016.
  • Xiang Lian, Lei Chen, and Zi Huang. Keyword Search Over Probabilistic RDF Graphs. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(5), pages 1246 - 1260, 2015.
  • Liang Hong, Lei Zou, Xiang Lian, and Philip S. Yu. Subgraph Matching with Set Similarity in a Large Graph Database. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(9), pages 2507-2521, 2015.
  • Weiguo Zheng, Lei Zou, Xiang Lian, Dong Wang, and Dongyan Zhao. Efficient Graph Similarity Search Over Large Graph Databases. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(4), pages 964-978, 2015.
  • Xiang Lian and Lei Chen. Trip Planner Over Probabilistic Time-Dependent Road Networks. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 26(8), pages 2058-2071, 2014.
  • Xiang Lian and Lei Chen. Efficient Query Answering in Probabilistic RDF Graphs. In Proceedings of the ACM Conference on the Management of Data (SIGMOD'11), pages 157-168, Athens, Greece, Jun. 12-16, 2011.
  • Xiaochen Zhu, Shaoxu Song, Xiang Lian, Jianmin Wang, and Lei Zou. Matching Heterogeneous Event Data. In Proceedings of the ACM Conference on the Management of Data (SIGMOD'14), pages 1211-1222, Snowbird, Utah, USA, Jun. 22-27, 2014.
  • Weiguo Zheng, Lei Zou, Xiang Lian, Jeffrey Xu Yu, Shaoxu Song, and Dongyan Zhao. How to Build Templates for RDF Question/Answering - An Uncertain Graph Similarity Join Approach. In Proceedings of the ACM Conference on the Management of Data (SIGMOD'15), pages 1809-1824, Melbourne, VIC, Australia, May 31 - Jun. 4, 2015.
     More ...

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   Spatio-Temporal Databases:
  • [New!] Weilong Ren, Xiang Lian, and Kambiz Ghazinour. Skyline Queries Over Incomplete Data Streams. In Very Large Data Bases Journal (VLDBJ), 2019.
  • [New!] Peng Cheng, Xiang Lian, Xun Jian, and Lei Chen. FROG: A Fast and Reliable Crowdsourcing Framework. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 31(5), pages 894-908, 2019.
  • Peng Cheng, Xiang Lian, Lei Chen, and Cyrus Shahabi. Prediction-Based Task Assignment on Spatial Crowdsourcing. In Proceedings of the International Conference on Data Engineering (ICDE'17), pages 997-1008, San Diego, California, USA, April 19 - 22, 2017.
  • Peng Cheng, Xiang Lian, Lei Chen, Jinsong Han, and Jizhong Zhao. Task Assignment on Multi-Skill Oriented Spatial Crowdsourcing. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(8), pages 2201-2215, 2016. [Technical Report]
  • Peng Cheng, Xiang Lian, Zhao Chen, Lei Chen, Jinsong Han, and Jizhong Zhao. Reliable Diversity-Based Spatial Crowdsourcing by Moving Workers. In Proceedings of the Very Large Data Bases Conference (PVLDB'15), 8(10), pages 1022-1033, Kohala, Hawai'i, USA, Aug. 31 - Sept. 4, 2015. [Technical Report] [3D Reconstruction Showcase Video]
  • Xiang Lian and Lei Chen. Subspace Similarity Search under Lp-Norm. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 24(2), pages 365-382, 2012.
  • Ke Yi, Xiang Lian, Feifei Li, and Lei Chen. The World in a Nutshell: Concise Range Queries. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 23(1), pages 139-154, 2011.
  • Yufei Tao, Dimitris Papadias, Xiang Lian, and Xiaokui Xiao. Multidimensional Reverse kNN Search . In Very Large Data Bases Journal (VLDBJ), 16(3), pages 293-316, 2007, invited submission from best of VLDB 2004. [Google Scholar Citations: 113]
  • Yufei Tao, Dimitris Papadias, and Xiang Lian. Reverse kNN Search in Arbitrary Dimensionality . In Proceedings of the Very Large Data Bases Conference (VLDB'04), pages 744-755, Toronto, Canada, Aug. 30-Sept. 3, 2004. [Google Scholar Citations: 389]
     More ...

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   Time-Series Databases:
  • Xiang Lian and Lei Chen. Efficient Similarity Join over Multiple Stream Time Series. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 21(11), pages 1544-1558, 2009.
  • Xiang Lian, Lei Chen, Jeffrey Xu Yu, Jinsong Han, and Jian Ma. Multi-Scale Representations for Fast Pattern Matching in Stream Time Series. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 21(4), pages 568-581, 2009.
  • Xiang Lian and Lei Chen. Efficient Similarity Search over Future Stream Time Series. In IEEE Transactions on Knowledge and Data Engineering (TKDE), 20(1), pages 40-54, 2008.
  • Qiuxia Chen, Lei Chen, Xiang Lian, Yunhao Liu, and Jeffrey Xu Yu. Indexable PLA for Efficient Similarity Search. In Proceedings of the Very Large Data Bases Conference (VLDB'07), pages 435-446, Vienna, Austria, Sept. 23-27, 2007. [Google Scholar Citations: 191]
  More publications (by year) ...

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Professional Services  [Full Service List]

  Chair and co-chair for:
  • Proceedings of the Very Large Data Bases Conference (PVLDB), Session Chair [2020];
  • International Conference on Data Engineering (ICDE), Session Chair [2017];
  • The Asia Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data (APWeb-WAIM), Proceedings Co-Chair [2017].
  • International Conference on Database Systems for Advanced Applications (DASFAA), Publicity Co-Chair [2017];
  • ACM Conference on the Management of Data (SIGMOD), Proceedings Co-Chair [2014, 2015]; and
  • International Conference on Web-Age Information Management (WAIM), Proceedings Co-Chair [2016].
     More ...

  Research grant/book proposal reviewer for:
  • National Science Foundation (NSF), Panelist [2017, 2019];
  • Swiss National Science Foundation (SNSF), Reviewer [2020];
  • Research Grants Council of Hong Kong (HK RGC), Reviewer [2017, 2018, 2019, 2020];
  • CRC Press, Book Proposal Reviewer [2020];
  • Wiley, Book Proposal Reviewer [2019];
  • Chilean National Science and Technology Commission (CONICYT), Chile, Reviewer [2015];
  • STW / Enabling new technology, Technology Foundation STW, Netherlands [2014];
  • IEEE Collabratec™, IEEE Platform Testing, IEEE [2014].
     More ...

  Journal reviewer for:
  • ACM Transactions on Database Systems (TODS) [2016, 2018, 2019, 2020];
  • Very Large Data Bases Journal (VLDBJ) [2010, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019];
  • IEEE Transactions on Knowledge and Data Engineering (TKDE) [2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020];
  • ACM Transactions on the Web (TWEB) [2009];
  • Information Systems (IS) [2013, 2018, 2019];
  • Knowledge and Information Systems (KAIS) [2012, 2013, 2018];
  • Information Sciences (INS) [2013, 2014, 2015, 2017, 2018, 2019, 2020];
  • Data and Knowledge Engineering Journal (DKE) [2012, 2013, 2018, 2019];
  • World Wide Web Journal (WWWJ) [2011, 2013, 2016, 2017, 2018];
  • Journal of Computer Science and Technology (JCST) [2012, 2013, 2015, 2016, 2018];
  • Distributed and Parallel Databases (DAPD) [2012, 2013, 2014, 2015, 2017];
  • International Journal on Advances of Computer Science for Geographic Information Systems (Geoinformatica) [2015];
  • Transactions on Knowledge Discovery from Data (TKDD) [2013, 2014];
  • Data Mining and Knowledge Discovery (DAMI) [2016, 2017, 2018];
  • ACM Transactions on Intelligent Systems and Technology (ACM TIST) [2020];
  • Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics (SMCB) [2012];
  • ACM Transactions on Interactive Intelligent Systems (ACM TiiS) [2013];
  • International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS) [2014, 2015, 2016, 2017];
  • International Journal of Cooperative Information Systems (IJCIS) [2015];
  • Frontiers of Computer Science (FCS) [2011, 2014, 2017, 2018, 2019];
  • Transactions on Fuzzy Systems (TFS) [2015, 2016, 2017, 2018, 2019, 2020];
  • IEEE Transactions on Big Data (TBD) [2019];
  • China Communication (CNCOMM) (Big Data Special Issue) [2014];
  • International Journal of Distributed Sensor Networks [2015];
  • Neurocomputing [2015];
  • The Journal of Computers (JCP) [2013, 2014];
  • The Computer Journal (COMPJ) [2014];
  • Transactions on Spatial Algorithms and Systems (TSAS) [2016];
  • IEEE Transactions on Network Science and Engineering (TNSE) [2017, 2018];
  • Journal of Computers and Electrical Engineering [2017];
  • Journal of Data and Information Management (DIM) [2017];
  • Journal of Data Science and Engineering (DSEJ) [2018, 2020];
  • ACM Journal of Data and Information Quality (JDIQ) [2018, 2019, 2020];
  • Statistical Methods in Medical Research [2019];
  • IEEE Access [2019, 2020];
  • Science China Information Sciences (SCIS) [2020];
  • SpringerPlus [2015]; and
  • Journal of Web Engineering (JWE) [2015].
     More ...

  Program committee (PC) member and reviewer for:
  • Very Large Data Bases Conference (VLDB) [2019];
  • International Conference on Data Engineering (ICDE) [2012, 2018 (Demo Track), 2021, 2022 (Research and Demo Tracks)];
  • International Conference on Extending Database Technology (EDBT) [2020];
  • ACM Conference on Information and Knowledge Management (CIKM) [2011, 2017, 2018, 2020];
  • Association for Computing Machinery's Special Interest Group on Information Retrieval (ACM SIGIR) [2020];
  • ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS) [2015];
  • International Conference on Web-Age Information Management (WAIM) [2010, 2013, 2014, 2016];
  • International Asia-Pacific Web Conference (APWeb) [2013, 2014, 2016];
  • The Asia Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data (APWeb-WAIM) [2017, 2018, 2019, 2020];
  • International Conference on Web Information Systems Engineering (WISE) [2017, 2018];
  • International Conference on Database Systems for Advanced Applications (DASFAA) [2015, 2017, 2018, 2019, 2020];
  • IEEE International Conference on Computer and Information Technology (CIT) [2010, 2011, 2013];
  • IEEE International Conference on Parallel and Distributed Systems (ICPADS) [2014, 2017, 2018];
  • Asia-Pacific Services Computing Conference (APSCC) [2014, 2016];
  • International Joint Conference on Artificial Intelligence (IJCAI) [2015];
  • IEEE International Conference on Big Data (IEEE BigData) [2019];
  • Australasian Database Conference (ADC) [2017, 2018];
  • Wireless Telecommunications Symposium (WTS) [2015, 2016, 2017, 2018, 2019, 2020];
  • International Conference on Mobile Ad Hoc and Sensor Networks (IEEE MSN) [2016, 2018, 2019];
  • IEEE Frontiers in Education Conference (FIE) [2015, 2017];
  • International Conference on Big Data Computing and Communication (BIGCOM) [2016, 2017, 2018, 2019];
  • IEEE International Conference on Intelligent Cloud Computing (ICC) [2016];
  • International Workshop on Semantic Big Data (SBD @ SIGMOD) [2016, 2017, 2018, 2019, 2020];
  • International Workshop on Uncertain Data Computing [2013];
  • International Workshop on Graph Database (IWGD) [2010]; and
  • International Workshop on Management and mining Of UNcertain Data (MOUND) [2009].
     More ...

  External reviewer for:
  • ACM Conference on the Management of Data (SIGMOD) [2006, 2007, 2008, 2009, 2010, 2011, 2015, 2016];
  • Very Large Data Bases Conference (VLDB) [2004, 2005, 2006, 2007, 2008, 2010, 2012, 2013, 2015];
  • International Conference on Data Engineering (ICDE) [2006, 2007, 2008, 2009, 2010, 2011, 2013, 2014, 2015, 2017];
  • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD) [2010];
  • IEEE International Conference on Data Mining (ICDM) [2009, 2010, 2012, 2017];
  • International Conference on Extending Database Technology (EDBT) [2006, 2013, 2014];
  • International World Wide Web Conferences (WWW) [2008, 2009];
  • ACM Conference on Information and Knowledge Management (CIKM) [2005, 2013];
  • IEEE International Conference on Computer Communications (INFOCOM) [2013];
  • International Conference on Scientific and Statistical Database Management (SSDBM) [2005, 2007, 2008, 2010];
  • International Conference on Database Systems for Advanced Applications (DASFAA) [2011, 2014];
  • ACM Multimedia (MM) [2012];
  • ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS) [2009, 2010];
  • Symposium on Spatial and Temporal Databases (SSTD) [2005];
  • International Conference on Database and Expert Systems Applications (DEXA) [2004, 2005]; and
  • Mobile Data Management (MDM) [2009].
     More ...

  Tutorial for:   More professional services ...

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Grants and Awards  [Full Grant and Award List]
  More grants and awards ...

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Group Members

  Current Students:
  • Kovan Bavi, Ph.D. Student, Spring 2018
  • Mariha Ahammed, Undergraduate Student (under the SURE program), Summer 2022; Student Research Experience (SRE), Spring 2023
  • Halie Eckert, Undergraduate Student (under the COF program), 2020 - present
  • Gavin Hulvey, Undergraduate Student (under the COF program), 2021 - present
  • Sydney Zuelzke, Undergraduate Student (under the COF program), 2021 - present
  • Nathan Wolfe, Undergraduate Student (under the COF program), 2022 - present
  • Jagr Groubert, Undergraduate Student (under the COF program), 2022 - present
  • Chad Losey, Undergraduate Student (under the COF program), 2023 - present
  Graduated Students:
  • Niranjan Rai, Ph.D. Student, Spring 2017 (Graduated in 2022; Ph.D. Thesis: "Efficient Query Processing Over Large Road-Network Graphs");
  • Ahmed Al-Baghdadi, Ph.D. Student, Summer 2017 (Graduated in 2022; Ph.D. Thesis: "Efficient Query Processing Over Spatial-Social Networks");
  • Weilong Ren, Ph.D. Student, Fall 2017 (Graduated in 2021; Ph.D. Thesis: "Query Processing Over Incomplete Data Streams");
  • Uriah Tedrick, Undergraduate Student (under the COF program), Fall 2022;
  • Rajvi Soni, Undergraduate Student (under the SURE program), Summer 2022;
  • Brandon Cossin, Undergraduate Student (under the COF program), 2021 - 2022;
  • Troy Toth, Undergraduate Student (under the COF program), 2021 - 2022;
  • Andrew Hughes, Undergraduate Student (under the COF program), 2020 - 2021;
  • Lorenzo Gage Bair, Undergraduate Student (under the COF program), 2020 - 2021;
  • Jamie Bowen, Undergraduate Student (under the COF program), 2020;
  • Luke Sabo, Undergraduate Student, Summer 2020 - 2021;
  • Taksch Dube, Undergraduate Student, 2019 - 2020;
  • Bamikole Ogundele, Master Student (Graduated in 2015; Master's thesis: "Efficient Query Processing Over Uncertain Road Networks");
  • Vincent Schoenmakers, Master Student (Graduated in 2014; Master's project: "Facility Reservation Management System for UTRGV Wellness and Recreational Center");
  • Yaqing Chen, Master Student (Graduated in 2014; Master's thesis: "Probabilistic Shortest Time Queries Over Uncertain Road Networks");
  • Weiguo Zheng, Visiting Scholar (Mar. 2013 - July 2013; UTRGV), Ph.D. at Beijing University (China), Post-Doctoral Fellow at the Chinese University of Hong Kong (Hong Kong), Associate Professor at Fudan University (Shanghai, China).
  Student Achievements:

  • Andrew Hughes, Halie Eckert, and Lorenzo Bair, Undergraduate Students, "Efficient and Effective Management and Analytics Over Spatial-Social Networks", Top Project Award, Choose Ohio First (COF) Regional Symposium, Kent State University, Kent, Ohio, USA, 2021;

  • Ahmed Al-Baghdadi, Ph.D. Student, University Fellowship, Kent State University, Kent, Ohio, USA, 2021-2022;

  • Ahmed Al-Baghdadi, Ph.D. Student, Clayton and Audrey Hine Scholarship in Computer Science, $500, Department of Computer Science, Kent State University, Kent, Ohio, USA, 2020;

  • Weilong Ren, Ph.D. Student, University Fellowship, Kent State University, Kent, Ohio, USA, 2020-2021;

  • Weilong Ren, Ph.D. Student, SIGIR Student Travel Grant, $1,000, SIGIR, 2019;

  • Luke Sabo, Undergraduate Student, Summer Undergraduate Research Experience (SURE) Award, $2,800, Kent State University, Kent, Ohio, USA, Summer 2020;

  • Ahmed Al-Baghdadi, Ph.D. Student, Presentation of a VLDB 2020 Conference Paper entitled "Topic-based Community Search over Spatial-Social Networks", Tokyo, Japan, 2020;

  • Weilong Ren, Ph.D. Student, Presentation of a CIKM 2019 Conference Paper entitled "Efficient Join Processing Over Incomplete Data Streams", Beijing, China, 2019;

  • Weilong Ren, Ph.D. Student, Invited 4-min Teaser Talk of a VLDBJ paper at the PVLDB 2020 Conference entitled "Skyline Queries Over Incomplete Data Streams", Tokyo, Japan, 2020.

  More group members ...

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Projects

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Useful Links

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Copyright © by Xiang Lian (连翔).