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Active Grants and Awards

Integrating Cybersecurity with Undergraduate IT Programs

Source:   National Science Foundation (NSF)

PI:  Vandana Janeja, PhD, Co PIs: Aryya Gangopadhyay, PhD, Carolyn Seaman, PhD

Awarded:  2015

Project Web page: http://userpages.umbc.edu/~vjaneja/CYBR.html

 

Cybersecurity has become a matter of national and global importance because of the economy’s dependence on the Internet, and on cyber-infrastructure. Workforce development through cyber education and training are key towards protecting the ever-growing cyberspace and cyberinfrastructure. However, US universities are not graduating nearly sufficient workforce in the IT areas, let alone cybersecurity. Academic programs in STEM and IT fields are uniquely positioned to address this need. Tailoring curricula in these areas to include cyber education can bridge the gap existing between the demand and supply of trained workforce. Existing certificate programs do not offer a data analytics perspective along with a software security and network security perspective for undergraduate curricula. In addition, the existing certificates are not seamlessly integrated with the existing curriculum towards a bachelor’s degree. This project is motivated to fill this gap.

 

Discovering Anomalous Spatio-temporal Associations

 

Source:   Army Corps of Engineers

PI:  Vandana Janeja, PhD

Awarded:  2015

Project Web page: http://userpages.umbc.edu/~vjaneja/SDM.html

 

The focus of this project is the discovery of unusual spatio-temporal associations across multiple phenomena from distinct application domains in a spatial region. We propose to find such associations across multiple phenomena represented by the series of anomalous windows discovered in each domain over a period of time. An anomalous window is made up of a set of contiguous points in a region and is unusual with respect to the rest of the data in the region, in terms of an attribute of interest. This proposal aims to discover potentially significant links between several such series of anomalous windows across domains in a spatial region across intervals of time.

 

Mining Big-Clinical Trial data for Supervised and Unsupervised  Learning

Source:   Ekagra Software Technologies

PI:  Vandana Janeja, PhD

Awarded:  2014

Big Data deals with huge-volumes of complex, exponentially growing data sets from multiple, sources. With rapid growth in networking we are now able to generate immense amount of data in almost any field imaginable, including physical, biological and biomedical sciences. With the diversity and amounts of data in healthcare there is an increasing need to evaluate components in big data frameworks and gauge their adaptability to analytical techniques. This project has two fold objectives:

First, a key step in adapting big data tools is the portability of RDBMS to big data environments. In this project we evaluate the performance of SQL like big data solutions for portability of existing RDBMS solutions. The project focuses on benchmarking multiple SQL like big data technologies over HDFS for Study Data Tabulation Model (SDTM) used in clinical trial databases for improving the efficiency of research in clinical trials where we measure key parameters such as usability, adaptability and modularity, robustness and efficiency. Second, due to dispersed nature of clinical trial data, it remains a challenge to harness this data for analytics. In this project, we propose a master data management (MDM) solution using ETL (extract-transform-load) techniques for integrating the scattered clinical reference data into its consolidated form, which can subsequently be used for data mining. Our aim is to correlate our findings from multiple data mining techniques such as classification, clustering and association analysis. We complement our results with the help of interactive visualizations. Overall, our approach aims at detecting interesting patterns from clinical trial data with the set of data integration and data mining methodologies.

 

Prior Grants and Awards

·         Biomedical Informatics for Clinical Decision  Support, sponsor: Northrop Grumman, 12/15/2013 – 12/14/2015, Co-PI

·         Big Data Analytics with the LexisNexis HPCC System, Sponsor LexisNexis, 12/15/2013 – 12/14/2014, Co-PI

·         UMBC, Special Research Assistantship/Initiative Support (SRAIS) Award, 2009-2010

·         Anomaly Detection for Traffic Monitoring Data, sponsor: MDoT-State Highway Administration, PI: Aryya Gangopadhyay, Co-PIs : Vandana Janeja and Andrew Sears, duration: 02/01/09-01/31/10

·         UMBC, Summer Faculty Fellowship (SFF) Award, Summer 2008

·         Rutgers Business School Dean’s Fellowship, September 2005 to June 2006.

·         Rutgers Business School Dean award - PhD competition, summer 2005.

·         Rutgers Business School Dean award - PhD competition, summer 2004.

·         “E-Business Solutions to Border Control Challenges”, Feature article in 2001-2002 Rutgers’s Newark Provost’s report with Dr. R. Koslowski.

·         Honors Scholarship from National Institute of Information Technology, India, 1994-1997.