World's Best Scientists 2026 revealed!
Naren Ramakrishnan

Naren Ramakrishnan

D-Index & Metrics

Computer Science

D-Index
60
Citations
12102
World Ranking
3286
National Ranking
1590

Research.com Recognitions

  • 2009 - ACM Distinguished Member

Overview

Naren Ramakrishnan is affiliated with Virginia Tech in the United States, specializing in Computer Science with a primary focus on Artificial Intelligence. Their research spans multiple subfields including Statistical and Nonlinear Physics, Molecular Biology, Computer Networks and Communications, and Epidemiology.

The scientist's work covers a range of topics, with notable emphasis on Anomaly Detection Techniques and Applications, Topic Modeling, Natural Language Processing Techniques, Network Security and Intrusion Detection, Data-Driven Disease Surveillance, Complex Network Analysis Techniques, and Scientific Computing and Data Management.

Naren Ramakrishnan has contributed extensively to academic literature with frequent publications in multiple venues. The top venues for their research include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • ACM Transactions on Knowledge Discovery from Data
  • ACM Transactions on Intelligent Systems and Technology
  • bioRxiv (Cold Spring Harbor Laboratory)

Some of their recent papers are:

  • Neural Abstractive Text Summarization with Sequence-to-Sequence Models, 2021, ACM/IMS Transactions on Data Science
  • Optimal sizing of rainwater harvesting systems for domestic water usages: A systematic literature review, 2020, Resources Conservation & Recycling X
  • Fine-Grained Photovoltaic Output Prediction Using a Bayesian Ensemble, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems, 2020, Big Data
  • Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19, 2021, Proceedings of the AAAI Conference on Artificial Intelligence

The scientist has collaborated frequently with several coauthors, including Nikhil Muralidhar, Mandar Sharma, Nathan Self, Subhodip Biswas, and Chang-Tien Lu.

In addition to journal publications, Naren Ramakrishnan has contributed to book publications with Springer Science+Business Media, notably on works titled Advances in Knowledge Discovery and Data Mining published in 2021.

Among recognized achievements, they have been named an ACM Distinguished Member since 2009.

Best Publications

  • Epidemiological modeling of news and rumors on Twitter

    Fang Jin;Edward Dougherty;Parang Saraf;Yang Cao

  • 'Beating the news' with EMBERS: forecasting civil unrest using open source indicators

    Naren Ramakrishnan;Patrick Butler;Sathappan Muthiah;Nathan Self

  • Neural Abstractive Text Summarization with Sequence-to-Sequence Models

    Tian Shi;Yaser Keneshloo;Naren Ramakrishnan;Chandan K. Reddy

  • Privacy risks in recommender systems

    N. Ramakrishnan;B.J. Keller;B.J. Mirza;A.Y. Grama

  • Deep Reinforcement Learning for Sequence-to-Sequence Models

    Yaser Keneshloo;Tian Shi;Naren Ramakrishnan;Chandan K. Reddy

  • The human is the loop: new directions for visual analytics

    Alex Endert;M. Shahriar Hossain;Naren Ramakrishnan;Chris North

  • Misinformation Propagation in the Age of Twitter

    Fang Jin;Wei Wang;Liang Zhao;Edward Dougherty

  • Photosynthetic Acclimation Is Reflected in Specific Patterns of Gene Expression in Drought-Stressed Loblolly Pine

    Jonathan I. Watkinson;Allan A. Sioson;Cecilia Vasquez-Robinet;Maulik Shukla

  • Studying Recommendation Algorithms by Graph Analysis

    Batul J. Mirza;Benjamin J. Keller;Naren Ramakrishnan

  • Multi-Task Learning for Spatio-Temporal Event Forecasting

    Liang Zhao;Qian Sun;Jieping Ye;Feng Chen

  • Sub2Vec : Feature Learning for Subgraphs

    Bijaya Adhikari;Yao Zhang;Naren Ramakrishnan;B. Aditya Prakash

  • Incorporating Prior Domain Knowledge into Deep Neural Networks

    Nikhil Muralidhar;Mohammad Raihanul Islam;Manish Marwah;Anuj Karpatne

  • Data mining: from serendipity to science

    N. Ramakrishnan;A.Y. Grama

  • Algorithms for Storytelling

    D. Kumar;N. Ramakrishnan;R.F. Helm;M. Potts

  • Collaborative efforts to forecast seasonal influenza in the United States, 2015–2016

    Craig J. McGowan;Matthew Biggerstaff;Michael Johansson;Karyn M. Apfeldorf

  • Crowdsourcing Cybersecurity: Cyber Attack Detection using Social Media

    Rupinder Paul Khandpur;Taoran Ji;Steve Jan;Gang Wang

  • Growing pains for global monitoring of societal events.

    Wei Wang;Ryan Kennedy;David Lazer;David Lazer;Naren Ramakrishnan

  • Turning CARTwheels: an alternating algorithm for mining redescriptions

    Naren Ramakrishnan;Deept Kumar;Bud Mishra;Malcolm Potts

  • PYTHIA-II: a knowledge/database system for managing performance data and recommending scientific software

    Elias N. Houstis;Ann C. Catlin;John R. Rice;Vassilios S. Verykios

  • In-building wideband multipath characteristics at 2.5 and 60 GHz

    C.R. Anderson;T.S. Rappaport;K. Bae;A. Verstak

  • Compression, clustering, and pattern discovery in very high-dimensional discrete-attribute data sets

    M. Koyuturk;A. Grama;N. Ramakrishnan

Frequent Co-Authors

Layne T. Watson
Layne T. Watson Virginia Tech
Chang-Tien Lu
Chang-Tien Lu Virginia Tech
Lenwood S. Heath
Lenwood S. Heath Virginia Tech
Chris North
Chris North Virginia Tech
B. Aditya Prakash
B. Aditya Prakash Georgia Institute of Technology
Ratnesh Sharma
Ratnesh Sharma NEC (United States)
Ananth Grama
Ananth Grama Purdue University West Lafayette
Richard F. Helm
Richard F. Helm Virginia Tech
Madhav V. Marathe
Madhav V. Marathe University of Virginia
Edward A. Fox
Edward A. Fox Virginia Tech

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