Scholar
Ling Liu
Google Scholar ID: VIwtdckAAAAJ
Georgia Institute of Technology
Citations & Impact
Citations
17,366
H-index
57
i10-index
277
Publications
20
Co-authors
136
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Prof. Dr. Ling Liu has published over 300 international journal and conference articles with high citations at Google Scholar. Her research group has produced several open-source software systems, including WebCQ, XWRAPElite, PeerCrawl, GTMobSIM, SHAPE, NEAT, TripleBit (jointly with Prof. Pingpeng Yuan), MemFlex, MemPipe, XMemPod, AdaTrace, FUSE, Fed-CDP, LRBench, XEnsemble1.0, Data Poisoning in FL. She is a recipient of the IEEE Computer Society Technical Achievement Award (2012) and an Outstanding Doctoral Thesis Advisor award from Georgia Institute of Technology in 2012. Her research group has received best paper awards 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.
Research Experience
- Prof. Dr. Ling Liu directs the research programs in Distributed Data Intensive Systems Lab (DiSL). Current active research projects include:
- - Big Data powered Artificial Intelligence, Machine Learning, and Cognitive Computing Systems
- - GTDLBench - Benchmarking Deep Learning Frameworks
- - LRBench - Benchmarking Learning Rate Policies for Deep Neural Networks
- - DP Model_Publishing - Differentially Private Model Publishing
- - CLDP - Condensed Local Differential Privacy for Privacy Preserving Data Collection
- - GT Attack Pod (MODEF)
- - DLEdge - Deep Learning on Edge Devices (Intel Sponsored)
- - NGramCNN - Learning to classify graph objects with a deep convolutional neural network
- - AdaTrace - Differentially Private and Attack Resilient Ap
Education
- No specific education background information provided.
Background
- Prof. Dr. Ling Liu is a full professor in the College of Computing at Georgia Institute of Technology and an elected IEEE Fellow. Her research interests are centered on data and intelligence powered computing, such as artificial intelligence, machine learning, knowledge discovery and data mining, big data systems and analytics. She is interested in developing innovative and efficient learning algorithms and systems for multi-modality of data, as well as algorithms and optimizations for improving performance, availability, security, privacy, trust of data and intelligence powered computing systems and applications, such as cloud and edge computing, distributed computing, Internet of smart things, mobile computing and location-based services, wireless and sensor networked computing, peer-to-peer and blockchain computing.
Miscellany
- No personal interests or other information provided in the given HTML content.
