Prof. Dr. Ling Liu


College of Computing

Georgia Institute of Technology

Office: KACB, room 3340

Georgia Tech, 266 Ferst Dr, Atlanta, GA 30332-0765 USA
Phone +1-404-385-1139
FAX +1-404-385-2295
Email: lingliu AT cc dot gatech dot edu

GT Directory

ng Liu


If we knew what it was we were doing,
it would not be called research, would it?

-- Albert Einstein


Research Interests | Research Projects | Publications

Teaching | Postdocs & Graduate Students | DiSL | Calendar

Keynotes/Panels/Tutorials/Invited Talks | Professional Services | Interesting Web Links

Important Conferences | DBLP | GT  Digital Library | BibFinder


Short Bio

Prof. Dr. Ling Liu is a Professor in the College of Computing at Georgia Institute of Technology and an elected IEEE Fellow. She directs the research programs in Distributed Data Intensive Systems Lab (DiSL), examining performance, availability, security, privacy, trust, data mining, and data management issues in big data systems, cloud computing, distributed computing systems and big data powered deep learning sysems. Prof. Liu and the DiSL research group have been working on various aspects of distributed data intensive systems, ranging from Big Data systems and data analytics, Cloud Computing and cloud datacenters, distributed systems, decentralized and social computing, mobile and location based services, sensor network and event stream processing, to service oriented computing and architectures. She has published over 300 international journal and conference articles. Her research group has produced a number of open source software systems, among which the most popular ones include WebCQ,  XWRAPElite, PeerCrawl, GTMobSIM, and SHAPE. Prof. Dr. Liu is a recipient of IEEE Computer Society Technical Achievement Award (2012) and an Outstanding Doctoral Thesis Advisor award from Georgia Institute of Technology in 2012. She has published over 300 international journal and conference articles and is a recipient of the best paper award from numerous top venues, including ICDCS 2003, WWW 2004, 2005 Pat Goldberg Memorial Best Paper Award, IEEE Cloud 2012, IEEE ICWS 2013, Mobiqutious 2014, APWeb 2015, IEEE/ACM CCGrid 2015, IEEE Symposium on Big Data 2016, IEEE Edge 2017 and IEEE IoT 2017. Prof. Dr. Ling Liu has served as a general chair or a PC chair of numerous IEEE and ACM conferences in data engineering, very large databasesBig data, and distributed computing fields, and most recently, the PC chair of IEEE ICDCS 2017 and a co-PC chair of IEEE 2016 Big Data Conference. Prof. Liu has been on editorial board of over a dozen international journals, and served as the Editor In Chief of IEEE Transactions on Service Computing (2013-2016). Prof. Dr. Liu's current research is primarily sponsored by NSF, IBM, and Intel.

Active Research Projects

Big Data Processing and Data Analytics as a Service

NGramCNN - Learning to classify graph objects with a deep convolutional neural network (incl. software download).

SI-Cluster - Social Influence Analytics in Heterogeneous Information Networks (software download)

VEPathCluster - Social Influence Analytics in Heterogeneous Information Networks (software download)

GraphLens - Social Influence Analytics in Heterogeneous Information Networks (software download)

SHAPE - Semantic Hash Partitioning for Distributed Processing of big RDF datasets

TripleBit - A Fast and Compact RDF Store

NEAT - Trajectory Clustering and Spatial Pattern Mining

Privacy Preserving Data Analytics

Adversarial Deep Learning with Privacy Awareness

PPML - Privacy Preserving Machine Learning

PrivacyGuard - NSF SaTC Medium: Privacy Preserving Computations in Big Data Clouds

Privacy and Security of EHR and eHealth Systems

PPN - NSF NetSE Medium: Privacy Preserving Information Networks and Services for eHealthcare Systems and `Applications

MedVault - NSF CyberTrust Medium: Ensuring Security & Privacy for Medical Data )

Mobile Internet: Systems, Services, Applications, and Beyond

GTMobiSIM - Mobility Simulation and Trace Generator (GTMobiSIM Visualizer)

MobiEyes - Distributed Computing Architecture and Algorithms for Processing Location Queries

GeoGrid / GeoCast - Decentralized Service Architecture for Mobile Location-based Information Delivery and Dissemination

Location Privacy - Location Privacy in Mobile Computing Systems and Applications

Spatial Alarms / mTriggers – High Performance Architecture and Models for Scalable Processing of Location Triggers

Location based Access Control (LBAC) – Secure Location Determination and Verification: Models and Techniques


Distributed Computing Systems Research

GTPeers - Peer-to-Peer and Grid Computing Research

HyperBee / Apoidea / PeerCrawl - Peer-to-Peer Web Crawling and Search

SGuard - Secure Guards for Massively Distributed Computing Systems

MedVault - Ensuring Security and Privacy for Electronic Medical Records

Guarding the Next Internet Frontier: Countering Denial of Information


Distributed Data Management and Large Scale Enterprise Services

XWrapElite - An Automated Wrapper Generation System for Web Sources

XWrapComposer - A Wrapper Generation System for Extracting Information from Multiple Web Pages

WebCQ - Continual Queries for Information Monitoring on the Web

Privacy-preserving Data Classification using Geometric Transformations

Enterprise Workflow and ServiceOriented Computing

Privacy Preserving in Data Stream and Event Stream Mining

Storage as Service: Architectures and Models for Performance, Failure Resilience, and Security


Past Research Projects

PeerCQ - Internet Information Monitoring Using a Peer-to-Peer network

PeerTrust  Trusted Computing in Peer to Peer Systems

TrustMe - Anonimity Support in Distributed Trust Management Systems

Edge Caching Grid for Dynamic Content Delivery

Scientific Data Management and BioComputing

VISTA - Effective Cluster Rendering of Very Large Data Sets and an application of VISTA

iVIBRATE - Interactive Visualization Based Framework for Clustering Large Datasets

BestK: the Critical Clustering Structure in Categorical Datasets

Infosphere - Infopipes Technology for Fresh Information Delivery

THOR - Deep Web Data Extraction

Athena - Web Service Discovery: A Source Biased Approach

OpenCQ - Continual Queries for Logistic Applications

XWrap Original - A Semi-Automated Wrapper Generation System for Structured or Semi-structured Data Sources

Omini - A Fast Object Extraction System for Web Sources

AQR - Distributed Query Routing

Ginga - Adaptive Query Processing with varying resource availabilities and constraints

PageDigest Efficient Encoding Scheme for Web Documents

Sdiff - Structurally aware change detection algorithms for HTML and XML documents

Context Cube - A Context Aware Methodology for Managing and Accessing Sensor Data - GT Aware Home

TAM - Restructuring and Self-Configuring of Transactional Workflow Systems




Data Mining and Data Warehousing



I have taught the following courses from 1999 to present. I have also created the course cs6220 (used to be cs8803 BDS since 2015.

CS8803: Big Data Systems and Analytics ( Fall 2018, Fall 2017, Fall 2016, Fall 2015)

CS6675/CS4675: Advanced Internet Computing Systems and Application Development ( Spring 2018, Spring 2017, Spring 2016, Spring 2015, Spring 2014, Spring 2013, Spring 2012,
used to be cs8803 AIA: 2011, 2010, 2009, 2008, Spring 2007, Spring 2006, Spring 2005, Spring 2004)

CS4420: Database System Implementation ( Fall 2014, Fall 2013, Spring 2013, Spring 2005, Spring 2004, Spring 2003)

CS4440: Emerging Database Technologies (Fall 2009, Fall 2008, Fall 2007)

CS1371: Computing for Engineers (Spring 2007)

cs3210 Design of Operating Systems (2011 Fall)

CS4400: Introduction to Database Systems (Spring 2006, Spring 2002, Spring 2000)

I have taught the following courses during 1997-1999 at OGI:

CSE515 Distributed Computing Systems

CSE543/CSE583 Distributed Information Management on the Net

I also supervisee A list of cs7001 mini-projects each year.

Research Groups

Distributed data Intensive Systems Lab (DiSL)

Systems Research Group

Database Research Group


Last updated Aug. 18, 2016. Ling Liu (lingliu at cc dot gatech dot edu)