My research interests encompass methodological studies for machine learning, statistical computing, graphical models, and Bayesian inference, with a specific focus on biomarker detection in imaging genomics, machine intelligence, and precision medicine. I aim to push the boundaries of applied machine learning and establish a strong connection between genomic studies and medical imaging, employing statistical modeling techniques to enhance biomarker detection. My motivation lies in uncovering relationships between molecular signatures and imaging phenotypes to identify crucial biomarkers, providing valuable insights into complex diseases. I also plan to advance applied machine learning by developing scalable methods for large-scale data, exploring automated techniques for specific tasks, and leveraging unsupervised and transfer learning to enhance model performance. Additionally, I intend to focus on varying-coefficient varying-structure (VCVS) graphical models in machine learning to broaden their applications and capabilities, contributing to the field's methodological studies and practical advancements in precision medicine.

* = authors contributed equally, ✉︎ = corresponding author

Zeya Wang, Veera Baladandayuthapan, Ahmed O Kaseb, Hesham M Amin, Manal M Hassan, Wenyi Wang, Jeffrey S Morris (2022). Bayesian Edge Regression in Undirected Graphical Models to Characterize Interpatient Heterogeneity in Cancer. Journal of the American Statistical Association

Zeya Wang✉︎, Yang Ni, Baoyu Jing, Deqing Wang, Hao Zhang, Eric Xing (2021). DNB: A Joint Learning Framework for Deep Bayesian Nonparametric Clustering. IEEE Transactions on Neural Networks and Learning Systems

Jieli Zhou, Baoyu Jing, Zeya Wang✉︎, Hongyi Xin, Hanghang Tong (2021). Soda: Detecting covid-19 in chest x-rays with semi-supervised open set domain adaptation. IEEE/ACM Transactions on Computational Biology and Bioinformatics

Shreya Kadambi*, Zeya Wang*✉︎, Eric Xing (2021). WGAN domain adaptation for the joint optic disc-and-cup segmentation in fundus images. International Journal of Computer Assisted Radiology and Surgery

Jeffrey S Morris, Manal M Hassan, Ye Emma Zohner, Zeya Wang, Lianchun Xiao, Asif Rashid, Abedul Haque, Reham Abdel‐Wahab, Yehia A Mohamed, Karri L Ballard, Robert A Wolff, Bhawana George, Liang Li, Genevera Allen, Michael Weylandt, Donghui Li, Wenyi Wang, Kanwal Raghav, James Yao, Hesham M Amin, Ahmed Omar Kaseb (2020). HepatoScore‐14: Measures of biological heterogeneity significantly improve prediction of hepatocellular carcinoma risk. Hepatology

Yang Ni, David Jones, Zeya Wang (2020). Consensus Variational and Monte Carlo Algorithms for Bayesian Nonparametric Clustering. IEEE International Conference on Big Data (IEEE BigData)

Zeya Wang, Baoyu Jing, Yang Ni, Nanqing Dong, Pengtao Xie, Eric Xing (2020). Adversarial domain adaptation being aware of class relationships. European Conference on Artificial Intelligence (ECAI) (Oral Presentation)

Baoyu Jing, Zeya Wang, Eric Xing (2019). Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-ray Reports. Annual Meeting of the Association for Computational Linguistics (ACL)

Zeya Wang, Nanqing Dong, Sean D Rosario, Min Xu, Pengtao Xie, Eric Xing (2019). Ellipse Detection of Optic Disc-and-Cup Boundary in Fundus Images. IEEE 16th International Symposium on Biomedical Imaging (ISBI)

Zeya Wang, Shaolong Cao, Jeffrey S Morris, Jaeil Ahn, Rongjie Liu, Svitlana Tyekucheva, Fan Gao, Bo Li, Wei Lu, Ximing Tang, Ignacio I Wistuba, Michaela Bowden, Lorelei Mucci, Massimo Loda, Giovanni Parmigiani, Chris C Holmes, Wenyi Wang (2018). Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration. iScience (Cell Press)

Zeya Wang, Nanqing Dong, Wei Dai, Sean D Rosario, Eric Xing (2018). Classification of Breast Cancer Histopathological Images using Convolutional Neural Networks with Hierarchical Loss and Global Pooling. International Conference Image Analysis and Recognition (ICIAR) (Oral Presentation)

Aliaksei Z Holik, Charity W Law, Ruijie Liu, Zeya Wang, Wenyi Wang, Jaeil Ahn, Marie-Liesse Asselin-Labat, Gordon K Smyth, Matthew E Ritchie (2017). RNA-seq mixology: designing realistic control experiments to compare protocols and analysis methods. Nucleic acids research