HR job title
- Professor
- Contact Info
- 1 979 458 2343
- Websites
Ding, Yu Professor
Positions
Dr. Yu Ding is the Mike and Sugar Barnes Professor of Industrial & Systems Engineering, Professor of Electrical & Computer Engineering, Associate Director for Research Engagement of Texas A&M Institute of Data Science (TAMIDS), and a Faculty Affiliate with Texas A&M Energy Institute and TEES Institute of Manufacturing Systems. Dr. Ding serves on the Executive Committee of Texas A&M TRIPODS Research Institute for Foundations of Interdisciplinary Data Science (FIDS). Dr. Ding's research interest is in data and quality science. Dr. Ding is the Editor-in-Chief of IISE Transactions (formerly IIE Transactions) for the term of 2021-2024. He previously served as an Editor for IEEE Transactions on Automation Science and Engineering and a Senior Editor for INFORMS Journal on Data Science. He also served as a Department Editor for IISE Transactions from 2005 to 2020, as an Associate Editor for IEEE Transactions on Automation Science and Engineering from 2006 to 2009, and a special issue Guest Co-Editor for Technometrics from 2013 to 2015.
- Overview
- Publications
- Research
- Teaching
- Works By Students
- Background
- Contact
- Other
- View All
Overview
Publications
selected publications
-
academic article
-
Wang, Y., Ding, Y. u., & Shahrampour, S.
(2023).
TAKDE: Temporal Adaptive Kernel Density Estimator for Real-Time Dynamic Density Estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence.
PP(99), 1-13.
-
Ding, Y. u.
(2023).
Editorial: Perspectives of ISE/OR researchers. IISE TRANSACTIONS.
55(1), 1-1.
-
Prakash, A., Tuo, R., & Ding, Y. u.
(2023).
The Temporal Overfitting Problem with Applications in Wind Power Curve Modeling. Technometrics.
65(1), 70-82.
-
Prakash, A., Lee, S. Y., Liu, X., Liu, L., Mallick, B., & Ding, Y. u.
(2023).
A Bayesian hierarchical model to understand the effect of terrain on wind turbine power curves. PP(99), 1-10.
-
Ahmed, I., Jun, M., & Ding, Y. u.
(2022).
A Spatio-Temporal Track Association Algorithm Based on Marine Vessel Automatic Identification System Data. IEEE Transactions on Intelligent Transportation Systems.
23(11), 20783-20797.
-
Xie, Y., Ding, Y. u., & Ji, S.
(2022).
Augmented Equivariant Attention Networks for Microscopy Image Transformation. IEEE Transactions on Medical Imaging.
41(11), 3194-3206.
-
Jin, S., Tuo, R., Tiwari, A., Bukkapatnam, S., Aracne-Ruddle, C., Lighty, A., Hamza, H., & Ding, Y. u.
(2022).
Hypothesis tests with functional data for surface quality change detection in surface finishing processes. IISE TRANSACTIONS.
55(9), 1-17.
-
Latiffianti, E., Ding, Y. u., Sheng, S., Williams, L., Morshedizadeh, M., & Rodgers, M.
(2022).
Analysis of leading edge protection application on wind turbine performance through energy and power decomposition approaches. Wind Energy.
25(7), 1203-1221.
-
Prakash, A., Tuo, R., & Ding, Y. u.
(2022).
Gaussian Process-Aided Function Comparison Using Noisy Scattered Data. Technometrics.
64(1), 92-102.
-
Shin, Y. E., Zhou, L., & Ding, Y. u.
(2022).
Joint Estimation of Monotone Curves via Functional Principal Component Analysis. Computational Statistics and Data Analysis.
166, 107343-107343.
-
Tuo, R., He, S., Pourhabib, A., Ding, Y. u., & Huang, J. Z.
(2021).
A Reproducing Kernel Hilbert Space Approach to Functional Calibration of Computer Models. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION.
1-15.
-
Ezzat, A. A., Liu, S., Hochbaum, D. S., & Ding, Y. u.
(2021).
A Graph-Theoretic Approach for Spatial Filtering and Its Impact on Mixed-Type Spatial Pattern Recognition in Wafer Bin Maps. IEEE Transactions on Semiconductor Manufacturing.
34(2), 194-206.
-
Ding, Y. u., Kumar, N., Prakash, A., Kio, A. E., Liu, X., Liu, L., & Li, Q.
(2021).
A case study of space-time performance comparison of wind turbines on a wind farm. Renewable Energy.
171, 735-746.
-
Ahmed, I., Hu, X. B., Acharya, M. P., & Ding, Y. u.
(2021).
Neighborhood Structure Assisted Non-negative Matrix Factorization and Its Application in Unsupervised Point-wise Anomaly Detection. JOURNAL OF MACHINE LEARNING RESEARCH.
22.
-
Ezzat, A. A., Tang, J., & Ding, Y. u.
(2020).
A model-based calibration approach for structural fault diagnosis using piezoelectric impedance measurements and a finite element model. Structural Health Monitoring: an international journal.
19(6), 1839-1855.
-
Qian, Y., Xu, J., Drummy, L. F., & Ding, Y. u.
(2020).
Effective Super-Resolution Methods for Paired Electron Microscopic Images. IEEE Transactions on Image Processing.
29, 7317-7330.
-
Qian, Y., Huang, J. Z., Park, C., & Ding, Y. u.
(2019).
FAST DYNAMIC NONPARAMETRIC DISTRIBUTION TRACKING IN ELECTRON MICROSCOPIC DATA. Annals of Applied Statistics.
13(3), 1537-1563.
-
Ezzat, A. A., Jun, M., & Ding, Y. u.
(2019).
SPATIO-TEMPORAL SHORT-TERM WIND FORECAST: A CALIBRATED REGIME-SWITCHING METHOD. Annals of Applied Statistics.
13(3), 1484-1510.
-
Ahmed, I., Dagnino, A., & Ding, Y. u.
(2019).
Unsupervised Anomaly Detection Based on Minimum Spanning Tree Approximated Distance Measures and Its Application to Hydropower Turbines. IEEE Transactions on Automation Science and Engineering.
16(2), 654-667.
-
Park, C., & Ding, Y. u.
(2019).
Automating material image analysis for material discovery. MRS Communications.
9(2), 545-555.
-
Ezzat, A. A., Jun, M., & Ding, Y. u.
(2018).
Spatio-temporal asymmetry of local wind fields and its impact on short-term wind forecasting. IEEE Transactions on Sustainable Energy.
9(3), 1437-1447.
-
Shin, Y. E., Ding, Y. u., & Huang, J. Z.
(2018).
COVARIATE MATCHING METHODS FOR TESTING AND QUANTIFYING WIND TURBINE UPGRADES. Annals of Applied Statistics.
12(2), 1271-1292.
-
Hwangbo, H., Johnson, A. L., & Ding, Y. u.
(2018).
Spline model for wake effect analysis: Characteristics of a single wake and its impacts on wind turbine power generation. IISE TRANSACTIONS.
50(2), 112-125.
-
Dong, L., Li, X., Qian, Y., Yu, D., Zhang, H., Zhang, Z., & Ding, Y. u.
(2018).
Quantifying Nanoparticle Mixing State to Account for Both Particle Location and Size Effects (vol 59, pg 391, 2017). Technometrics.
60(1), 133-133.
-
Niu, B., Hwangbo, H., Zeng, L. i., & Ding, Y. u.
(2018).
Evaluation of alternative power production efficiency metrics for offshore wind turbines and farms. Renewable Energy.
128, 81-90.
-
Hwangbo, H., Johnson, A., & Ding, Y. u.
(2017).
A production economics analysis for quantifying the efficiency of wind turbines. Wind Energy.
20(9), 1501-1513.
-
Dong, L., Li, X., Yu, D., Zhang, H., Zhang, Z., Qian, Y., & Ding, Y. u.
(2017).
Quantifying Nanoparticle Mixing State to Account for Both Location and Size Effects. Technometrics.
59(3), 391-403.
-
Qian, Y., Huang, J. Z., & Ding, Y. u.
(2017).
Identifying multi-stage nanocrystal growth using in situ TEM video data. IISE TRANSACTIONS.
49(5), 532-543.
-
Hwangbo, H., Johnson, A. L., & Ding, Y. u.
(2017).
Power Curve Estimation: Functional Estimation Imposing the Regular Ultra Passum Law
-
Hwangbo, H., Ding, Y. u., Eisele, O., Weinzierl, G., Lang, U., & Pechlivanoglou, G.
(2017).
Quantifying the effect of vortex generator installation on wind power production: An academia-industry case study. Renewable Energy.
113, 1589-1597.
-
Wang, Y., Moreno-Centeno, E., & Ding, Y. u.
(2017).
Matching Misaligned Two-Resolution Metrology Data. 14(1), 222-237.
-
Yanjun Qian, .., Huang, J. Z., Xiaodong Li, .., & Yu Ding.
(2016).
Robust Nanoparticles Detection From Noisy Background by Fusing Complementary Image Information. IEEE Transactions on Image Processing.
25(12), 5713-5726.
-
Pourhabib, A., Huang, J. Z., & Ding, Y. u.
(2016).
Short-Term Wind Speed Forecast Using Measurements From Multiple Turbines in A Wind Farm. Technometrics.
58(1), 138-147.
-
Pourhabib, A., Mallick, B. K., & Ding, Y. u.
(2015).
Absent Data Generating Classifier for Imbalanced Class Sizes. JOURNAL OF MACHINE LEARNING RESEARCH.
16, 2695-2724.
-
Lee, G., Ding, Y. u., Xie, L. e., & Genton, M. G.
(2015).
A kernel plus method for quantifying wind turbine performance upgrades. Wind Energy.
18(7), 1207-1219.
-
Pourhabib, A., Huang, J. Z., Wang, K., Zhang, C., Wang, B., & Ding, Y. u.
(2015).
Modulus prediction of buckypaper based on multi-fidelity analysis involving latent variables. IIE Transactions.
47(2), 141-152.
-
Perez, E., Ntaimo, L., & Ding, Y. u.
(2015).
Multi-component wind turbine modeling and simulation for wind farm operations and maintenance. SIMULATION.
91(4), 360-382.
-
Lee, G., Ding, Y. u., Genton, M. G., & Xie, L. e.
(2015).
Power Curve Estimation With Multivariate Environmental Factors for Inland and Offshore Wind Farms. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION.
110(509), 56-67.
-
Chen, Y., Ding, Y. u., Joseph, V. R., & Nair, V.
(2015).
Untitled. Technometrics.
57(3), 303-304.
-
Pourhabib, A., Liang, F., & Ding, Y. u.
(2014).
Bayesian site selection for fast Gaussian process regression. IIE Transactions.
46(5), 543-555.
-
Lee, G., Byon, E., Ntaimo, L., & Ding, Y. u.
(2013).
BAYESIAN SPLINE METHOD FOR ASSESSING EXTREME LOADS ON WIND TURBINES. 7(4), 2034-2061.
-
Bansal, M., Kianfar, K., Ding, Y. u., & Moreno-Centeno, E.
(2013).
Hybridization of Bound-and-Decompose and Mixed Integer Feasibility Checking to Measure Redundancy in Structured Linear Systems. 10(4), 1151-1157.
-
Li, C., Gaukler, G. M., & Ding, Y. u.
(2013).
Using container inspection history to improve interdiction logistics for illicit nuclear materials. Naval Research Logistics.
60(6), 433-448.
-
Konomi, B. A., Dhavala, S. S., Huang, J. Z., Kundu, S., Huitink, D., Liang, H., Ding, Y. u., & Mallick, B. K.
(2013).
BAYESIAN OBJECT CLASSIFICATION OF GOLD NANOPARTICLES. Annals of Applied Statistics.
7(2), 640-668.
-
Gokce, E. I., Shrivastava, A. K., & Ding, Y. u.
(2013).
Fault Tolerance Analysis of Surveillance Sensor Systems. 62(2), 478-489.
-
Park, C., Huang, J. Z., Ji, J. X., & Ding, Y. u.
(2013).
Segmentation, Inference and Classification of Partially Overlapping Nanoparticles. IEEE Transactions on Pattern Analysis and Machine Intelligence.
35(3), 669-681.
-
Park, C., Huang, J. Z., Huitink, D., Kundu, S., Mallick, B. K., Liang, H., & Ding, Y. u.
(2012).
A multistage, semi-automated procedure for analyzing the morphology of nanoparticles. IIE Transactions.
44(7), 507-522.
-
Gaukler, G. M., Li, C., Ding, Y. u., & Chirayath, S. S.
(2012).
Detecting nuclear materials smuggling: performance evaluation of container inspection policies. Risk Analysis: an international journal.
32(3), 531-554.
-
Park, C., Huang, J. Z., & Ding, Y. u.
(2012).
GPLP: A Local and Parallel Computation Toolbox for Gaussian Process Regression. JOURNAL OF MACHINE LEARNING RESEARCH.
13, 775-779.
-
Byon, E., Prez, E., Ding, Y. u., & Ntaimo, L.
(2011).
Simulation of wind farm operations and maintenance using discrete event system specification. SIMULATION.
87(12), 1093-1117.
-
Gaukler, G. M., Li, C., Cannaday, R., Chirayath, S. S., & Ding, Y. u.
(2011).
Detecting nuclear materials smuggling: using radiography to improve container inspection policies. Annals of Operations Research.
187(1), 65-87.
-
Park, C., Huang, J. Z., & Ding, Y. u.
(2011).
Domain Decomposition Approach for Fast Gaussian Process Regression of Large Spatial Data Sets. JOURNAL OF MACHINE LEARNING RESEARCH.
12, 1697-1728.
-
Kianfar, K., Pourhabib, A., & Ding, Y. u.
(2011).
An Integer Programming Approach for Analyzing the Measurement Redundancy in Structured Linear Systems. 8(2), 447-450.
-
Xia, H. H., Ding, Y. u., & Mallick, B. K.
(2011).
Bayesian hierarchical model for combining misaligned two-resolution metrology data. IIE Transactions.
43(4), 242-258.
-
Byon, E., Perez, E., Ding, Y. u., & Ntaimo, L.
(2011).
Simulation of wind farm operations and maintenance using discrete event system specification. SIMULATION.
87(12), 1093-1117.
-
Gokce, E. I., Shrivastava, A. K., Cho, J. J., & Ding, Y. u.
(2011).
Decision Fusion from Heterogeneous Sensors in Surveillance Sensor Systems. IEEE Transactions on Automation Science and Engineering.
8(1), 228-233.
-
Byon, E., & Ding, Y. u.
(2010).
Season-Dependent Condition-Based Maintenance for a Wind Turbine Using a Partially Observed Markov Decision Process. IEEE TRANSACTIONS ON POWER SYSTEMS.
25(4), 1823-1834.
-
Byon, E., Ntaimo, L., & Ding, Y. u.
(2010).
Optimal Maintenance Strategies for Wind Turbine Systems Under Stochastic Weather Conditions. 59(2), 393-404.
-
Park, C., Huang, J. Z., & Ding, Y. u.
(2010).
A Computable Plug-In Estimator of Minimum Volume Sets for Novelty Detection. Operations Research.
58(5), 1469-1480.
-
Byon, E., Shrivastava, A. K., & Ding, Y. u.
(2010).
A classification procedure for highly imbalanced class sizes. IIE Transactions.
42(4), 288-303.
-
Cho, J. J., Ding, Y. u., Chen, Y., & Tang, J.
(2010).
Robust Calibration for Localization in Clustered Wireless Sensor Networks. 7(1), 81-95.
-
Cho, J. J., Chen, Y., & Ding, Y. u.
(2009).
Calculating the Breakdown Point of Sparse Linear Models. Technometrics.
51(1), 34-46.
-
Ren, Y., & Ding, Y. u.
(2009).
Optimal sensor distribution in multi-station assembly processes for maximal variance detection capability. IIE Transactions.
41(9), 804-818.
-
Ren, Y., Ding, Y. u., & Liang, F.
(2008).
Adaptive evolutionary Monte Carlo algorithm for optimization with applications to sensor placement problems. Statistics and Computing.
18(4), 375-390.
-
Xia, H. H., Ding, Y. u., & Wang, J.
(2008).
Gaussian process method for form error assessment using coordinate measurements. IIE Transactions.
40(10), 931-946.
-
Hao, S., Zhou, S., & Ding, Y. u.
(2008).
Multivariate process variability monitoring through projection. Journal of Quality Technology.
40(2), 214-226.
-
Ding, Y., & Apley, D. W.
(2007).
Guidelines for placing additional sensors to improve variation diagnosis in assembly processes. International Journal of Production Research.
45(23), 5485-5507.
-
Cho, J. J., Chen, Y., & Ding, Y. u.
(2007).
On the (co)girth of a connected matroid. DISCRETE APPLIED MATHEMATICS.
155(18), 2456-2470.
-
Li, Z., Zhou, S., & Ding, Y. u.
(2007).
Pattern matching for variation-source identification in manufacturing processes in the presence of unstructured noise. IIE Transactions.
39(3), 251-263.
-
Ding, Y. u., Elsayed, E. A., Kumara, S., Lu, J., Niu, F., & Shi, J. J.
(2006).
Distributed sensing for quality and productivity improvements. IEEE Transactions on Automation Science and Engineering.
3(4), 344-359.
-
Chen, Y., Ding, Y. u., Jin, J. J., & Ceglarek, D.
(2006).
Integration of process-oriented tolerancing and maintenance planning in design of multistation manufacturing processes. 3(4), 440-453.
-
Ding, Y. u., & Shi, J.
(2006).
Special section on distributed sensing for quality and productivity improvement. IEEE Transactions on Automation Science and Engineering.
3(4), 342-343.
-
Ren, Y., Ding, Y. u., & Zhou, S.
(2006).
A data mining approach to study the significance of nonlinearity in multistation assembly processes. IIE Transactions.
38(12), 1069-1083.
-
Mandroli, S. S., Shrivastava, A. K., & Ding, Y.
(2006).
A survey of inspection strategy and sensor distribution studies in discrete-part manufacturing processes. IIE Transactions.
38(4), 309-328.
-
Gupta, A., Ding, Y. u., Xu, L., & Reinikainen, T.
(2006).
Optimal parameter selection for electronic packaging using sequential computer simulations. 128(3), 705-715.
-
Ding, Y. u., Zeng, L. i., & Zhou, S.
(2006).
Phase I analysis for monitoring nonlinear profiles in manufacturing processes. Journal of Quality Technology.
38(3), 199-216.
-
Liu, C., Ding, Y., & Chen, Y.
(2005).
Optimal coordinate sensor placements for estimating mean and variance components of variation sources. 37(9), 877-889.
-
Apley, D. W., & Ding, Y.
(2005).
A, characterization of diagnosability conditions for variance components analysis in assembly operations. IEEE Transactions on Automation Science and Engineering.
2(2), 101-110.
-
Kim, P., & Ding, Y.
(2005).
Optimal engineering system design guided by data-mining methods. Technometrics.
47(3), 336-348.
-
Ding, Y., Jin, J. H., Ceglarek, D., & Shi, J. J.
(2005).
Process-oriented tolerancing for multi-station assembly systems. IIE Transactions.
37(6), 493-508.
-
Kim, P., & Ding, Y.
(2004).
Optimal design of fixture layout in multistation assembly processes. IEEE Transactions on Automation Science and Engineering.
1(2), 133-145.
-
Jin, J. H., & Ding, Y.
(2004).
Online automatic process control using observable noise factors for discrete-part manufacturing. IIE Transactions.
36(9), 899-911.
-
Ding, Y., Gupta, A., & Apley, D. W.
(2004).
Singularity issues in fixture fault diagnosis for multi-station assembly processes. 126(1), 200-210.
-
Ceglarek, D., Huang, W., Zhou, S., Ding, Y., Kumar, R., & Zhou, Y.
(2004).
Time-Based Competition in Multistage Manufacturing: Stream-of-Variation Analysis (SOVA) MethodologyReview. Flexible Services and Manufacturing Journal.
16(1), 11-44.
-
Ding, Y., Kim, P., Ceglarek, D., & Jin, J.
(2003).
Optimal sensor distribution for variation diagnosis in multistation assembly processes. IEEE Transactions on Automation Science and Engineering.
19(4), 543-556.
-
Zhou, S., Ding, Y. u., Chen, Y., & Shi, J.
(2003).
Diagnosability Study of Multistage Manufacturing Processes Based on Linear Mixed-Effects Models. Technometrics.
45(4), 312-325.
-
Ding, Y., Ceglarek, D., & Shi, J. J.
(2002).
Design evaluation of multi-station assembly processes by using state space approach. Journal of Mechanical Design - Transactions of the ASME.
124(3), 408-418.
-
Ding, Y., Ceglarek, D., & Shi, J. J.
(2002).
Fault diagnosis of multistage manufacturing processes by using state space approach. 124(2), 313-322.
-
Ding, Y., Shi, J. J., & Ceglarek, D.
(2002).
Diagnosability analysis of multi-station manufacturing processes. Journal of Dynamic Systems Measurement and Control: Transactions of the ASME.
124(1), 1-13.
-
Wang, Y., Ding, Y. u., & Shahrampour, S.
(2023).
TAKDE: Temporal Adaptive Kernel Density Estimator for Real-Time Dynamic Density Estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence.
PP(99), 1-13.
-
chapter
-
Wang, Y., Ding, Y. u., & Shahrampour, S.
(2024).
Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach. Dynamic Data Driven Applications Systems.
(pp. 275-282).
Springer Nature.
-
Wang, Y., Ding, Y. u., & Shahrampour, S.
(2024).
Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach. Dynamic Data Driven Applications Systems.
(pp. 275-282).
Springer Nature.
-
conference paper
-
Vijayaraghavan, V., Kianfar, K., Ding, Y. u., & Parsaei, H.
(2018).
A Mixed Integer Programming Based Recursive Variance Reduction Method for Reliability Evaluation of Linear Sensor Systems. IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering.
836-842.
-
Ahmed, I., Dagnino, A., Bongiovi, A., & Ding, Y. u.
(2018).
Outlier Detection for Hydropower Generation Plant. IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering.
193-198.
-
Vijayaraghavan, V., Kianfar, K., Ding, Y. u., & Parsaei, H.
(2017).
An L1-Minimization Based Algorithm to Measure the Redundancy of State Estimators in Large Sensor Systems. IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering.
424-428.
-
Sy, E., Jacobs, S. A., Dagnino, A., & Ding, Y. u.
(2016).
Graph-Based Clustering for Detecting Frequent Patterns in Event Log Data. IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering.
972-977.
-
Ding, Y. u., & Bukkapatnam, S.
(2015).
Challenges and Needs for Automating Nano Image Processing for Material Characterization. Proceedings of SPIE.
95560z-95560z-7.
-
Ding, Y. u., Tang, J., & Huang, J. Z.
(2015).
DATA ANALYTICS METHODS FOR WIND ENERGY APPLICATIONS. v009t46a020-v009t46a020.
-
Zhang, S., Tang, J., & Ding, Y. u.
(2014).
MODELING AND ANALYSIS OF TIME-PERIODIC GEARBOX VIBRATION. v03bt46a032-v03bt46a032.
-
Perez, E., Ntaimo, L., & Ding, Y. u.
(2013).
SIMULATION OF WIND FARM OPERATIONS AND MAINTENANCE. v008t44a007-v008t44a007.
-
Byon, E., & Ding, Y.
(2011).
Integrating simulation and optimization for wind farm operations under stochastic conditions
-
Prez, E., Ntaimo, L., Byon, E., & Ding, Y.
(2010).
A stochastic DEVS wind turbine component model for wind farm simulation. Simulation Series.
20-27.
-
Prez, E., Ntaimo, L., Byon, E., & Ding, Y. u.
(2010).
A stochastic DEVS wind turbine component model for wind farm simulation. 138-138.
-
Byon, E., Ntaimo, L., & Ding, Y. u.
(2009).
OPTIMAL MAINTENANCE STRATEGIES FOR WIND TURBINE SYSTEMS. 75-79.
-
Park, C., Ding, Y. u., & Byon, E.
(2008).
Collaborative data reduction for energy efficient sensor networks. IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering.
442-447.
-
Cho, J. J., Ding, Y. u., Chen, Y., & Tang, J.
(2007).
Robust calibration for localization in clustered wireless sensor networks. IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering.
43-48.
-
Ding, Y. u., Gupta, A., & Apley, D. W.
(2003).
Singularity Issue in Dimensional Variation Diagnosis of Multi-Station Assembly Processes. 339-350.
-
Ding, Y., Ceglarek, D., & Shi, J.
(2002).
Design evaluation of multi-station assembly processes by using state space approach. 369-378.
-
Ding, Y. u., Shi, J., & Ceglarek, D.
(2002).
Diagnosability Analysis of Multi-Station Manufacturing Processes. 475-484.
-
Ahmed, I., Galoppo, T., & Ding, Y. u.
O-LoMST: An Online Anomaly Detection Approach And Its Application In A Hydropower Generation Plant. IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering.
762-767.
-
Vijayaraghavan, V., Kianfar, K., Ding, Y. u., & Parsaei, H.
(2018).
A Mixed Integer Programming Based Recursive Variance Reduction Method for Reliability Evaluation of Linear Sensor Systems. IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering.
836-842.
Research
principal investigator on
- CPS: Medium: Real-Time Learning and Control of Stochastic Nanostructure Growth Processes Through in situ Dynamic Imaging awarded by Directorate for Engineering - (Arlington, Virginia, United States) 2021 - 2023
- S&AS: INT: Autonomous Experimentation Platform for Accelerating Manufacturing of Advanced Materials awarded by National Science Foundation - (Arlington, Virginia, United States) 2019 - 2022
- BIGDATA: IA: Collaborative Research: From Bytes to Watts - A Data Science Solution to Improve Wind Energy Reliability and Operation awarded by National Science Foundation - (Arlington, Virginia, United States) 2017 - 2020
- CPS: Synergy: Collaborative Research: Cybernizing Mechanical Structures through Integrated Senor-Structure Fabrication awarded by National Science Foundation - (Arlington, Virginia, United States) 2016 - 2019
- Structure-Aware Reliability Analysis of State Estimators in Large-Scale Sensor Systems awarded by Qatar National Research Fund - (Doha, Qatar) 2015 - 2018
- Dynamic, Data-Driven Modeling of Nanoparticle Self Assembly Processes awarded by United States Air Force - (Arlington, Virginia, United States) 2016 - 2017
- GOALI: Collaborative Research: A System-Level Framework for Operation and Maintenance: Synergizing Near and Long Term Cares for Wind Turbines awarded by National Science Foundation - (Arlington, Virginia, United States) 2013 - 2017
- Dynamic, Data-Driven Modeling of Nanoparticle Self Assembly Processes awarded by United States Air Force - (Arlington, Virginia, United States) 2013 - 2016
- Collaborative Research: Multi-Accuracy Bayesian Models for Improving Property Prediction of Nanotube Buckypaper Composites awarded by National Science Foundation - (Arlington, Virginia, United States) 2010 - 2015
Teaching
teaching activities
- ISEN614 Advan Quality Control Instructor
- ISEN616 Des & Analy Ind Exper Instructor
- ISEN619 Analysis & Prediction Instructor
- ISEN681 Seminar Instructor
- ISEN684 Professional Internship Instructor
- ISEN684 Professional Internship: In-ab Instructor
- ISEN689 Sptp:forecasting Renew Energy Instructor
- ISEN691 Research Instructor
- ISEN692 Professional Study Instructor
- ITDE684 Professional Internship Instructor
Works By Students
chaired theses and dissertations
-
Byon, Eunshin (2011-08). Simulation and Optimization of Wind Farm Operations under Stochastic Conditions.
-
Chin, Chang-Ho (2005-11). Optimal filter design approaches to statistical process control for autocorrelated processes.
-
Cho, Jung Jin (2009-05). On the robustness of clustered sensor networks.
-
Gupta, Abhishek (2004-09). Robust design using sequential computer experiments.
-
Hwangbo, Hoon (2017-07). Performance Evaluation of Wind Power Systems Based on Production Economics Theory.
-
Kim, Pansoo (2004-11). Near optimal design of fixture layouts in multi-station assembly processes.
-
Lawley, Jason Kriel (2018-07). Optimal Personnel Deployment Strategy for Self-Perform Maintenance on Wind Farms.
-
Lee, Giwhyun (2013-05). Data Analytics Methods in Wind Turbine Design and Operations.
-
Lee, Hyun Cheol (2005-11). Robust design of control charts for autocorrelated processes with model uncertainty.
-
Liu, Qinyan (2005-08). Optimal coordinate sensor placements for estimating mean and variance components of variation sources.
-
Park, Chiwoo (2012-10). Automated Morphology Analysis of Nanoparticles.
-
Perez, David Matthew (2018-07). Exploring Key Variables In Wind Turbine Power Curve Modeling.
-
Pourhabib, Arash (2014-07). Gaussian Process Modeling and Computation in Engineering Applications.
-
Qian, Yanjun (2018-06). Data Science Methods for Analyzing Nanomaterial Images and Videos.
-
Ren, Yuan (2010-01). Adaptive Evolutionary Monte Carlo for Heuristic Optimization: With Applications to Sensor Placement Problems.
-
Shrivastava, Abhishek Kumar (2011-02). Listing Unique Fractional Factorial Designs.
-
Xia, Haifeng (2010-01). Bayesian Hierarchical Model for Combining Two-resolution Metrology Data.
-
Zhang, Feng (2005-02). Identifying nonlinear variaiton patterns in multivariate manufacturing processes.
Background
education and training
- Ph.D. in Mechanical Engineering, University of Michigan-Ann Arbor - (Ann Arbor, Michigan, United States) 2001
- M.S. in Mechanical Engineering, Pennsylvania State University - (State College, Pennsylvania, United States) 1998
- M.S. in Precision Instrument, Tsinghua University - (Beijing, Beijing, China) 1996
- B.S. in Precision Engineering, University of Science and Technology of China - (Hefei, China) 1993
awards and honors
- Association of Former Students University-Level Distinguished Achievement Award, The, conferred by Texas A&M University - (College Station, Texas, United States), 2020
- Fellow Award, conferred by Institute of Industrial Engineers - (Hong Kong, Hong Kong, China), 2015
- IIE Transactions Award, conferred by Institute of Industrial Engineers - (Hong Kong, Hong Kong, China), 2014
- IIE Transactions Award, conferred by Institute of Industrial Engineers - (Hong Kong, Hong Kong, China), 2006
- Faculty Early Career Development (CAREER) Program, conferred by National Science Foundation - (Arlington, Virginia, United States), 2004
Contact
first name
- Yu
has last name
- Ding
mailing address
-
Texas A&M University
Industrial and Systems Engineering
3131 TAMU
College Station, TX 77843-3131
USA
Other
In the News
- New Method Improves EM Image Quality without Compromising Samples News Release
- New Super-Resolution Method Reveals The Fine Details News Release
- New super-resolution method reveals fine details without constantly needing to zoom in News Release
- Texas A&M Announces 2020 Distinguished Achievement Award Recipients News Release
- yuding@tamu.edu