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Biography

Shouyi Wang received the B.S. degree in Control Science and Engineering from Harbin Institute of Technology, Harbin, China, in 2003 and the M.S. degree in Systems and Control Engineering from Delft University of Technology, Delft, the Netherlands, in 2005 and the Ph.D. degree in Industrial and Systems Engineering from Rutgers University, Piscataway, NJ in 2012. From 2011-2013, he was a research scientist in the Department of Industrial and Systems Engineering and the Integrated Brain Imaging Center at School of Medicine, University of Washington, Seattle. Currently, he is an Assistant Professor of Industrial and Manufacturing Systems Engineering at the University of Texas at Arlington, Arlington, TX. His current research interests include data analytics, decision analytics, machine learning, and AI technologies with applications to optimize complex systems in healthcare, manufacturing, energy, agriculture, and other industries that require data-driven technologies.

Education

    • 2012 PhD in Industrial & Systems Engineering
      Rutgers University, 2012
    • 2005 MS in Systems & Control Engineering
      Delft University of Technology, Netherlands, 2005
    • 2003 BS in Control Science & Engineering
      Harbin Institute of Technology, China, 2003

Appointments

    • Aug 2012 to July 2013 Research Associate
      Joint ISE Dept. and School of Medicine ,University of Washington (Seattle, WA, United States)
      worked as a research associate at UW Complex Systems Modeling & Optimization Lab at ISE Department and the Integrated Brain Imaging Center at UW school of medicine. The research was conducted to develop novel data mining and machine learning solutions for challenging biomedical research problems.
    • Sept 2011 to July 2012 Research Scientist
      Integrated Brain Imaging Center ,University of Washington (Seattle, WA, United States)
      worked as a research associate at UW Complex Systems Modeling & Optimization Lab at ISE Department and the Integrated Brain Imaging Center at UW school of medicine. The research was conducted to develop novel data mining and machine learning solutions for challenging biomedical research problems.

Memberships

    • Jan 2013 to Present Institute of Industrial Engineers
      Member
    • Jan 2010 to Present Institute of Electrical and Electronics Engineers
      Member
    • Jan 2009 to Present Institute for Operations Research and the Management Sciences
      Member

Awards and Honors

    • Aug  2018 Foxconn Research Innovation Award on Smart Manufacturing sponsored by Foxconn Global Advanced Manufacturing Research Center
    • Oct  2016 Best Paper Award Runner Up sponsored by The 9th International Conference on Brain Informatics
    • Mar  2014 Featured Article with Media Report sponsored by Physics in Medicine and Biology
    • Jan  2014 Featured Article sponsored by International Journal of Data Mining and Bioinformatics
    • Dec  2013 Featured Article with Media Report sponsored by IEEE Transactions on Knowledge and Data Engineering
    • Nov  2012 Best Paper Award Runners Up sponsored by Data Mining Section, the 2012 Annual Meeting of The Institute for Operations Research and the Management Sciences (INFORMS)
    • Dec  2011 Travel Award sponsored by The 2011 IEEE International Conference on Bioinformatics & Biomedicine

News Articles

Publications

      Journal Article 2018
      • Cost-effectiveness of Patient-Specific Motion Management Strategy in Lung Cancer Radiation Therapy Planning
        [Liu, Shan, Wang, Shouyi, Chaovalitwongse, W.Art, Bowen, StephenR.]. Engineering Economist, Special Issue on Engineering Economic Models in Healthcare Systems.
      2018
      • Discriminative Analysis of Parkinson's Disease Based on fMRI Functional Connectivity at Different Sub-frequency Bands
        [Wang, Shouyi, Puk, Kin-Ming, Hosseini, Rahilsadat, Chaovalitwongse, Wanpracha, Grabowski, Thomas]. Brain Informatics.
      2018
      • Machine Learning of Tumor Cluster Dosi-Radiomics to Predict Regional Changes on Early-Response FDG PET/CT Imaging of FLARE-RT Protocol Patients
        [Duan, Chunyan, Chaovalitwongse, Wanpracha, Puk, Kinming, Wang, Shouyi, Hippe, Dan, Pierce, L, Liu, X]. Medical Physics. 45(6), E441-E442.
      2018
      • An fNIRS-Based Feature Learning and Classification Framework to Distinguish Hemodynamic Patterns in Children Who Stutter
        [Hosseini, Rahilsadat, Walsh, Bridget , Tian, Fenghua , Wang, Shouyi]. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26(6), 1254-1263. "IEEE".
      2018
      • Discriminative Spectral Pattern Analysis for Positive Margin Detection of Prostate Cancer
        [Chan, Henry, Kapur, Payal, Cadeddu, Jeffrey, Liu, Hanli, , Wang, Shouyi]. IISE Transactions on Healthcare Systems Engineering. 8(2), 144-154. Array: "IISE".
      Research Report 2018
      • A Comprehensive Simulation-Based Approach for iPhone Manufacturing System Modeling and Operations Optimization
        [Wang, Shouyi, Puk, Kinming, Thriu Elangho Raj, Arvind]. Array.
      2018
      • Integration of the Intelligent Pattern Learning System with Multiple Automated Micro-screw Driving Platforms
        [Wang, Shouyi, Liu, Feng, Puk, Kinming]. Array.
      2018
      • High-Precision Pattern Classification of Micro-Screw Driving Operations Using Torque Feedback Signals
        [Wang, Shouyi, Liu, Feng]. Array.
      Journal Article Submitted
      • Real Time Prediction of Respiratory Motion Using a Novel Pattern-Based Approach
        [Kam, K., Wang, Shouyi, Bowen, S., Chaovalitwongse, W.]. IEEE Transactions on Human Machine Systems.
      Submitted
      • A Novel Information-Integrated Sparse Feature Learning Approach to Identify Biomarkers of Posttraumatic Stress Disorder using Functional Near Infrared Brain Imaging
        [Hosseini, Rahilsadat, Wang, Shouyi, Liu, Hanli, Tian, Fenghua]. IEEE Transactions on Neural Systems and Rehabilitation Engineering. "IEEE".
      Revising to Resubmit
      • Low-Rank Representation for EEG Source Localization with Temporal Graph Regularization
        [Liu, Feng, Rosenberger, Jay, Lou, Yifei, Wang, Shouyi]. IEEE Transactions on Biomedical Engineering.
      Revising to Resubmit
      • Musical Training and Memorial Advantages in Recognition: An Electrophysiological Study
        [Kam, K., Schaeffer, J., Wang, Shouyi, Park, H.]. Brain Informatics.
      Submitted
      • A Minimum Spanning Tree-based Statistical Modeling Approach for Directed Connectivity Analysis of Brain Networks
        [Hosseini, Rahilsadat, Wang, Shouyi]. IEEE Journal of Biomedical and Health Informatics. "IEEE".
      Submitted
      • Probing Protein Allostery as a Residue-specific Concept via Residue Perturbation Maps
        [Hayatshahi, Hamed, Ahuactzin, Emilio , Tao, Peng, Wang, Shouyi, Liu, Jin]. PLoS Computational Biology. "PLos".
      Submitted
      • Sensitivity analysis of tumor cluster dosi-radiomics to predict regional changes on early-response FDG PET/CT Imaging of FLARE-RT Protocol Patients
        [Duan, Chunyan, Chaovalitwongse, Wanpracha, Puk, Kinming, Wang, Shouyi, Hippe, Dan, Pierce, L, Liu, X]. Physics in Medicine & Biology.
      Revising to Resubmit
      • A Supervised Learning Model for Predicting Tibia Soft Tissue Insertions Using Multi-Response Support Vector Regression
        [Puk, Kinming, Wang, Shouyi, Rosenberger, JayM]. IEEE Transactions on Knowledge and Data Engineering.
      Revising to Resubmit
      • Sparse Group Selection and Analysis of Function-Related Residue for Protein-State Recognition
        [Wang, Shouyi, Puk, Kinming, Zhou, Hongyu, Dong, Zheng, Tao, Peng]. Journal of Computational Chemistry. "John Wiley & Sons".
      Submitted
      • Uncovering Dynamic Functional Connectivity of Parkinson's Disease Using Sparse Group Lasso and Topological Features
        [Puk, Kinming, Wang, Shouyi]. Neuroinformatics. "Springer".
      Revising to Resubmit
      • An Efficient and Robust Approach for Automated Online Segmentation of Time Series Streams
        [Wang, Shouyi, Kam, Kinming, Chaovalitwongse, W.]. Pattern Recognition.
      Revising to Resubmit
      • Discover Discriminative Source Activations in EEG Brain Mapping using a Supervised Sparse Dictionary Learning Approach
        [Liu, Feng, Wang, Shouyi, Rosenberger, Jay, Su, Jianzhong, Liu, Hanli]. IEEE Transactions on Knowledge and Data Engineering.
      Conference Proceeding Accepted
      • Construction of Sparse Weighted Directed Network from the Multivariate Time-series
        [Hosseini, Rahilsadat, Wang, Shouyi].
      Submitted
      • A Novel Automated Approach for Online Segmentation of Time Series Data
        [Wang, Shouyi, Kam, Kinming, , ]. "AAAI 2019".
      Accepted
      • Uncovering Dynamic Functional Connectivity of Parkinson's Disease Using Topological Features and Sparse Group Lasso
        [Puk, Kin-Ming, Wang, Shouyi, Xiang, Wei, Chaovalitwongse, Wanpracha, Grabowski, Thomas].
      Accepted
      • Estimating Latent Brain Sources with Low-Rank Representation and Graph Regularization
        [Liu, Feng, Rosenberger, Jay, Lou, Yifei, Wang, Shouyi]. IEEE Transactions on Biomedical Engineering.
      Software Published
      • A Real-Time Smart Pattern Recognition and Visualization System for an Automated Micro-screw Driving Platform
        [Wang, Shouyi].
      Journal Article 2017
      • An Adaptive Pattern Learning Framework to Personalize Online Seizure Prediction
        [Xiao, Cao, Wang, Shouyi, Iasemidis, Leon , Wong, Stephen, Wanpracha , Chaovalitwongse]. IEEE Transactions on Big Data. 1(1), 128-140. "IEEE". DOI http://dx.doi.org/10.1109/TBDATA.2017.2675982
      2017
      • Graph Regularized EEG Source Imaging with In-Class Consistency and Out-Class Discrimination
        [Liu, Feng, Rosenberger, JayM, Lou, Yifei, Hosseini, Rahilsadat, Su, Jianzhong, Wang, Shouyi]. IEEE Transactions on Big Data. 3(4), 378-391. "IEEE". DOI http://dx.doi.org/10.1109/TBDATA.2017.2756664
      2017
      • Temporal Dynamics of Eye-Tracking and EEG During Reading and Relevance Decisions
        [Gwizdka, Jacek, Hosseini, Rahilsadat, Cole, Michael, Wang, Shouyi]. Journal of the Association for Information Science and Technology. 68(10), 2299-2312. "John Wiley & Sons". DOI http://dx.doi.org/10.1002/asi.23904
      Conference Proceeding 2017
      • EEG source imaging based on spatial and temporal graph structures
        [Qin, Jing, Liu, Feng, Wang, Shouyi, Rosenberger, JayM]. 1, 1-6.
      2017
      • Supervised Discriminative EEG Brain Source Imaging with Graph Regularization
        [Liu, Feng , Hosseini, Rahilsadat , Rosenberger, JayM, Wang, Shouyi, Su, Jianzhong].
      2017
      • An interactive multisensing framework for personalized human robot collaboration and assistive training using reinforcement learning
        [Tsiakas, Konstantinos, Papakostas, Michalis , Theofanidis, Michail , Bell, Morris , Mihalcea, Rada , Wang, Shouyi, Burzo, Mihai , Makedon, Fillia]. 423-427. "ACM".
      2017
      • A Sparse Dictionary Learning Framework to Discover Discriminative Source Activations in EEG Brain Mapping.
        [Liu, Feng, Wang, Shouyi, Rosenberger, JayM, Su, Jianzhong, Liu, Hanli]. 1431-1437. "AAAI 2017".
      Research Report 2017
      • An Ensemble Pattern Learning and Prediction Framework for Multivariate Sensory Signals
        [Wang, Shouyi, Puk, Kinming]. Array.
      Other 2017
      Journal Article 2016
      • An integrated feature ranking and selection framework for ADHD characterization
        [Xiao, Cao, Bledsoe, Jesse, Wang, Shouyi, Chaovalitwongse, WanprachaArt, Mehta, Sonya, Semrud-Clikeman, Margaret, Grabowski, Thomas]. Brain Informatics. 3(3), 145-155.
      2016
      • A Patient-Specific Model for Predicting Tibia Soft Tissue Insertions From Bony Outlines Using a Spatial Structure Supervised Learning Framework
        [Xiao, Cao, Wang, Shouyi, Zheng, Liying, Zhang, Xudong, Chaovalitwongse, WanprachaArt]. IEEE Transactions on Human Machine Systems. 46(5), 638-646. "IEEE".
      2016
      • Using Wireless EEG Signals to Assess Memory Workload in the $ n $-Back Task
        [Wang, Shouyi, Gwizdka, Jacek, Chaovalitwongse, W.Art]. IEEE Transactions on Human Machine Systems. 46(3), 424-435.
      Conference Proceeding 2016
      • A Novel Mutual-Information-Guided Sparse Feature Selection Approach for Epilepsy Diagnosis Using Interictal EEG Signals
        [Wang, Shouyi, Xiao, Cao, Tsai, JeffreyJ., Chaovalitwongse, Wanpracha, Grabowski, ThomasJ.]. 274-284. "Springer".
      2016
      • A Comprehensive Feature and Data Mining Study on Musician Memory Processing Using EEG Signals
        [Kam, KinMing, Schaeffer, James, Wang, Shouyi, Park, Heekyeong]. 138-148. "Springer".
      2016
      • Pattern Classification and Analysis of Memory Processing in Depression Using EEG Signals
        [Puk, KinMing, Gandy, KellenC., Wang, Shouyi, Park, Heekyeong]. 124-137. "Springer".
      2016
      • Prediction of seizure spread network via sparse representations of overcomplete dictionaries
        [Liu, Feng, Xiang, Wei, Wang, Shouyi, Lega, Bradley]. 262-273. "Springer".
      2016
      • An Efficient Time Series Subsequence Pattern Mining and Prediction Framework with an Application to Respiratory Motion Prediction.
        [Wang, Shouyi, Kam, KinMing, Xiao, Cao, Bowen, StephenR., Chaovalitwongse, WanprachaArt]. 2159-2165. "AAAI 2016".
      Journal Article 2015
      • Online prediction of driver distraction based on brain activity patterns
        [Wang, Shouyi, Zhang, Yiqi, Wu, Changxu, Darvas, Felix, Chaovalitwongse, WanprachaArt]. IEEE Transactions on Intelligent Transportation Systems : A Publication of the IEEE Intelligent Transportation Systems Council. 16(1), 136-150. "IEEE".
      Conference Proceeding 2015
      • Pattern-Based Variant-Best-Neighbors Respiratory Motion Prediction Using Orthogonal Polynomials Approximation.
        [Kam, KinMing, Wang, Shouyi, Bowen, StephenR., Chaovalitwongse, WanprachaArt]. 1364-1370. "AAAI 2015".
      Conference Proceeding 2014
      • A Novel Probabilistic Framework to Personalize Online Epileptic Seizure Prediction
        [Wang, Shouyi, Chaovalitwongse, W., Wong, S.]. "KDD".
      Journal Article 2014
      • Respiratory trace feature analysis for the prediction of respiratory-gated PET quantification
        [Wang, Shouyi, Bowen, StephenR., Chaovalitwongse, W.Art, Sandison, GeorgeA., Grabowski, ThomasJ., Kinahan, PaulE.]. Physics in Medicine & Biology. 59(4), 1027. "IOP".
      2014
      • A gradient-based adaptive learning framework for online seizure prediction
        [Wang, Shouyi, Chaovalitwongse, WanprachaArt, Wong, Stephen]. International journal of data mining and bioinformatics. 10(1), 49-64. "Inderscience".
      Journal Article 2013
      • Online seizure prediction using an adaptive learning approach
        [Wang, Shouyi, Chaovalitwongse, WanprachaArt, Wong, Stephen]. IEEE Transactions on Knowledge and Data Engineering. 25(12), 2854-2866.
      Journal Article 2012
      • Machine learning algorithms in bipedal robot control
        [Wang, Shouyi, Chaovalitwongse, Wanpracha, Babuska, Robert]. IEEE Transactions on Systems, Man and Cybernetics. Part C, Applications and Reviews. 42(5), 728-743. "IEEE".
      Journal Article 2011
      • Early detection of numerical typing errors using data mining techniques
        [Wang, Shouyi, Lin, Cheng-Jhe, Wu, Changxu, Chaovalitwongse, WanprachaArt]. IEEE Transactions on Systems, Man, and Cybernetics. Part A, Systems and Humans : A Publication of the IEEE Systems, Man, and Cybernetics Society. 41(6), 1199-1212.
      2011
      • Pattern-and network-based classification techniques for multichannel medical data signals to improve brain diagnosis
        [Chaovalitwongse, WanprachaArt, Pottenger, RebeccaS., Wang, Shouyi, Fan, Ya-Ju, Iasemidis, LeonD.]. IEEE Transactions on Systems, Man, and Cybernetics. Part A, Systems and Humans : A Publication of the IEEE Systems, Man, and Cybernetics Society. 41(5), 977-988. "IEEE". DOI http://dx.doi.org/10.1109/TSMCA.2011.2106118
      Conference Proceeding 2010
      • A novel reinforcement learning framework for online adaptive seizure prediction
        [Wang, Shouyi, Chaovalitwongse, WanprachaArt, Wong, Stephen]. 499-504. "IEEE".
      Book Chapter 2010
      • Evaluating and Comparing Forecasting Models
        [Wang, Shouyi, Chaovalitwongse, W.]. "Wiley & Sons".
      2010
      • Operations Research in Data Mining
        [Wang, Shouyi, Seref, O., Chaovalitwongse, W.]. "Wiley & Sons".
      Conference Proceeding 2006
      • Reinforcement learning control for biped robot walking on uneven surfaces
        [Wang, Shouyi, Braaksma, Jelmer, Babuska, Robert, Hobbelen, Daan]. 4173-4178. "IEEE".

Presentations

    • August  2018
      Wang, Shouyi, "Future Factory: How Data Science and AI Technologies Are Transforming Manufacturing", Foxconn Global Advanced Manufacturing Research Center, Taiyuan, China. (August 1, 2018).
    • January  2018
      Wang, Shouyi, "Data Analytics and Machine Learning in Manufacturing", Foxconn IE University, Zhengzhou, China. (January 10, 2018).
    • November  2017
      Wang, Shouyi, "Discriminative EEG Source Imaging with Machine Learning Algorithm", Beijing, China. (November 17, 2017).
    • October  2017
      Wang, Shouyi, "Data Analytics and Modeling in Medical Imaging Analysis and Decision Making", Houston, USA. (October 21, 2017).
    • August  2017
      Wang, Shouyi, "The Future of Manufacturing with Data Analytics and Machine Learning", Foxconn China Headquarters in Shenzhen, Shenzhen, China. (August 13, 2017).
    • November  2016
      Wang, Shouyi, "Discriminating Parkinson’s Disease Using Supervised Learning of Brain Network Analysis", Nashville, TN, USA. (November 13, 2016).
    • November  2015
      Wang, Shouyi, "A CT-Imaging-Based Structural Learning Framework to Recover Natural Anatomy of Soft Tissue Insertions for Knee Reconstruction Surgery", Arlington, TX, USA. (November 10, 2015).
    • November  2015
      Wang, Shouyi, "An Efficient Orthogonal-polynomial-based Approach for Time Series Representation and Prediction", Philadelphia, USA. (November 2, 2015).
    • November  2015
      Wang, Shouyi, "Big Data Analytics and Supercomputing for Healthcare", Austin, TX, USA. (November 1, 2015).
    • June  2015
      Wang, Shouyi, "Discriminating Parkinson’s Disease (PD) Using Functional Connectivity and Brain Network Analysis", Stanford, CA, USA. (June 1, 2015).
    • March  2015
      Wang, Shouyi, "Classification of EEG signals of memory between musicians and non-musicians", San Francisco, CA, USA. (March 1, 2015).
    • January  2015
      Wang, Shouyi, "Pattern-Based Variant-Best-Neighbors Respiratory Motion Prediction Using Orthogonal Polynomials Approximation", Austin, TX, USA. (January 1, 2015).
    • November  2014
      Wang, Shouyi, "Using Physiological Signals to Assess Mental Workload on Human-Computer Interaction Tasks", San Francisco, CA, USA. (November 10, 2014).
    • August  2014
      Wang, Shouyi, "An Adaptive Learning Framework for Personalized Online Epileptic Seizure Prediction", New York, NY, USA. (August 1, 2014).
    • March  2014
      Wang, Shouyi, "Automated Time Series Modeling and Pattern Learning for Personalized Healthcare Decision-Making Systems". (March 1, 2014).
    • October  2013
      Wang, Shouyi, "Enhancing Clinical Utility of Respiratory-Gated PET/CT by Respiratory-Motion-Based Patient Classification", Minneapolis, MI, USA. (October 7, 2013).
    • October  2012
      Wang, Shouyi, "A Probabilistic Prediction Framework for Personalized Online Prediction of Epileptic Seizures", Phoenix, AZ, USA. (October 14, 2012).
    • October  2012
      Wang, Shouyi, "Online Monitoring and Prediction of Complex Time Series Events", Phoenix, AZ, USA. (October 14, 2012).
    • June  2012
      Wang, Shouyi, "Adaptive Learning Approaches for Online Monitoring and Prediction of Epileptic Seizures", Beijing, China. (June 1, 2012).
    • June  2012
      Wang, Shouyi, "An Efficient Approach for Automated Online Segmentation of Time Series", Beijing, China. (June 1, 2012).
    • November  2011
      Wang, Shouyi, "A Gradient-Based Adaptive Learning Framework for an Online Seizure Prediction", Charlotte, NC, USA. (November 13, 2011).
    • December  2010
      Wang, Shouyi, "A Novel Reinforcement Learning Framework for Online Adaptive Seizure Prediction", Hong Kong, China. (December 18, 2010).
    • July  2006
      Wang, Shouyi, "Reinforcement Learning Control for Biped Robot Walking on Uneven Surfaces", Vancouver, Canada. (July 16, 2006).

Support & Funding

This data is entered manually by the author of the profile and may duplicate data in the Sponsored Projects section.
    • Sept 2018 to Aug 2022 ALFA-IoT: ALliance For Smart Agriculture in the Internet of Things Era sponsored by  - $145000
      (Funded)
    • Sept 2018 to Aug 2019 Decision Analytics for Joint Optimization of Urban Life Environments (JOULE) sponsored by  - $20000
      (Funded)
    • Sept 2015 to Aug 2019 Collaborative Research: Decision Model for Patient-Specific Motion Management in Radiation Therapy Planning sponsored by  - $65237
      Shouyi Wang (Funded)
    • June 2015 to May 2017 A System for Neuro-Feedback Anger Management to Prevent Domestic Violence sponsored by  - $20000
      (Funded)
    • Nov 2017 to Dec 2018 Improving Data-Driven Assistive Technologies for Human Performance and Quality Management of Large-Scale Manufacturing Production Line sponsored by  - $53000
      (Funded)
    • June 2017 to May 2018 Big Data and Advanced Artificial Intelligence Techniques to Improve Manufacturing Operation Efficiency and Decision-Making sponsored by  - $234435
      (Funded)
    • June 2016 to Aug 2017 Integrated Brain Network Modeling to Improve PreSurgical Evaluation of Epilepsy sponsored by  - $10000
      Shouyi Wang (Funded)

Students Supervised

    • Present
      Bahareh Nasirian, (Industrial Engineering)
      Data Fusion and Supervised Machine Learning for Data-Driven Smart Manufacturing
    • Present
      Singh Jashandeep, (Industrial Engineering)
      Developing Simulation-based Approaches for Manufacturing Process Modeling and Optimization (Collaborative Research with Foxconn)
    • Present
      Kinming Puk, (Industrial Engineering)
      Spatial-temporal Medical Imaging Analytics and Prediction for Patients with Lung Cancer (Collaborative Research with UW Radiation Oncology)
    • Present
      Nikolai Drigalenko, (Industrial Engineering)
      Graph-Based Machine Learning for Brain Connectivity Analysis (Collaborative Research with UTSW Epilepsy Center)
    • Present
      Sharukh Kamal, (Industrial Engineering)
      Using machine learning to discover evolutionary mechanisms of antibiotic resistance and the emergence of superbugs (Collaborative Research with SMU Chemistry Department)
    • Present
      Alireza Fallahi, (Industrial Engineering)
      Linear Programming-based Optimization Approaches for Multi-Agent Demand Response Management
    • Aug 2018
      Aditya Sheth, (Industrial Engineering)
      Developing Automated Data Extraction and Statistical Analysis for iPhone Manufacturing Process (Collaborative Research with Foxconn)
    • Aug 2018
      Juan Castillo, (Industrial Engineering)
      Statistical Meta-Model For Air Traffic Flow And Capacity Management Based On Airspace Optimization-Simulation: The Continuous Challenge Of The Hub Of The America Congestion
    • Aug 2018
      Kinming Puk, (Industrial Engineering)
      Supervised Sparse Learning with Applications in Bioinformatics
    • Aug 2018
      Rahilsadat Hosseini, (Industrial Engineering)
      A Sparse Network Construction Method and a Mutual-Information based Sparse Feature Selection Algorithm for Multivariate Time-series Analysis & Its Application in Medical Diagnostic Problems
    • May 2018
      Yanyan Xu, (Industrial Engineering)
      Quality control and Statistical Modeling of Mobile Phone Manufacturing Process (Collaborative Research with FIH Mobile Fort Worth)
    • Mar 2018
      Feng Liu, (Industrial Engineering)
      Supervised Sparse Learning and Network Optimization for Bioinformatics & Neurosciences
    • Dec 2017
      Arvind Thriu Elangho Raj, (Industrial Engineering)
      Data-Driven Quality Management for Process Improvement in Smartphone Manufacturing (Collaborative Research with Foxconn)
    • Nov 2017
      Jianwei Cao, (Bioengineering)
      Revealing hemodynamic response and dynamic changes in functional cortical networks using functional near-infrared spectroscopy (fNIRS)
    • Aug 2017
      Tejas Pawar, (Industrial Engineering)
      Discrete-Event Simulation to Support Manufacturing Logistics Decision-Making (Collaborative Research with Foxconn)
    • Aug 2017
      Ying Chen, (Industrial Engineering)
      Plug-In Hybrid Electric Vehicle Charging Station Using Stochastic Dynamic Programming
    • Dec 2016
      Srividya Sekar, (Industrial Engineering)
      Improving Data Collection and Statistical Analysis of Manufacturing Operations Management
    • Dec 2016
      Marjan Sayadi, (Industrial Engineering)
      A Design And Analysis Of Computer Experiments Approach For Green Building
    • Dec 2016
      Soma Sek Balasubramanian, (Industrial Engineering)
      Evaluating the Risk Factors Associated with Hospital Closures and Deployment of Quality Improvement Initiatives
    • Aug 2016
      Wei Xiang, (Computer Science and Engineer)
      Deep Learning and GPU Accelerated Computing for Brain Imaging Analytics Research
    • May 2016
      Daniel Taylor Gellerup, (Industrial Engineering)
      Discriminating Parkinson’s Disease Using Functional Connectivity And Brain Network Analysis (Collaborative Research with UW Integrated Brain Imaging Center)
    • May 2016
      Kellen Gandy, (Psychology)
      An EEG Investigation Of A Depressive Self-Schema Related To Levels Of Processing In Individuals With High Depressive Symptomatology
    • May 2016
      Shalini Gupta, (Industrial Engineering)
      Sleep monitoring and neuromodulation using EEG signals
    • May 2015
      Kinming Kam, (Industrial Engineering)
      Stationary And Non-stationary Time Series Prediction Using State Space Model And Pattern-based Approach
    • Apr 2014
      Asama Kulvanitchaiyanunt, (Industrial Engineering)
      A Design And Analysis Of Computer Experiments-based Approach To Approximate Infinite Horizon Dynamic Programming With Continuous State Spaces

Courses

      • IE 6318-001 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Spring - Regular Academic Session - 2020
      • IE 6318-002 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Spring - Regular Academic Session - 2020
      • IE 3301-004 ENGINEERING PROBABILITY
        (Course Id: 103178)
        Spring - Regular Academic Session - 2020
      • IE 6318-001 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Fall - Regular Academic Session - 2019
      • IE 6318-002 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Fall - Regular Academic Session - 2019
      • IE 6318-003 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Fall - Regular Academic Session - 2019
      • IE 6318-004 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Fall - Regular Academic Session - 2019
      • IE 5698-012 THESIS
        (Course Id: 103285)
        Fall - Regular Academic Session - 2019
      • IE 4300-001 TOPICS INDUSTRIAL ENGINEERING
        (Topic: DATA MINING | Course Id: 103194)
        Fall - Regular Academic Session - 2019
      • IE 6318-001 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Spring - Regular Academic Session - 2019
      • IE 6318-002 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Spring - Regular Academic Session - 2019
      • IE 3301-004 ENGINEERING PROBABILITY
        (Course Id: 103178)
        Spring - Regular Academic Session - 2019
      • IE 6397-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103300)
        Spring - Regular Academic Session - 2019
      • IE 5398-012 THESIS
        (Course Id: 103282)
        Spring - Regular Academic Session - 2019
      • IE 4300-001 TOPICS INDUSTRIAL ENGINEERING
        (Course Id: 103194)
        Spring - Regular Academic Session - 2019
      • IE 4300-1
        (Course Id: 90185)
        Fall - 2018
      • IE 5391-12
        (Course Id: 86023)
        Fall - 2018
      • IE 5398-12
        (Course Id: 86268)
        Fall - 2018
      • IE 5698-12
        (Course Id: 86300)
        Fall - 2018
      • IE 6318-1
        (Course Id: 90186)
        Fall - 2018
      • IE 6318-2
        (Course Id: 90187)
        Fall - 2018
      • IE 6318-3
        (Course Id: 90188)
        Fall - 2018
      • IE 6318-4
        (Course Id: 91536)
        Fall - 2018
      • IE 6397-12
        (Course Id: 86026)
        Fall - 2018
      • IE 6399-12
        (Course Id: 86029)
        Fall - 2018
      • IE 6697-12
        (Course Id: 86032)
        Fall - 2018
      • IE 6699-12
        (Course Id: 86035)
        Fall - 2018
      • IE 6997-12
        (Course Id: 86038)
        Fall - 2018
      • IE 6999-12
        (Course Id: 86041)
        Fall - 2018
      • IE 7399-12
        (Course Id: 86044)
        Fall - 2018
      • IE 6318-001 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Fall - Regular Academic Session - 2018
      • IE 6318-002 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Fall - Regular Academic Session - 2018
      • IE 6318-003 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Fall - Regular Academic Session - 2018
      • IE 6318-004 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Fall - Regular Academic Session - 2018
      • IE 4300-001 TOPICS INDUSTRIAL ENGINEERING
        (Course Id: 103194)
        Fall - Regular Academic Session - 2018
      • IE 6999-008 DISSERTATION
        (Course Id: 103309)
        Summer - Eleven Week - 2018
      • IE 7399-012 DOCTORAL DEGREE COMPLETION
        (Course Id: 111647)
        Summer - Five Week - Second - 2018
      • IE 6318-001 DATA MINING & ANALYTICS
        (Course Id: 112909 | Servlearn: No)
        Spring - Regular Academic Session - 2018 Download Syllabus
      • IE 6318-002 DATA MINING & ANALYTICS
        (Course Id: 112909 | Servlearn: No)
        Spring - Regular Academic Session - 2018 Download Syllabus
      • IE 6318-003 DATA MINING & ANALYTICS
        (Course Id: 112909)
        Spring - Regular Academic Session - 2018 Download Syllabus
      • IE 6999-012 DISSERTATION
        (Course Id: 103309)
        Spring - Regular Academic Session - 2018
      • IE 3301-004 ENGINEERING PROBABILITY
        (Course Id: 103178 | Servlearn: No)
        Spring - Regular Academic Session - 2018 Download Syllabus
      • IE 6397-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103300)
        Spring - Regular Academic Session - 2018
      • IE 6997-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103308)
        Spring - Regular Academic Session - 2018
      • IE 6399-012 DISSERTATION
        (Course Id: 103301)
        Fall - Regular Academic Session - 2017
      • IE 6397-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103300)
        Fall - Regular Academic Session - 2017
      • IE 6997-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103308)
        Fall - Regular Academic Session - 2017
      • IE 5300-001 TOPICS IN INDUSTRIAL ENGNR
        (Topic: Data Mining and Data Analytics | Course Id: 103228 | Servlearn: No)
        Fall - Regular Academic Session - 2017 Download Syllabus
      • IE 5300-002 TOPICS IN INDUSTRIAL ENGNR
        (Course Id: 103228 | Servlearn: No)
        Fall - Regular Academic Session - 2017 Download Syllabus
      • IE 5300-004 TOPICS IN INDUSTRIAL ENGNR
        (Topic: Data Mining & Data Analytics | Course Id: 103228 | Servlearn: No)
        Fall - Regular Academic Session - 2017 Download Syllabus
      • IE 5391-012 ADV STUDY IN INDUST ENGR
        (Course Id: 103280)
        Spring - Regular Academic Session - 2017
      • IE 6397-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103300)
        Spring - Regular Academic Session - 2017
      • IE 6697-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103304)
        Spring - Regular Academic Session - 2017
      • IE 6997-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103308)
        Spring - Regular Academic Session - 2017
      • IE 5317-001 INTRO TO STATISTICS
        (Course Id: 103245 | Servlearn: No)
        Fall - Regular Academic Session - 2016 Download Syllabus
      • IE 5317-002 INTRO TO STATISTICS
        (Course Id: 103245)
        Fall - Regular Academic Session - 2016 Download Syllabus
      • IE 5317-004 INTRO TO STATISTICS
        (Course Id: 103245 | Servlearn: No)
        Fall - Regular Academic Session - 2016 Download Syllabus
      • IE 6697-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103304)
        Fall - Regular Academic Session - 2016
      • IE 6997-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103308)
        Fall - Regular Academic Session - 2016
      • IE 6397-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103300)
        Spring - Regular Academic Session - 2016
      • IE 6697-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103304)
        Spring - Regular Academic Session - 2016
      • IE 5698-012 THESIS
        (Course Id: 103285)
        Spring - Regular Academic Session - 2016
      • IE 5300-001 TOPICS IN INDUSTRIAL ENGNR
        (Topic: Data Mining & Analytics | Course Id: 103228 | Servlearn: No)
        Spring - Regular Academic Session - 2016 Download Syllabus
      • IE 5300-002 TOPICS IN INDUSTRIAL ENGNR
        (Topic: Data Mining & Analytics | Course Id: 103228)
        Spring - Regular Academic Session - 2016 Download Syllabus
      • IE 5300-004 TOPICS IN INDUSTRIAL ENGNR
        (Topic: Data Mining | Course Id: 103228 | Servlearn: No)
        Spring - Regular Academic Session - 2016 Download Syllabus
      • IE 5317-001 INTRO TO STATISTICS
        (Course Id: 103245 | Servlearn: No)
        Fall - Regular Academic Session - 2015 Download Syllabus
      • IE 5317-002 INTRO TO STATISTICS
        (Course Id: 103245)
        Fall - Regular Academic Session - 2015 Download Syllabus
      • IE 5317-004 INTRO TO STATISTICS
        (Course Id: 103245 | Servlearn: No)
        Fall - Regular Academic Session - 2015 Download Syllabus
      • IE 6397-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103300)
        Fall - Regular Academic Session - 2015
      • IE 6697-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103304)
        Fall - Regular Academic Session - 2015
      • IE 5398-012 THESIS
        (Course Id: 103282)
        Fall - Regular Academic Session - 2015
      • IE 5698-012 THESIS
        (Course Id: 103285)
        Fall - Regular Academic Session - 2015
      • IE 6397-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103300)
        Summer - Eleven Week - 2015
      • IE 6697-012 RESEARCH IN INDUSTRIAL ENGR
        (Course Id: 103304)
        Spring - Regular Academic Session - 2015
      • IE 5300-001 TOPICS IN INDUSTRIAL ENGNR
        (Topic: Data Mining & Analytics | Course Id: 103228 | Servlearn: No)
        Spring - Regular Academic Session - 2015 Download Syllabus
      • IE 5300-002 TOPICS IN INDUSTRIAL ENGNR
        (Topic: Data Mining & Analytics | Course Id: 103228)
        Spring - Regular Academic Session - 2015 Download Syllabus
      • IE 5300-003 TOPICS IN INDUSTRIAL ENGNR
        (Topic: Data Mining & Analytics | Course Id: 103228)
        Spring - Regular Academic Session - 2015 Download Syllabus
      • IE 2308-001 ECONOMICS FOR ENGINEERS
        (Course Id: 112241 | Servlearn: No)
        Fall - Regular Academic Session - 2014 Download Syllabus
      • IE 5300-001 TOPICS IN INDUSTRIAL ENGNR
        (Topic: Data Mining & Analytics | Course Id: 103228 | Servlearn: No)
        Spring - Regular Academic Session - 2014 Download Syllabus
      • IE 3312-001 ECONOMICS FOR ENGINEERS
        (Course Id: 103179 | Servlearn: No)
        Fall - Regular Academic Session - 2013 Download Syllabus

Service to the University

    • June 2014 to  Present Committee Member
      The iPerform Center for Assistive Technologies to Enhance Human Performance
      Reach out and establish university-industry collaborative research on human assistive technologies and human-centered computing.
    • Feb 2014 to  Present Committee Member
      UTA Data-Driven Discovery for Knowledge Enhancement Research Group
      University Strategic Thrust Areas
    • Feb 2014 to  Present Committee Member
      UTA Health and the Human Condition Research Group
      University Strategic Thrust Areas
    • Sept 2013 to  Present Committee Member
      Center On Stochastic Modeling, Optimization, & Statistics (COSMOS)
    • Sept 2013 to  Present Committee Member
      Industrial and Manufacturing Systems Engineering Research Committee

Service to the Profession

    • Oct 2014 to  Present
      Member
      Institute of Industrial Engineers (IIE)
    • Aug 2012 to  Present
      Member
      Institute of Electrical and Electronics Engineers (IEEE)
    • Oct 2010 to  Present
      Member
      Institute for Operations Research and the Management Sciences (INFORMS)
    • Feb 2017 to  Dec 2019
      Editor, Book
      Springer Book: Data Analytics - Models and Applications in Matlab
      Editor for the new Book “Data Analytics - Models and Applications in Matlab” by Springer, book proposal approved, planned book publication in 2017.
    • June 2018 to  Aug 2019
      Editor, Associate Editor
      International Supply Chain Technology Journal (ISCTJ)
      My main role as one of the associate editor is to ensure high-quality paper submissions; provide constructive feedback to authors; assign and evaluate the performance of reviewers and makes recommendations for the paper improvements to ensuring the readability and high quality.
    • Aug 2018 to  Dec 2018
      Editor, Conference Proceedings (Arlington, TEXAS, United States)
      The 11th International Conference on Brain Informatics
    • Oct 2017 to  Nov 2018
      Council Member
      INFORMS Data Mining Section
    • Oct 2017 to  Nov 2018
      Workshop Organizer (Phenix , Arizona, United States)
      The 13TH INFORMS Workshop On Data Mining & Decision Analytics
    • June 2016 to  Aug 2018
      Reviewer, Journal Article
      Brain Informatics (6 papers)
    • Jan 2014 to  Aug 2018
      Reviewer, Journal Article
      Annals of Operations Research (3 paper)
    • Apr 2018 to  Apr 2018
      Committee Member (Arlington, TEXAS, United States)
      The 2018 Smart and Connected Cyber Secured Internet of Things (IoT) - RFID Conference
    • Jan 2017 to  Nov 2017
      Workshop Organizer
      The 2nd International Workshop on Big Data Neuroimaging Analytics for Brain and Mental Health (in joint with BI17 )
    • Nov 2016 to  Nov 2017
      Publicity Chair (Beijing, China)
      International Conference on Brain Informatics & Health (BIH)
    • Feb 2017 to  Oct 2017
      Session Chair
      INFORMS Annual Meeting - Session Data Analytics and Modeling for Medical Prognosis and Decision Making
    • Jan 2014 to  Aug 2017
      Reviewer, Journal Article
      IEEE Transactions on Human Machine Systems (4 papers)
    • Sept 2014 to  Feb 2017
      Editor, Journal Editor
      Annals of Operations Research, Special Volume: Applied Optimization and Data Mining: Theory and Applications
      Guest Editor, Annals of Operations Research, Special Volume: Applied Optimization and Data Mining: Theory and Applications (2014 – Present), to be published in 2016.
    • Mar 2016 to  Nov 2016
      Session Chair (Nashville, TN ,
      INFORMS Annual Conference - Data Analytics and Modeling for Medical Prognosis and Decision Making
    • Mar 2016 to  Nov 2016
      Committee Member
      INFORMS Data Mining Student Paper Competition
    • Jan 2016 to  Nov 2016
      Session Chair
      INFORMS Annual Meeting - Session Data Analytics and Modeling for Medical Prognosis and Decision Making
    • Jan 2016 to  Nov 2016
      Committee Member
      INFORMS Data Mining Student Paper Competition
    • Jan 2016 to  Oct 2016
      Workshop Organizer (Omaha, Nebraska, USA)
      The First International Workshop on Big Data Neuroimaging Analytics for Brain and Mental Health (in joint with BIH 2016)
      Organized the The 1st International Workshop on Big Data Neuroimaging Analytics for Brain and Mental Health (in joint with BIH 2016).
    • Feb 2016 to  Oct 2016
      Workshop/Special Session Co-Chair
      International Conference on Brain Informatics & Health (BIH)
    • Feb 2015 to  Nov 2015
      Session Chair (Philadelphia, PA, United States)
      INFORMS Annual Conference - Data Analytics and Statistical Learning Session in Data Mining Cluster
    • Jan 2015 to  Nov 2015
      Session Chair
      INFORMS Annual Conference - Recent Advances on Support Vector Machines Research in Big Data Cluster
    • Feb 2015 to  Nov 2015
      Session Chair
      The Reborn of Traditional OR Methods in the Era of Big Data Session in Modeling and Methodologies in Big Data Cluster, INFORMS Annual Conference
    • May 2015 to  Aug 2015
      Reviewer, Journal Article
      Neurophotonics (1 paper)
    • Feb 2015 to  June 2015
      Reviewer, Journal Article
      OMEGA (1 paper)
    • Mar 2015 to  June 2015
      Reviewer, Journal Article
      IEEE Journal of Biomedical and Health Informatics (1 paper)
    • Jan 2015 to  Mar 2015
      Reviewer, Journal Article
      Computers in Biology and Medicine (1 paper)
    • Feb 2014 to  Nov 2014
      Committee Member
      INFORMS Data Mining Student Paper Competition
    • Feb 2014 to  Nov 2014
      Session Chair
      INFORMS Annual Conference - Optimization and Modeling in Radiation Therapy Treatment Planning Session in Data Mining Cluster
    • Jan 2014 to  Mar 2014
      Reviewer, Journal Article
      IIE Transactions on Healthcare Systems Engineering (1 paper)
    • Jan 2014 to  Mar 2014
      Reviewer, Journal Article
      Optimization Letters (1 paper)
    • Mar 2013 to  Oct 2013
      Session Chair
      INFORMS Annual Conference - Data Analytics and Modeling for Healthcare Management I & II Session in Data Mining Cluster
    • Feb 2012 to  Oct 2012
      Session Chair
      INFORMS Annual Conference - Decision Making and Planning: Methods and Applications Session in Data Mining Cluster
    • Feb 2012 to  Oct 2012
      Session Chair
      INFORMS Annual Conference - Optimization and Machine Learning Methods for Brain Data Analysis” in Health Informatics Cluster
    • Feb 2012 to  Oct 2012
      Session Chair
      International INFORMS Conference - Data Mining and Human Factors in Healthcare Systems Session in OR/MS in Medicine and Healthcare Cluster

Service to the Community

    • Sept 2015 to  Present
      Program Coordinator (Fort Worth, TX, United States)
      Fort Worth Regional Science and Engineering Fair
      Assist program director and board committees on various organization activities, coordinate schedule, and assignment of judges, and provide assistance for student project demonstration.