For the most up to date list of publications please visit ORCID iD icon ORCID, Google Scholar, or DBLP Computer Science Bibliography.

Theses

Peer-reviewed Journal Articles

  1. Vilkomir, K., Phen, C., Baldwin, F., Cole, J., Herndon, N., and Zhang, W. (2024). Classification of mandibular molar furcation involvement in periapical radiographs by deep learning. Imaging Science in Dentistry, 2024, Aug;54:e33.
  2. Spoor, S., Wytko, C., Soto, B., Chen, M., Almsaeed, A., Condon, B., Herndon, N., Hough, H., Jung, S., Staton, M., Wegrzyn, J., Main, D., Feltus, F. A., and Ficklin, S. P. (2020). Tripal and Galaxy: supporting reproducible scientific workflows for community biological databases. Database, 2020. baaa032.
  3. Herndon, N., Shelton, J., Gerischer, L., Ioannidis, P., Ninova, M., Dönitz, J., Waterhouse, R. M., Liang, C., Damm, C., Siemanowski, J., Kitzmann, P., Ulrich, J., Dippel, S., Oberhofer, G., Hu, Y., Schwirz, J., Schacht, M., Lehmann, S., Montino, A., Posnien, N., Gurska, D., Horn, T., Seibert, J., Vargas Jentzsch, I. M., Panfilio, K. A., Li, J., Wimmer, E. A., Stappert, D., Roth, S., Schröder, R., Park, Y., Schoppmeier, M., Chung, H.-R., Klingler, M., Kittelmann, S., Friedrich, M., Chen, R., Altincicek, B., Vilcinskas, A., Zdobnov, E., Griffiths-Jones, S., Ronshaugen, M., Stanke, M., Brown, S. J., and Bucher, G. (2020). Enhanced genome assembly and a new official gene set for tribolium castaneum. BMC Genomics, 21(1):47.
  4. Wegrzyn, J. L., Falk, T., Grau, E., Buehler, S., Ramnath, R., and Herndon, N. (2019). Cyberinfrastructure and resources to enable an integrative approach to studying forest trees. Evolutionary Applications, 00:1-14, 2019.
  5. Wegrzyn, J. L., Staton, M. A., Street, N. R., Main, D., Grau, E., Herndon, N., Buehler, S., Falk, T., Zaman, S., Ramnath, R., Richter, P., Sun, L., Condon, B., Almsaeed, A., Chen, M., Mannapperuma, C., Jung, S., and Ficklin, S. (2019). Cyberinfrastructure to improve forest health and productivity: The role of tree databases in connecting genomes, phenomes, and the environment. Frontiers in Plant Science, 10:813, 2019.
  6. Harper, L., Campbell, J., Cannon, E. K. S., Jung, S., Poelchau, M., Walls, R., Andorf, C., Arnaud, E., Berardini, T. Z., Birkett, C., Cannon, S., Carson, J., Condon, B., Cooper, L., Dunn, N., Elsik, C. G., Farmer, A., Ficklin, S. P., Grant, D., Grau, E., Herndon, N., Hu, Z.-L., Humann, J., Jaiswal, P., Jonquet, C., Laporte, M.-A., Larmande, P., Lazo, G., McCarthy, F., Menda, N., Mungall, C. J., Munoz-Torres, M. C., Naithani, S., Nelson, R., Nesdill, D., Park, C., Reecy, J., Reiser, L., Sanderson, L.-A., Sen, T. Z., Staton, M., Subramaniam, S., Tello-Ruiz, M. K., Unda, V., Unni, D., Wang, L., Ware, D., Wegrzyn, J., Williams, J., Woodhouse, M., Yu, J., and Main, D. (2018). AgBioData Consortium Recommendations for Sustainable Genomics and Genetics Databases for Agriculture, Database, 2018:bay088.
  7. Falk, T., Herndon, N., Grau, E., Buehler, S., Richter, P., Zaman, S., Baker, E. M., Ramnath, R., Ficklin, S., Staton, M., Feltus, F. A., Jung, S., Main, D., and Wegrzyn, J. L. (2018). Growing and cultivating the forest genomics database, TreeGenes. Database (2018) Vol. 2018.
  8. Kim, D., Jaworski, D. C., Cheng, C., Nair, A. D. S., Ganta, R. R., Herndon, N., Brown, S. J., and Park, Y. (2018). The transcriptome of the lone star tick, Amblyomma americanum, reveals molecular changes in response to infection with the pathogen, Ehrlichia chaffeensis. Journal of Asia-Pacific Entomology, 21(3):852–863, 2018.
  9. Li, H., Caragea, D., Caragea, C., and Herndon, N. (2017). Disaster response aided by tweet classification with a domain adaptation approach. Journal of Contingencies and Crisis Management, 2017;00:1-12.
  10. Kanost, M. R., Arrese, E. L., Cao, X., Chen, Y.-R., Chellapilla, S., Goldsmith, M. R., Grosse-Wilde, E., Heckel, D. G., Herndon, N., Jiang, H., Papanicolaou, A., Qu, J., Soulages, J. L., Vogel, H., Walters, J., Waterhouse, R. M., Ahn, S.-J., Almeida, F. C., An, C., Aqrawi, P., Bretschneider, A., Bryant, W. B., Bucks, S., Chao, H., Chevignon, G., Christen, J. M., Clarke, D. F., Dittmer, N. T., Ferguson, L. C., Garavelou, S., Gordon, K. H., Gunaratna, R. T., Han, Y., Hauser, F., He, Y., Heidel-Fischer, H., Hirsh, A., Hu, Y., Jiang, H., Kalra, D., Klinner, C., Konig, C., Kovar, C., Kroll, A. R., Kuwar, S. S., Lee, S. L., Lehman, R., Li, K., Li, Z., Liang, H., Lovelace, S., Lu, Z., Mansfield, J. H., McCulloch, K. J., Mathew, T., Morton, B., Muzny, D. M., Neunemann, D., Ongeri, F., Pauchet, Y., Pu, L.-L., Pyrousis, I., Rao, X.-J., Redding, A., Roesel, C., Sanchez- Gracia, A., Schaack, S., Shukla, A., Tetreau, G., Wang, Y., Xiong, G.-H., Traut, W., Walsh, T. K., Worley, K. C., Wu, D., Wu, W., Wu, Y.-Q., Zhang, X., Zou, Z., Zucker, H., Briscoe, A. D., Burmester, T., Clem, R. J., Feyereisen, R., Grimmelikhuijzen, C. J., Hamodrakas, S. J., Hansson, B. S., Huguet, E., Jermiin, L. S., Lan, Q., Lehman, H. K., Lorenzen, M., Merzendorfer, H., Michalopoulos, I., Morton, D. B., Muthukrishnan, S., Oakeshott, J. G., Palmer, W., Park, Y., Passarelli, A. L., Rozas, J., Schwartz, L. M., Smith, W., Southgate, A., Vilcinskas, A., Vogt, R., Wang, P., Werren, J., Yu, X.-Q., Zhou, J.-J., Brown, S. J., Scherer, S. E., Richards, S., and Blissard, G. W. (2016). Multifaceted biological insights from a draft genome sequence of the tobacco hornworm moth, Manduca sexta. Insect Biochemistry and Molecular Biology 76 (2016): 118-147.
  11. Raithel, S., Johnson, L., Galliart, M., Brown, S. J., Shelton, J. M., Herndon, N., and Bello, N. M. (2016). Inferential considerations for low-count RNA-seq transcripts: a case study on an edaphic subspecies of dominant prairie grass Andropogon gerardii. BMC Genomics, 17(140):1-16.
  12. Herndon, N., and Caragea, D. (2016). A Study of Domain Adaptation Classifiers Derived from Logistic Regression for the Task of Splice Site Prediction. IEEE Transactions on NanoBioscience, PP(99):1-9.
  13. Herndon, N., and Caragea, D. (2016). An evaluation of approaches for using unlabeled data with domain adaptation. Network Modeling Analysis in Health Informatics and Bioinformatics, 5(25):1-12.
  14. Tangirala, K., Herndon, N., and Caragea, D. (2016). A Comparative Analysis between k-mers and Community Detection-based Features for the Task of Protein Classification. IEEE Transactions on NanoBioscience, PP(99):1-9.
  15. Shelton, J. M., Coleman, M. C., Herndon, N., Lu, N., Lam, E. T., Anantharaman, T., Sheth, P., and Brown, S. J. (2015). Tools and pipelines for BioNano data: molecule assembly pipeline and FASTA super scaffolding tool. BMC Genomics, 16(1):734.
  16. Zhao, C., Escalante, L., Chen, H., Benatti, T., Qu, J., Chellapilla, S., Waterhouse, R., Wheeler, D., Andersson, M., Bao, R., Batterton, M., Behura, S., Blankenburg, K., Caragea, D., Carolan, J., Coyle, M., El-Bouhssini, M., Francisco, L., Friedrich, M., Gill, N., Grace, T., Grimmelikhuijzen, C., Han, Y., Hauser, F., Herndon, N., Holder, M., Ioannidis, P., Jackson, L., Javaid, M., Jhangiani, S., Johnson, A., Kalra, D., Korchina, V., Kovar, C., Lara, F., Lee, S., Liu, X., Lofstedt, C., Mata, R., Mathew, T., Muzny, D., Nagar, S., Nazareth, L., Okwuonu, G., Ongeri, F., Perales, L., Peterson, B., Pu, L.-L., Robertson, H., Schemerhorn, B., Scherer, S., Shreve, J., Simmons, D., Subramanyam, S., Thornton, R., Xue, K., Weissenberger, G., Williams, C., Worley, K., Zhu, D., Zhu, Y., Harris, M., Shukle, R., Werren, J., Zdobnov, E., Chen, M.-S., Brown, S., Stuart, J., and Richards, S. (2015). A Massive Expansion of Effector Genes Underlies Gall-Formation in the Wheat Pest Mayetiola destructor. Current Biology, 25(5):613 - 620.

Book Chapters

  1. Mehta, A., Bi, R., Moamen, S., Abdelaal, M., and Herndon, N. (2023). Automatic Detection of Facial Landmarks for Denture Models. Cuzzocrea, A., Gusikhin, O., Hammoudi, S., Quix, C. (Eds.) Data Management Technologies and Applications. Communications in Computer and Information Science, Springer Nature Switzerland, 2023, vol. 1860, pp. 114–133.
  2. Herndon, N., Falk, T., Grau, E. S., Jung, S., Ficklin, S., Main, D., Staton, M. E., and Wegrzyn, J. L. (2018). Association mapping for forest trees with CartograTree. Thessen, AE (Ed.) Application of Semantic Technologies in Biodiversity Science. Studies on the Semantic Web, IOS Press/AKA Verlag, 2018, vol. 33, pp. 137-149.
  3. Herndon, N., and Caragea, D. (2015). Empirical Study of Domain Adaptation Algorithms on the Task of Splice Site Prediction. In Biomedical Engineering Systems and Technologies, ser. Communications in Computer and Information Science, Springer International Publishing, 2015, vol. 511, pp. 195-211.
  4. Herndon, N., and Caragea, D. (2014). Predicting Protein Localization Using a Domain Adaptation Approach. In Biomedical Engineering Systems and Technologies, ser. Communications in Computer and Information Science, Springer Berlin Heidelberg, 2014, vol. 452, pp. 191-206.

Interviews, Speeches, Lectures

  1. Herndon, N. and Hart, D. (2024). How AI Learns and Why that Matters to You. Teaching and Research in the Age of Artificial Intelligence (AI), Greenville, NC. November 6, 2024. Workshop presentation.
  2. Herndon, N., and Uche, A. (2024). WITN, hosted by Amarachi Uche. TV interview. Expert discusses AI misinformation hitting Western Carolina following Helene, October 4, 2024.
  3. Herndon, N., and Ryu, H. (2024). WITN, hosted by Hojung Ryu. TV interview. ECU holds job fair amid growing AI presence in the job market, September 25, 2024.
  4. Hart, D., and Herndon, N. (2024). How AI Learns and Why That Matters. Greenville Noon Rotary Club, Greenville, NC. August 19, 2024. Short presentation.
  5. Herndon, N., and Morgan, M. (2024). WITN, hosted by Merit Morgan. TV interview. ECU Computer Science expert breaks down Artificial Intelligence advancements, July 30, 2024.
  6. Herndon, N., and Hart, D. (2024). Is AI a friend or a foe?. AI Roundtable: Artificial Intelligence and Machine Learning in Defense & Industry at DANC Science & Technology Forum. April 23, 2024. Short presentation and panel discussion.
  7. Herndon, N. (2023). You and AI. East Carolina University’s podcast, Talk Like a Pirate, hosted by Rich Klindworth. November 8, 2023. Podcast interview.
  8. Herndon, N., Lassiter, S., and Madigan, B. (2023). WNCT 9 On Your Side, hosted by Erin Jenkins and Sarah Gray Barr. TV interview. Classroom Conversations: The discussions of AI in classrooms, August 29, 2023.
  9. Herndon, N. (2023). NewsChannel 12 Investigates, hosted by Tyler Hardin, NewsChannel 12. TV interview.
  10. Haberstroh, A., Kariko, D., Kavner, A., Lamb, R., Thomas, J., and Herndon, N. (2023). Transforming Research Practice Through Artificial Intelligence, April 26, 2023, East Carolina University, Greenville, NC. Panel discussion.
  11. Banks, W., Faranesh, L., Click-Kimber, C.J., Herndon, N., Haberstroh, A., Thomas, J., and Tillman, J. (2023). Teaching and Learning in the Age of Generative Artificial Intelligence (ChatGPT): Opportunities and Challenges, April 3, 2023, East Carolina University, Greenville, NC. Panel discussion.
  12. Herndon, N. (2023). Ethical considerations for data collection and use. Love Data Week, Greenville, NC. February 14, 2023. Lecture.
  13. Herndon, N. (2022). Is AI smarter than a 5th grader? Nerd Nite Greenville, NC. October 14, 2022. 20 minute fun-yet-informative presentation.
  14. Herndon, N. (2021). Data science to mitigate global warming effects. The 30th International Conference on Software Engineering and Data Engineering (SEDE 2021), Virtual Conference Online. October 11, 2021. Keynote speech.

Peer-reviewed Conference Papers

  1. Vilkomir, K. and Herndon, N. (2024). Challenges of Automatic Document Processing with Historical Data. In Proceedings of the 62nd ACMSE Conference (ACMSE 2024), Marietta, GA, pp. 50–59. [Regular paper]
  2. Rose, M., Geradts, J., and Herndon, N. (2024). Deep learning in digital breast pathology. In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOINFORMATICS 2024), Rome, Italy, pp. 404–414. [Regular paper. Acceptance rate: 11%]
  3. Mehta A., Abdelaal M., Sheba M., and Herndon, N. (2023). Finding Similar Non-Collapsed Faces to Collapsed Faces Using Deep Learning Face Recognition. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP 2023), Lisbon, Portugal, pp. 897-904. [Short paper]
  4. Mehta A., Abdelaal M., Sheba M., and Herndon, N. (2022). Automated Neoclassical Vertical Canon Validation in Human Faces with Machine Learning. In Proceedings of the 11th International Conference on Data Science, Technology and Applications (DATA 2022), Lisbon, Portugal, pp. 461-467. [Short paper]
  5. Olufowobi K., and Herndon, N. (2022). Towards a Low-Cost Vision System for Real-Time Pavement Condition Assessment. In Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2022), Online Streaming, pp. 526-533. [Short paper]
  6. Gudivada, V.N., Herndon, N., and Rao, D. (2021). ISPeL: A topic dependency-driven system for personalized learning. In Proceedings of the 15th International Conference on Semantic Computing (ICSC 2021), Laguna Hills, CA, pp. 463-467.
  7. Sokolov M., and Herndon, N. (2021). Predicting Malware Attacks using Machine Learning and AutoAI. In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2021), Vienna, Austria, pp. 295–301. [Short paper]
  8. Sokolov M., Olufowobi K., and Herndon, N. (2020). Visual Spoofing in Content-Based Spam Detection. In Proceedings of the 13th International Conference on Security of Information and Networks (SINCONF 2020), Istanbul, Turkey, pp. 1-5. [Short paper, Best presentation award]
  9. Rao D.L., Pala V.R., Herndon, N., and Gudivada V.N. (2020). A Deep Learning Architecture for Corpus Creation for Telugu Language. In: Iyer B., Rajurkar A., Gudivada V. (eds) Applied Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 1155. Springer, Singapore.
  10. Herndon, N., Grau, E. S., Batra, I., Demurjian Jr., S. A., Vasquez-Gross, H. A., Staton, M. E., and Wegrzyn, J. L. (2016). CartograTree: Enabling Landscape Genomics for Forest Trees. In Proceedings of the Open Source Geospatial Research & Education Symposium (OGRS 2016), Perugia, Italy, pp. 1-7. [Short paper]
  11. Herndon, N., and Caragea, D. (2016). Ab initio Splice Site Prediction with Simple Domain Adaptation Classifiers. In Proceedings of the 7th International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2016), Rome, Italy, pp. 245-252. [Short paper]
  12. Roy, S., DeLoach, J., Li, Y., Herndon, N., Caragea, D., Ou, X., Ranganath, V. P., Li, H., and Guevara, N. (2015). Experimental Study with Real-world Data for Android App Security Analysis using Machine Learning. In Proceedings of the 2015 Annual Computer Security Applications Conference (ACSAC 2015), Los Angeles, CA, pp. 81-90. [Regular paper. Acceptance rate: 25%]
  13. Tangirala, K., Herndon, N., and Caragea, D. (2015). Community Detection-Based Feature Construction for Protein Sequence Classification. In Proceedings of the 11th International Symposium on Bioinformatics Research and Applications (ISBRA 2015), Norfolk, VA, pp. 331-342. [Regular paper. Acceptance rate: 35%]
  14. Li, H., Guevara, N., Herndon, N., and Caragea, D., Neppalli, K., Caragea, C., Squicciarini, A. C., Tapia, A. H. (2015). Twitter Mining for Disaster Response: A Domain Adaptation Approach. In Proceedings of the 12th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2015), Kristiansand, Norway. [Short paper. Acceptance rate: 70%]
  15. Herndon, N., and Caragea, D. (2015). An Evaluation of Self-training Styles for Domain Adaptation on the Task of Splice Site Prediction. In Proceedings of the 4th International Symposium on Network Enabled Health Informatics, Biomedicine and Bioinformatics (HI-BI-BI 2015), Paris, France, pp. 1042-1047. [Regular paper. Acceptance rate: 35%. Best paper award]
  16. Herndon, N., and Caragea, D. (2015). Domain Adaptation with Logistic Regression for the Task of Splice Site Prediction. In Proceedings of the 11th International Symposium on Bioinformatics Research and Applications (ISBRA 2015), Norfolk, VA, pp. 125-137. [Regular paper. Acceptance rate: 35%]
  17. Herndon, N., Tangirala, K., and Caragea, D. (2014). Predicting Protein Localization Using a Domain Adaptation Naive Bayes Classifier with Burrows Wheeler Transform Features. In Proceedings of the 6th IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2014), Belfast, UK, pp. 501-504. [Short paper. Acceptance rate: 38%]
  18. Herndon, N., and Caragea, D. (2014). Empirical Study of Domain Adaptation with Naive Bayes on the Task of Splice Site Prediction. In Proceedings of the 5th International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2014), Angers, France, pp. 57-67. [Regular paper. Acceptance rate: 14%. Nominated for best paper award]
  19. Herndon, N., and Caragea, D. (2013). Naive Bayes Domain Adaptation for Biological Sequences. In Proceedings of the 4th International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2013), Barcelona, Spain, pp. 62-70. [Regular paper. Acceptance rate: 10%. Nominated for best student paper award]
  20. Vert, G., and Herndon, N. (2006). Secure Simultaneous Search of Distributed, Heterogeneous Bioinformatics Databases. In Proceedings of the 2006 International Conference on Security & Management (SAM 2006), Las Vegas, NV, USA, pp. 384-389.