(Conference) Design and Analysis of Experiments Conference 2024 will be hosted by Department of Statistics at Virginia Tech on May 15-17, 2024.

(Workshop) IMSI Long Program on Uncertainty Quantification and AI for Complex Systems will be hosted by IMSI at Chicago, IL on March 3 -May 23, 2025.

(July 2023) Jiayi Lian defended his PhD dissertation. Congratulations, Jiayi!

(April 2023) VT-SAIL has received an NSF funding on Modeling and Active Learning of Quantitative-Sequence Experiments. Congratulations!

(Janruary 2023) VT-SAIL has received a CCI funding on Enhancing Human Confidence and Trust in Deep Learning Models. Congratulations!

(Conference) ASA/IMS Spring Research Conference 2023 will take place at Banff Center on May 24-26, 2023.

(CFP) Special Issue of “Design and Analysis of Experiments for Data Science” at New England Journal of Statistics in Data Science (NEJSDS)

(September 2022) Qing Guo has been awarded the Amazon Fellowship. Congratulations, Qing Guo!

(August 2022) Yanran Wei defended her PhD dissertation. Congratulations, Yanran!

(June 2022) Yueyao Wang defended her PhD dissertation. Congratulations, Yueyao!

(June 2022) Xinwei Deng has been promoted to the full professor. Congratulations, Xinwei!

(February 2022) Zhihao Hu defended his PhD dissertation. Congratulations, Zhihao!

(Janruary 2022) Yueyao Wang won the ASA SPES+QP Best Student Paper Award. Congratulations, Yueyao!

(Janruary 2022) VT-SAIL has received VT-COS research equipment grant for building flexible small-scale GPU computing power. Congratulations!

(December 2021) Xinwei Deng has been awarded the Data Science Faculty Fellowship. Congratulations, Xinwei!

(June 2021) Li Xu defended his PhD dissertation. Congratulations, Li!

(June 2021) VT-SAIL has received CoVA CCI Cybersecurity research funding for assessment of the federated AI algorithms in cyber-physical systems. Congratulations!

(May 2021) VT-SAIL has received the Commonwealth Cyber Initiative (CCI) funding for experimental research in CCI Testbeds. Congratulations!

(May 2020) Yili Hong has been promoted to the full professor. Congratulations, Yili!

(January 2020) VT-SAIL has received an NSF grant to investigate the robustness of AI algorithms. Congratulations!

(December 2019) Sumin Shen defended his PhD dissertation. Congratulations, Sumin!

(August 2019) Zhongnan Jin defended his PhD dissertation. Congratulations, Zhongnan!

(July 2019) Maggie Mao defended her PhD dissertation. Congratulations, Maggie!

(April 2019) VT-SAIL Lab is launched!

Xiao, Q., Wang, Y., Mandal, A., and Deng, X. (2023). Modeling and Active Learning for Experiments with Quantitative-Sequence Factors, Journal of the American Statistical Association, in press.

Wang, Y., Xu, L., Hong, Y., Pan, R., Chang, T., Lux, T., Bernard, J., Watson, L., and Cameron, K. (2023). Design Strategies and Approximation Methods for High-Performance Computing Variability Management, Journal of Quality Technology , 55, 88-103.

Liu, X., Hu, Z., Kuhlman, C. J. and Deng, X. (2023). Learning Common Knowledge Networks Via Exponential Random Graph Models, 11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2023) (Acceptance rate 17%).

Shen, S., Mao, H., Zhang, Z., Chen, Z., Nie, K., and Deng, X. (2023). Clustering-based Imputation for Dropout Buyers in Large-scale Online Experimentation, New England Journal of Statistics in Data Science, accepted.

Liu, X., Hu, Z., Deng, X., and Kuhlman, C. J. (2023). A Calibration Model for Bot-Like Behaviors in Agent-Based Anagram Game Simulation, Winter Simulation Conference (WSC 2023), accpeted.

Lian, J., Choi, K., Veeramani, B., Hu, A., Freeman, L., Bowen, E., and Deng, X. (2023). Do-AIQ: A Design-of-Experiment Approach to Quality Evaluation of AI Mislabel Detection Algorithm, Journal of Quality Technology , submitted.

Guo, Q., Chen, J., Wang, D., Yang, Y., Deng, X., Huang J., Carin, L., Tao, C. and Li, F. (2022). Tight Mutual Information Estimation with Contrastive Fenchel-Legendre Optimization, Advances in Neural Information Processing Systems (NeurIPS 2022), accepted.

Hong, Y., Min, J., King, C.B. and Meeker, W. Q. (2022). Reliability Analysis of Artificial Intelligence Systems Using Recurrent Events Data from Autonomous Vehicles, Journal of the Royal Statistical Society Series C (Applied Statistics), in press.

Kenett, R. S., Gotwalt, C., Freeman, L., and Deng, X. (2022). Self-Supervised Cross Validation using Data Generation Structure, Applied Stochastic Models in Business and Industry, accepted.

Hong, Y., Lian, J., Xu, L., Min, J., Wang, Y., Freeman, L., and Deng, X. (2022). Statistical Perspectives on Reliability of Artificial Intelligence Systems, Quality Engineering, accepted.

Liu, X., Hu, Z., Deng, X., and Kuhlman, C. J. (2022). A Bayesian Uncertainty Quantification Approach for Agent-Based Modeling of Networked Anagram Games, Winter Simulation Conference (WSC 2022), in press.

Liu, X., Hu, Z., Deng, X., and Kuhlman, C. J. (2022). Bayesian Approach to Uncertainty Visualization of Heterogeneous Behaviors in Modeling Networked Anagram Games, The International Conference on Complex Networks and their Applications (CNA 2022), in press.

Hu, Z., Deng, X., Kuhlman, C. J. (2021). Versatile Uncertainty Quantification of Contrastive Behaviors for Modeling Networked Anagram Games, The International Conference on Complex Networks and their Applications (CNA 2021), in press.

Hu, Z., Deng, X., Kuhlman, C. J. (2021). An Uncertainty Quantification Approach for Agent-Based Modeling of Human Behavior in Networked Anagram Games, Winter Simulation Conference (WSC 2021), in press.

Shojaee, P., Zeng, Y., Chen, X., Jin, R., Deng, X., and Zhang, C. (2021). Deep Neural Network Pipelines for Multivariate Time Series Classification in Smart Manufacturing, The 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS), in press.

Cai, X., Xu, L., Lin, C. D., Hong, Y., and Deng, X. (2021). Sequential Design of Computer Experiments with Quantitative and Qualitative Factors in Applications to HPC Performance Optimization, SIAM Journal of Uncertainty Quantification, revision submitted.

Lian, J., Freeman, L., Hong, Y., and Deng, X. (2020). Investigating the Robustness of Artificial Intelligent Algorithms with Mixture Experiments, Journal of Quality Technology, submitted.

Xie, W., and Deng, X. (2020). Scalable Algorithms for the Sparse Ridge Regression, SIAM Journal on Optimization, in press.

Xu, L., Wang, Y., Lux, T., Chang, T., Bernard, J., Li, B., Hong, Y., Watson, L., and Cameron, K. (2020). Modeling I/O Performance Variability in High-Performance Computing Systems using Mixture Distributions, Journal of Parallel and Distributed Computing, 139, 87-98.

Mao, H., Deng, X., Jiang, H., Shi, L., Li, H., Tuo, L., and Guo, F. (2020). Driving Safety Assessment for Ride-hailing Drivers, Accident Analysis and Prevention, in press.

Kang, X., Chen, X., Jin, R., Wu, H., and Deng, X. (2020). Multivariate Regression of Mixed Responses for Evaluation of Visualization Designs, IISE Transactions, in press.

Xie, Y., Xu L., Li, J., Deng, X., Hong, Y., and Kolivras, K. N. (2019). Spatial Variable Selection via Elastic Net with an Application to Virginia Lyme Disease Case Data, Journal of the American Statistical Association, 114(528), 1466-1480.

Cedeno-Mieles, V., Hu, Z., Deng, X., Ren, Y., et al. (2019). Networked Experiments and Modeling for Producing Collective Identity in a Group of Human Subjects Using an Iterative Abduction Framework, Social Network Analysis and Mining, 10, 11.

Cameron, K., Anwar, A., Cheng, Y., Xu, L., Li, B., Ananth, U., Bernard, J., Jearls, C., Lux, T., Hong, Y., Watson, L., and Butt, A. (2019). MOANA: Modeling and Analyzing HPC I/O Variability, IEEE Transactions on Parallel and Distributed Systems, 30(8), 1843-1856.

Shen, S., Zhang, Z., and Deng, X. (2019). On Design and Analysis of Funnel Testing Experiments in Webpage Optimization, Journal of Statistical Theory and Practice, 14, 3.

Cedeno-Mieles, V., Hu, Z., Deng, X., Ren, Y., et al. (2019). Mechanistic and Data-Driven Agent-Based Models to Explain Human Behavior in Web-Based Group Anagrams Games, 11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019) (Acceptance rate 14%).

Cadena, J., Basak, A., Vullikanti, A., and Deng, X. (2018). Graph Scan Statistics with Uncertainty, 32nd AAAI Conference on Artificial Intelligence (AAAI-18), 2771-2778. (Acceptance rate 25%).

Ren, Y., Cedeno-Mieles, V., Hu, Z., Deng, X., et al. (2018). Generative Modeling of Human Behavior and Social Interactions Using Abductive Analysis, 10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2018), 413-420. (Acceptance rate 15%).

Here is a blog of Data Thinking at VT.