Keke Chen

Assistant Professor

Office: 385 Joshi

Phone: 937-775-4642

Email: keke.chen AT wright dot edu

http://www.cs.wright.edu/~keke.chen

I direct the Data-Intensive Analysis and Computing (DIAC) Lab at Wright State University, and also affiliated with the Ohio Center of Excellence in Knowledge-Enabled Computing (the Kno.e.sis Center). Before joining Wright State, I was a senior scientist in Yahoo! Labs during 2006-2008. I received my Ph.D. degree in Computer Science from the College of Computing, Georgia Tech, in 2006.

Papers in 2011: Cresp - optimal MapReduce resource allocation, CloudVista - cloud-based data exploration, RASP perturbation for secure half-space queries on outsourced data.
Our research on cloud computing is supported by Amazon Web Services Research Grants!

I am looking for highly motivated students who are interested in doing research in data-intensive distributed computing and large-data analysis. Please stop by my office or email me (with your CV) if you are interested in working with me.

Research Interests

I am interested in topics related to data intensive computing and analysis, including but not limited to

Secure and privacy-preserving computing;
Databases, data mining, and scalable learning algorithms;
Visual analytics;
Web science: learning to rank, ranking function adaptation, anti-spamming, and social computing

Cresp: Cloud resource provisioning for large scale MapReduce programs.
RASP: efficient privacy-preserving outsourced query services on attack-resiliant perturbed databases in the cloud
CloudVista: Interactive visual data analytics for extreme scale data in the cloud.
Trada: regression tree based domain adaptation
GBRank: Learning to rank with pairwise preference data in the regression framework
Geometric data perturbation for privacy preserving outsourced data mining
BestK: Categorical data clustering and validation
TransClusterTransactional data clustering and validation
Stream BestK/HE-Tree: Change detection on categorical/transactional data streams
iVIBRATE: a visual framework for clustering large datasets
VISTA: visual rendering and validating clustering structures

IEEE International Conference on Cloud and Service Computing (CSC2011)
IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2011)
The International Conference on Web Information System Engineering (WISE 2011)
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2011)
IEEE Conference on Cloud Computing (CLOUD 2011, 2012)
IEEE Conference on Distributed Computing Systems (ICDCS 2011,2012)
MobiCloud Workshop In Conjunction with MobiCASE 2010
IEEE Conference on Web Services (ICWS 2010, 2011, 2012)
IEEE Conference on Data Mining (ICDM08),
International Future Internet Symposium (FIS08, FIS09),
International Conference on Cooperative Information Systems (CoopIS08),
Second International Workshop on Management of Cloud Systems in conjunction with ISCC 2012 (International Symposium on Computers and Communications)

Publicity Chair: On the Move Federated Conferences and Workshops (OTM2008)
Tutorial Chair: International Conference onf Collaborative Computing: CollaborateCom 2009

Distributed Computing and Systems (CEG435/635): Winter 2010
Cloud Computing (CS499/699): Fall 2009, Fall 2010, Fall 2011
Introduction to Database Systems (CS405/605): Spring 2009, Fall 2009, Spring 2010, Fall 2010, Winter 2011, Spring 2011
Special Topics in Privacy Aware Computing (CS790): Winter 2009, Winter 2011, Winter 2012
Data Structures and Algorithms (CS 400/600): Fall 2008, Fall 2011, Winter 2012
Introduction to Computer Science (CS240): Spring 2011

visits since Aug. 2008. Last Modified 2011