Doan, K. D., Lao, Y., & Li, P. (2021). Backdoor Attack with Imperceptible Input and Latent Modification. Thirty-Fifth Conference on Neural Information Processing Systems.

Doan, K. D., Lao, Y., Zhao, W., & Li, P. (2021). LIRA: Learnable, Imperceptible and Robust Backdoor Attacks. 2021 International Conference on Computer Vision.

Doan, K. D., Manchanda, S., Mahapatra, S., & Reddy, C. K. (2021). Interpretable Graph Similarity Computation via Differentiable Optimal Alignment of Node Embeddings. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 665–674.

Doan, K. D., & Reddy, C. K. (2020). Efficient Implicit Unsupervised Text Hashing Using Adversarial Autoencoder. Proceedings of The Web Conference 2020, 684–694.

Doan, K. D., Manchanda, S., Wang, F., Selvaraj, S. K., Bhowmik, A., & Reddy, C. K. (2020). Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space. ArXiv Preprint ArXiv:2003.11774.

Doan, K. D., Manchanda, S., Badirli, S., & Reddy, C. K. (2020). Image Hashing by Minimizing Discrete Component-wise Wasserstein Distance. ArXiv Preprint ArXiv:2003.00134.

Manchanda, S., Doan, K. D., Yadav, P., & Selvaraj, S. K. (2020). Regression via implicit models and optimal transport cost minimization. ArXiv Preprint ArXiv:2003.01296.

Badirli, S., Liu, X., Xing, Z., Bhowmik, A., Doan, K. D., & Selvaraj, S. K. (2020). Gradient boosting neural networks: Grownet. ArXiv Preprint ArXiv:2002.07971.

Manchanda, S., Yadav, P., Doan, K. D., & Selvaraj, S. K. (2019). Targeted display advertising: the case of preferential attachment. Proceedings of the 2019 IEEE International Conference on Big Data, 1868–1877.

Doan, K. D., Yadav, P., & Reddy, C. K. (2019). Adversarial Factorization Autoencoder for Look-Alike Modeling. Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2803–2812.

Doan, K. D., Yang, G., & Reddy, C. K. (2019). An Attentive Spatio-Temporal Neural Model for Successive Point of Interest Recommendation. Proceedings of the 2019 Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 346–358.

Kuo, K.-S., Oloso, A. O., Rilee, M. L., Doan, K. D., Clune, T. L., & Yu, H. (2017). Quest for Value in Big Earth Data. EGU General Assembly Conference Abstracts, 8413.

Doan, K. D., Oloso, A. O., Kuo, K.-S., Clune, T. L., Yu, H., Nelson, B., & Zhang, J. (2016). Evaluating the impact of data placement to spark and SciDB with an Earth Science use case. Proceedings of the 2016 IEEE International Conference on Big Data, 341–346.

Kuo, K.-S., Oloso, A., Doan, K. D., Clune, T. L., & Yu, H. (2016). Implications of data placement strategy to Big Data technologies based on shared-nothing architecture for geosciences. 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 7605–7607.

Clune, T., Kuo, K.-S., Doan, K. D., & Oloso, A. (2015). SciDB versus Spark: A preliminary comparison based on an Earth science use case. AGU Fall Meeting Abstracts, 2015.

Doan, K. D., Oloso, A., Kuo, K.-S., Clune, T. L., & Bayesics, L. L. C. (2014). Performance comparison of big-data technologies in locating intersections in satellite ground tracks. Proceedings of the 2014 ASE BigData/SocialInformatics/PASSAT/BioMedCom Conference.

Kuo, K., Clune, T., Ramachandran, R., Rushing, J., Fekete, G., Lin, A., Doan, K. D., Oloso, A. O., & Duffy, D. (2013). A Demonstration of Big Data Technology for Data Intensive Earth Science. AGU Fall Meeting Abstracts, 2013.