Assistant Professor, Department of Statistics

University of Kentucky

I earned my Ph.D. in Statistics from Rice University. My professional journey includes serving as a Senior Machine Learning Engineer at TikTok, where I specialized in predictive modeling, video understanding, and anomaly detection. Additionally, I contributed as a Research Scientist at Petuum Inc., founded by Carnegie Mellon University, focusing on machine learning and medical imaging. I have also held a significant role as a Postdoctoral Research Fellow at the University of Texas MD Anderson Cancer Center, where I delved into statistical modeling on omics data.

My research interests encompass methodological studies for machine learning, statistical computing, graphical models, deep learning, and Bayesian inference, with a specific focus on machine intelligence, precision medicine, and biomarker detection in imaging genomics.

Email: Zeya.Wang@uky.edu; Personal Email: zw17.rice@gmail.com

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Professional Experience

• Assistant Professor, University of Kentucky, 2023 - Present

• Machine Learning Engineer, TikTok, 2021 - 2023

• Data Scientist, Petuum, 2017 - 2021

• Postdoc, UT MD Anderson Cancer Center, 2017

• Visiting Postdoc, Wellcome Sanger Institute, 2017

• Research Intern, IBM Research, 2016

• Graduate Research Assistant, UT MD Anderson Cancer Center, 2013 - 2017

• Graduate Student, Rice University, 2012 - 2017

Publications

Journal Publications

* = 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

• 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)

• 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

• Malin Song, Wanping Zheng, Zeya Wang (2016). Environmental efficiency and energy consumption of highway transportation systems in China. International Journal of Production Economics

• Malin Song, Yaqin Song, Huayin Yu, Zeya Wang (2013). Calculation of China’s environmental efficiency and relevant hierarchical cluster analysis from the perspective of regional differences. Mathematical and Computer Modelling

• Malin Song, Linling Zhang, Qingxian An, Zeya Wang, Zhen Li (2013). Statistical analysis and combination forecasting of environmental efficiency and its influential factors since China entered the WTO. Journal of Cleaner Production

• Malin Song, Qingxian An, Wei Zhang, Zeya Wang, Jie Wu (2012). Environmental efficiency evaluation based on data envelopment analysis: a review. Renewable and Sustainable Energy Reviews

Conference Publications

• 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)

• Wei Dai, Nanqing Dong, Zeya Wang, Xiaodan Liang, Hao Zhang, Eric Xing (2018). SCAN: Structure correcting adversarial network for organ segmentation in chest X-rays. International Workshop on Deep Learning in Medical Image Analysis(DLMIA)

• Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric Xing (2018). Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-slide Images. International Workshop on Deep Learning in Medical Image Analysis (DLMIA)

• Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric Xing (2018). Unsupervised domain adaptation for automatic estimation of cardiothoracic ratio. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)

• 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)

Unrefereed Manuscripts

• Zeya Wang, Chenglong Ye (2024). Deep Clustering Evaluation: How to Validate Internal Clustering Validation Measures.

• Hao Zhang, Peng Wu, Zhijie Deng, Christy Li, Qirong Ho, Aurick Qiao, Zeya Wang, Eric Xing (2021). Autodist: A Composable and Automated Synchronization System for Distributed Deep learning.

• Shaolong Cao*, Zeya Wang*, Fan Gao, Jingxiao Chen, Feng Zhang, Daniel E Frigo, Eleni Efstathiou, Scott Kopetz, Wenyi Wang (2019). An R Implementation of Tumor-Stroma-Immune Transcriptome Deconvolution Pipeline using DeMixT.

Contributed Softwares

• DeMixT: A Computational Tool for Cell Type-specific Deconvolution of Heterogeneous Tumor Samples Using Expression Data from RNAseq or Microarray Platforms

• AutoDist: A Composable and Automated Synchronization System for Distributed Deep Learning

• Tuun: A Toolkit for Efficient Hyperparameter Tuning via Uncertainty Modeling, with a Focus on Flexible Model choice, Scalability, and Use in Distributed Settings.

Academic Activities

Program Committee Members or Reviewers for:

• Journals: Statistica Sinica, Annals of Applied Statistics, Journal of the Royal Statistical Society: Series C, Journal of Applied Statistics, Artificial Intelligence Review, Knowledge and Information Systems, IEEE Transactions on Cybernetics, BMC Genomics, Scientific Report, PLOS One, Computer Methods and Programs in Biomedicine, Information Sciences, Journal of Digital Imaging, Journal of Cleaner Production, Mathematical Biosciences, Chemometrics and Intelligent Laboratory Systems, Computational Biology and Chemistry

• Conferences: The Conference on Neural Information Processing Systems (NeurIPS), The AAAI Conference on Artificial Intelligence (AAAI), The Conference on Empirical Methods in Natural Language Processing (EMNLP) , ACM International Conference on Web Search and Data Mining (WSDM), International Symposium on Bioinformatics Research and Applications (ISBRA), IEEE International Conference on Bioinformatics and Biomedicine (BIBM), International Conference On Intelligent Computing

Teaching Experience:

• Instructor of STA 695: Statistical Machine Learning and Predictive Modeling, Fall 2023, University of Kentucky
• Instructor of STA 652: Advanced Statistical Models, Spring 2024, University of Kentucky
• TA of STAT 581: Mathematical Probability I, Fall 2014, Rice University

Alumni Students:

• Xinrong Hu, Graduate Intern (2022) -> Machine Learning Scientist @ TikTok

• Alexander Gurung, Graduate Intern (2021) -> AI Resident @ Facebook

Social Activities

I’m also a soccer enthusiast and have played striker for amateur teams like Phoenix FC, Riverrats FC, and Partizan Pittsburgh FC in the Greater Pittsburgh Soccer League.