Publication

You can also find my articles on my Google Scholar profile.

* Indicates equal contribution.

In the Pipeline

  1. Asiaee*, A., Abrams*, Z. B., Nakayiza, S., Sampath, D., & Coombes, K. R. (2019). Identification and comparison of genes differentially regulated by transcription factors and miRNAs.
  2. Asiaee, A., Oymak, S., Coombes, K. R., & Banerjee, A. High Dimensional Data Enrichment: Interpretable, Fast, and Data-Efficient. Under Review In.
  3. Abrams, Z. B., Joglekar, A., Gershkowitz, G. R., Sinicropiyao, S., Asiaee, A., Carbone, D. P., & Coombes, K. R. Personalized Transcriptomics: Selecting Drugs Based on Gene Expression Profiles. Under Review.

Applications in Biology

  1. Asiaee*, A., Abrams*, Z. B., Nakayiza, S., Sampath, D., & Coombes, K. R. (2020). Explaining Gene Expression Using Twenty-One MicroRNAs. Journal of Computational Biology, Forthcoming.
  2. Asiaee*, A., Abrams*, Z. B., Nakayiza, S., Sampath, D., & Coombes, K. R. (2019). Explaining Gene Expression Using Twenty-One MicroRNAs. In Computational Biology Workshop at ICML 2019.
  3. Cho, M. H., Asiaee*, A., & Kurtek, S. (2019). Elastic Statistical Shape Analysis of Biological Structures with Case Studies: A Tutorial. Bulletin of Mathematical Biology, 81(7), 2052–2073.
  4. Abrams, Z. B., Zucker, M., Wang, M., Asiaee Taheri, A., Abruzzo, L. V., & Coombes, K. R. (2018). Thirty biologically interpretable clusters of transcription factors distinguish cancer type. BMC Genomics, 19(1), 738.

High Dimensional Statistics

  1. Asiaee, A., Oymak, S., Coombes, K. R., & Banerjee, A. (2019). Data Enrichment: Multi-task Learning in High Dimension with Theoretical Guarantees. In Adaptive and Multi-Task Learning Workshop at ICML 2019.
  2. Asiaee T., A., Chaterjee, S., & Banerjee, A. (2016). High Dimensional Structured Estimation with Noisy Designs. In 16th SIAM International Conference on Data Mining (SDM) (pp. 801–809). SIAM.

Social Network Analysis

  1. Golnari*, G., Asiaee T.*, A., Banerjee, A., & Zhang, Z.-L. (2015). Revisiting Non-Progressive Influence Models: Scalable Influence Maximization in Social Networks. In 31st Conference on Uncertainty in Artificial Intelligence (UAI) (pp. 316–325).
  2. Asiaee T., A., Afshar, M., & Asadpour, M. (2013). Influence maximization for informed agents in collective behavior. In Distributed Autonomous Robotic Systems (pp. 389–402). Springer.
  3. Asiaee T., A., Tepper, M., Banerjee, A., & Sapiro, G. (2012). If you are happy and you know it... tweet. In 21st ACM international conference on Information and knowledge management (CIKM) (pp. 1602–1606). ACM.

General Machine Learning

  1. Asiaee T., A., Goel, H., Gosh, S., Yegneswaran, V., & Banerjee, A. (2018). Time Series Deinterleaving of DNS Traffic. In 1st Deep Learning and Security Workshop (DLS).