World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
65
Citations
18148
World Ranking
2446
National Ranking
1225

Research.com Recognitions

  • 2018 - ACM Distinguished Member
  • 2018 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2006 - ACM Senior Member

Overview

Vasant Honavar is affiliated with Pennsylvania State University in the United States. Their primary research domain lies within Computer Science, with a focus on several subfields including Artificial Intelligence, Molecular Biology, Computer Networks and Communications, Computational Theory and Mathematics, and Computer Vision and Pattern Recognition.

Their research topics encompass a diverse range of areas:

  • Topic Modeling
  • Bayesian Modeling and Causal Inference
  • Adversarial Robustness in Machine Learning
  • Protein Structure and Dynamics
  • Computational Drug Discovery Methods
  • Time Series Analysis and Forecasting
  • Recommender Systems and Techniques

Honavar has published extensively in various academic venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Sleep Health
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of Clinical Oncology

Significant recent papers authored or co-authored include:

  • "Two-dimensional hybrid organic-inorganic perovskites as emergent ferroelectric materials" (2020), Journal of Applied Physics
  • "Feeding the machine: Challenges to reproducible predictive modeling in resting-state connectomics" (2021), Network Neuroscience
  • "Algorithmic Bias in Recidivism Prediction: A Causal Perspective (Student Abstract)" (2020), Proceedings of the AAAI Conference on Artificial Intelligence
  • "Detecting and Interpreting Changes in Scanning Behavior in Large Network Telescopes" (2022), IEEE Transactions on Information Forensics and Security
  • "Connected in health: Place-to-place commuting networks and COVID-19 spillovers" (2022), Health & Place

Frequent collaborators include:

  • Justin Petucci
  • Teng Xiao
  • Aria Khademi
  • Junjie Liang
  • Avnish Katoch

Over the course of their career, Vasant Honavar has received several recognitions including being named an ACM Distinguished Member and a Fellow of the American Association for the Advancement of Science (AAAS) in 2018. Additionally, they were designated an ACM Senior Member in 2006.

Best Publications

  • Feature subset selection using a genetic algorithm

    J. Yang;V. Honavar

  • Learn++: an incremental learning algorithm for supervised neural networks

    R. Polikar;L. Upda;S.S. Upda;V. Honavar

  • Mobile health technology evaluation: The mHealth evidence workshop

    Santosh Kumar;Wendy J. Nilsen;Amy Abernethy;Audie Atienza

  • Predicting linear B-cell epitopes using string kernels.

    Yasser El-Manzalawy;Drena Dobbs;Vasant Honavar

  • Predicting RNA-Protein Interactions Using Only Sequence Information

    Usha K Muppirala;Vasant G Honavar;Drena Dobbs

  • Constructive neural-network learning algorithms for pattern classification

    R. Parekh;J. Yang;V. Honavar

  • Grammar Inference Automata Induction and Language Acquisition

    Rajesh Parekh;Vasant Honavar

  • Predicting flexible length linear B-cell epitopes.

    Yasser EL-Manzalawy;Drena Dobbs;Vasant Honavar

  • Intelligent agents for intrusion detection

    G.G. Helmer;J.S.K. Wong;V. Honavar;L. Miller

  • Lightweight agents for intrusion detection

    Guy Helmer;Johnny S. K. Wong;Vasant G. Honavar;Les Miller

  • Prediction of RNA binding sites in proteins from amino acid sequence

    Michael Terribilini;Jae Hyung Lee;Changhui Yan;Robert L. Jernigan

  • Glycosylation site prediction using ensembles of Support Vector Machine classifiers

    Cornelia Caragea;Jivko Sinapov;Adrian Silvescu;Drena Dobbs

  • Recent advances in B-cell epitope prediction methods.

    Yasser EL-Manzalawy;Yasser EL-Manzalawy;Vasant Honavar

  • Learning classifiers for misuse and anomaly detection using a bag of system calls representation

    Dae-Ki Kang;D. Fuller;V. Honavar

  • Computational prediction of protein interfaces: A review of data driven methods

    Li C. Xue;Drena Dobbs;Alexandre M.J.J. Bonvin;Vasant Honavar

  • A two-stage classifier for identification of protein--protein interface residues

    Changhui Yan;Drena Dobbs;Vasant Honavar

  • A software fault tree approach to requirements analysis of an intrusion detection system

    Guy G. Helmer;Johnny S. Wong;Mark Slagell;Vasant G. Honavar

  • Predicting DNA-binding sites of proteins from amino acid sequence

    Changhui Yan;Michael Terribilini;Feihong Wu;Robert L. Jernigan

  • A framework for semantic web services discovery

    Jyotishman Pathak;Neeraj Koul;Doina Caragea;Vasant G. Honavar

  • Adversarial Attacks on Graph Neural Networks via Node Injections: A Hierarchical Reinforcement Learning Approach

    Yiwei Sun;Suhang Wang;Xianfeng Tang;Tsung-Yu Hsieh

  • Handbook of Natural Language Processing

    Rajesh Parekh;Vasant Honavar

Frequent Co-Authors

Jyotishman Pathak
Jyotishman Pathak Cornell University
Cornelia Caragea
Cornelia Caragea University of Illinois at Chicago
Robert L. Jernigan
Robert L. Jernigan Iowa State University
James D. McCalley
James D. McCalley Iowa State University
Robi Polikar
Robi Polikar Rowan University
Christopher K. Tuggle
Christopher K. Tuggle Iowa State University
James M. Reecy
James M. Reecy Iowa State University
Alexandre M. J. J. Bonvin
Alexandre M. J. J. Bonvin Utrecht University
Dianne Cook
Dianne Cook Monash University
Orfeu M. Buxton
Orfeu M. Buxton Pennsylvania State University

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