Researcher Profile

Researcher Profile

Vasant Gajanan Honavar, PhD

Vasant Gajanan Honavar, PhD

Professor and Edward Frymoyer Chair of Information Sciences and Technology, College of Information Sciences and Technology
Professor of Computer Science, College of Information Sciences and Technology
Scientific Program:Cancer Control
Disease Teams:
Institute for CyberScience (ICS) - Co-hire
vuh14@psu.edu

Research Interests

  • Proteins
  • RNA
  • Binding Sites
  • B-Lymphocyte Epitopes
  • Databases
  • Genes
  • Learning
  • Gene Expression
  • Amino Acid Sequence
  • Amino Acids
  • Protein Interaction Maps
  • Epitopes

Recent Publications

2019

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Honavar, VG 2019, 'Machine learning in clinical care: Quo vadis?', Indian Journal of Ophthalmology, vol. 67, no. 7, pp. 985-986. https://doi.org/10.4103/ijo.IJO_1167_19
Sun, Y, Bui, N, Hsieh, TY & Honavar, VG 2019, Multi-view network embedding via graph factorization clustering and co-regularized multi-view agreement. in Z Li, H Tong, F Zhu & J Yu (eds), Proceedings - 18th IEEE International Conference on Data Mining Workshops, ICDMW 2018., 8637384, IEEE International Conference on Data Mining Workshops, ICDMW, vol. 2018-November, IEEE Computer Society, pp. 1006-1013, 18th IEEE International Conference on Data Mining Workshops, ICDMW 2018, Singapore, Singapore, 11/17/18. https://doi.org/10.1109/ICDMW.2018.00145
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Liang, J, Hu, J, Dong, S & Honavar, VG 2019, Top-N-Rank: A Scalable List-wise Ranking Method for Recommender Systems. in Y Song, B Liu, K Lee, N Abe, C Pu, M Qiao, N Ahmed, D Kossmann, J Saltz, J Tang, J He, H Liu & X Hu (eds), Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018., 8621994, Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1052-1058, 2018 IEEE International Conference on Big Data, Big Data 2018, Seattle, United States, 12/10/18. https://doi.org/10.1109/BigData.2018.8621994
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2018

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Hsieh, TY, Elmanzalawi, Y, Sun, Y & Honavar, VG 2018, Compositional Stochastic Average Gradient for Machine Learning and Related Applications. in H Yin, P Novais, D Camacho & AJ Tallón-Ballesteros (eds), Intelligent Data Engineering and Automated Learning – IDEAL 2018 - 19th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11314 LNCS, Springer Verlag, pp. 740-752, 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, Madrid, Spain, 11/21/18. https://doi.org/10.1007/978-3-030-03493-1_77
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Gur, S & Honavar, VG 2018, PATENet: Pairwise Alignment of Time Evolving Networks. in P Perner (ed.), Machine Learning and Data Mining in Pattern Recognition - 14th International Conference, MLDM 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10934 LNAI, Springer Verlag, pp. 85-98, 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, New York, United States, 7/15/18. https://doi.org/10.1007/978-3-319-96136-1_8
Jung, Y, Elmanzalawi, Y, Dobbs, D & Honavar, VG 2018, 'Partner-specific prediction of RNA-binding residues in proteins: A critical assessment', Proteins: Structure, Function and Bioinformatics. https://doi.org/10.1002/prot.25639
Khademi, A, Elmanzalawi, Y, Buxton, OM & Honavar, VG 2018, Toward personalized sleep-wake prediction from actigraphy. in 2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 414-417, 2018 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2018, Las Vegas, United States, 3/4/18. https://doi.org/10.1109/BHI.2018.8333456
Dyer, R, Honavar, VG, Leavens, GT, Nguyen, HA, Nguyen, TN & Rajan, H 2018, 'Welcome to the WASPI workshop' WASPI 2018 - Proceedings of the 1st ACM SIGSOFT International Workshop on Automated Specification Inference, Co-located with FSE 2018, pp. III.

2017

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Honavar, VG, Yelick, K, Nahrstedt, K, Rushmeier, H, Rexford, J, Hill, MD, Bradley, E & Mynatt, E 2017, Advanced Cyberinfrastructure for Science, Engineering, and Public Policy. Computing Community Consortium.
Hager, GD, Bryant, R, Horvitz, E, Mataric, M & Honavar, V 2017, Advances in Artificial Intelligence Require Progress Across all of Computer Science. Computing Community Consortium.
Barocas, S, Bradley, E, Honavar, V & Provost, F 2017, Big Data, Data Science, and Civil Rights. Computing Community Consortium.
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2016

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Honavar, VG, Hill, MD & Yelick, K 2016, Accelerating Science: A Computing Research Agenda. Computing Community Consortium.
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Dobbs, D, Brenner, SE, Honavar, VG, Jernigan, RL, Laederach, A & Morris, Q 2016, Regulatory RNA. in Pacific Symposium on Biocomputing 2016, PSB 2016. World Scientific Publishing Co. Pte Ltd, pp. 429-432, 21st Pacific Symposium on Biocomputing, PSB 2016, Big Island, United States, 1/4/16.
Santhanam, GR, Basu, S & Honavar, V 2016, Representing and Reasoning with Qualitative Preferences: Tools and Applications. in WW Cohen, RJ Brachman & P Stone (eds), Representing and Reasoning with Qualitative Preferences: Tools and Applications. Synthesis Lectures on Artificial Intelligence and Machine Learning, vol. 31, Morgan and Claypool Publishers, pp. 1-154. https://doi.org/10.2200/S00689ED1V01Y201512AIM031
Santhanam, GR, Basu, S & Honavar, V 2016, Representing and reasoning with qualitative preferences: Tools and applications. Synthesis Lectures on Artificial Intelligence and Machine Learning, vol. 10, Morgan and Claypool Publishers.
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2015

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Honavar, V 2015, Discovery informatics in biological and biomedical sciences: Research challenges and opportunities. in 20th Pacific Symposium on Biocomputing, PSB 2015. Stanford University, pp. 482, 20th Pacific Symposium on Biocomputing, PSB 2015, Big Island, United States, 1/4/15.
Lin, HT, Bui, N & Honavar, V 2015, Learning classifiers from remote RDF data stores augmented with RDFS subclass hierarchies. in F Luo, K Ogan, MJ Zaki, L Haas, BC Ooi, V Kumar, S Rachuri, S Pyne, H Ho, X Hu, S Yu, MH-I Hsiao & J Li (eds), Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015., 7363953, Proceedings - 2015 IEEE International Conference on Big Data, IEEE Big Data 2015, Institute of Electrical and Electronics Engineers Inc., pp. 1807-1813, 3rd IEEE International Conference on Big Data, IEEE Big Data 2015, Santa Clara, United States, 10/29/15. https://doi.org/10.1109/BigData.2015.7363953
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Sawyer, AM, Kang, Y, Honavar, V, Griffin, P & Prabhu, V 2015, 'Stimulating new and innovative perspectives on old and persistent problems: A commentary on "attempters adherers and non-adherers: Latent profile analysis of CPAP use with correlates" by wohlgemuth et al.' Sleep Medicine, vol. 16, no. 3, pp. 311-312. https://doi.org/10.1016/j.sleep.2014.11.011
Bui, N, Yen, J & Honavar, V 2015, Temporal causality of social support in an online community for cancer survivors. in K Xu, N Agarwal & N Osgood (eds), Social Computing, Behavioral-Cultural Modeling, and Prediction - 8th International Conference, SBP 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9021, Springer Verlag, pp. 13-23, 8th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, SBP 2015, Washington, United States, 3/31/15. https://doi.org/10.1007/978-3-319-16268-3_2

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