Naren RamakrishnanProfessor and Associate Head for Graduate Studies
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Research Interests
Naren Ramakrishnan is a professor and associate head for graduate studies in the department of computer science at Virginia Tech. He also serves as an adjunct professor at the Institute of Bioinformatics and Applied Biotechnology (IBAB), Bangalore, India. His expertise is data mining in scientific domains; past research has spanned protein design, biochemical networks, neuroscience, plant physiology, wireless communications, wood-based composites design, and sustainable design of data centers. His work has been covered by many outlets, including the NIH outreach publication Biomedical Computation Review, the National Science Foundation's Discoveries series, and ACM Technews (seven times). He serves on the editorial boards of IEEE Computer, Data Mining and Knowledge Discovery, Journal of Intelligent Information Systems, and Knowledge and Information Systems.
Naren has received an NSF Faculty Early CAREER Development grant (2000), the New Century Technology Council Innovation Award (2001), Dean's awards for both teaching excellence (2005) and research excellence (2010) at Virginia Tech, and HP Labs innovation awards (2009; 2010). He was an invited co-organizer of the National Academy of Engineering Frontiers of Engineering Symposium, held in Irvine, CA, Sep 2009. He has received funding from NSF, ONR, NIH, General Motors Research, and HP Labs.
Naren was included in two "40 under 40" lists: Computerworld's innovative IT people to watch (2007) and Purdue University's list of distinguished alumni (2010). Naren is an ACM Distinguished Scientist (2009). He received his Ph.D. in computer sciences from Purdue University. He is a member of the ACM, IEEE Computer Society, and the AAAI.
SoftlabURL: http://people.cs.vt.edu/~naren/group.html Softlab's emphasis is on the design of software systems that provide high-level abstractions to their users, in support of problem solving, knowledge discovery, or, information finding. Our work is highly interdisciplinary, both in the domains outside computer science that we support and in the areas within computer science that we integrate. |
Please see projects at: http://people.cs.vt.edu/~ramakris/
A Digital Library Testbed for Research Related to 4/16/2007 at Virginia Tech
Granting Institution: NSF IIS Special Projects Program
Amount: $199,993
Computational Models for Gene Silencing: Elucidating A Pervasive Biological Defense
Granting Institution: National Science Foundation
Amount: $1,267,410
Discovering the Neural Code: Data Mining Algorithms For Network Reconstruction
Granting Institution: General Motors Corporation
Amount: $220,262
Dryophile Genes To Engineer Stasis-Recovery Of Human Cells
Granting Institution: Office of Naval Research
Amount: $78,358
Formal Models, Algorithms, and Visualizations for Storytelling Analytics
Granting Institution: National Science Foundation
Amount:
III: Medium: Collaborative Research: Integration, Prediction, and Generation of Mixed Mode Information using Graphical Models, with Applications to Protein-Protein Interactions
Granting Institution: National Science Foundation
Amount:
Integrated Digital Library Support for Crisis, Tragedy, and Recovery, Co-Principal Investigator
Granting Institution: National Science Foundation: Information Integration and Informatics
Amount: $500,000
Participation on the Town Square in the Era of Web 2.0, Principal Investigator
Granting Institution: National Science Foundation, Social-Computational Systems Program
Amount: $750,000
Storytelling in the National Nuclear Archive
Granting Institution: Idaho National Labs
Amount: $10,866
Temporal Data Mining Solutions for Sustainable Data Centers
Granting Institution: Hewlett-Packard Labs Innovation Research
Amount:
The Adaptive Code Kitchen & Flexible Tools for Dynamic Application Composition
Granting Institution: National Science Foundation
Amount: $470,047
The Eukaryotic Cell Cycle as a Test Case for Modeling Cellular Regulation in a Collaborative PSE
Granting Institution: DARPA
Amount: $2,442,399

