Research Overview

Book Chapters

Tucker, C.Quantifying the Relevance of Product Feature Classification in Product Family Design”, Product Platform and Product Family Design: Methods and Applications, edited by Siddique, Z. and Jiao, R. J. Vol. 2, 2013.

Peer Reviewed Journal Publications


Lim, S. and Tucker, C., (2016), "A Bayesian Sampling Method for Product Feature Extraction from Large Scale Textual Data", Journal of Mechanical Design, doi:10.1115/1.4033238.

Bharathi, A., Singh, A., Tucker, C., and Nembhard, H. (2016), "Knowledge Discovery of Game Design Features By Mining User-Generated Feedback", Computers in Human Behavior, 60, 361-371.

Munoz, D. and Tucker, C. (2015), "Modeling the Semantic Structure of Textually-Derived Learning Content and its Impact on Recipients’ Response States", ASME Journal of Mechanical Design, doi:10.1115/1.4032398.

Tucker, C., Behoora, I.,  Black-Nembhard, H., Lewis, M., Sterling, N., and Huang, X. (2015), “Machine Learning Classification of Medication Adherence in Patients with Movement Disorders Using Non-Wearable Sensors”, Computers in Biology and Medicine, 66, 120-134.

Kang, S., and Tucker, C. (2015), "An automated approach to quantifying functional interactions by mining large-scale product specification data", Journal of Engineering Design, 1-24.

Tucker, C., Han, Y., Nembhard-Black, H., Lee, W., Lewis, M., Sterling, N. and Huang, X. (2015), “A Data Mining Methodology For Predicting Early Stage Parkinson'S Disease Using Non-Invasive, High-Dimensional Gait Sensor Data”, IIE Transactions on Healthcare Systems Engineering, 5(4), 238-254.

Behoora, I. and Tucker, C. (2015), "Machine Learning Classification of Design Team Members' Body Language Patterns For Real Time Emotional State Detection", Design Studies, 39, 100-127.

K. Kotobi, P. B. Mainwaring, C. S. Tucker, and Bilén, S.G. (2015), “Data-Throughput Enhancement Using Data Mining-Informed Cognitive Radio”, Electronics, 4(2), 221–238.

Tuarob, S. and Tucker, C. (2015), "Automated Discovery of Lead Users and Latent Product Features By Mining Large Scale Social Media Networks", ASME Journal of Mechanical Design, 137(7), 071402.

Tuarob, S. and Tucker, C. (2014), “Quantifying Product Favorability and Extracting Notable Product Features Using Large Scale Social Media Data”, ASME Journal of Computing and Information Science in Engineering, 15(3), 031003.

Tucker, C., Pursel, B. and Divinsky, A. (2014), “Mining Student-Generated Textual Data in MOOCS And Quantifying Their Effects on Student Performance and Learning Outcomes”, ASEE Computers in Education Journal (CoEd),  5(4), 84-95.

Tuarob, S., Tucker, C., Salathe, M. and Ram, N. (2014), "An Ensemble Heterogeneous Classification Methodology for Discovering Health-Related Knowledge in Social Media Messages", Journal of Biomedical Informatics, 49, 255-268.

Kang, S., Sane, C., Vasudevan, N. and Tucker, C. (2013), "Product Resynthesis: Knowledge Discovery Of The Value Of End- Of-Life Assemblies And Subassemblies", ASME Journal of Mechanical Design, 136(1), 011004.

Tucker C. and Kim, H.M. (2011), "Trend Mining for Predictive Product Design",  ASME Journal of Mechanical Design, 133(11), 111008.

Tucker C., Kim, H.M., Barker, D.E., and Zhang, Y. (2010), "A Relief F Attribute Weighting and X-Means Clustering Methodology for Top-Down Product Family Optimization", Engineering Optimization Journal, 42(7), 593-616.

Tucker, C. and Kim, H. M. (2009), "Data-Driven Decision Tree Classification for Product Portfolio Design Optimization," Journal of Computing And Information Science In Engineering (JCISE), 9(4), 041004.

Tucker, C. and Kim, H. M. (2008), "Optimal Product Portfolio Formulation by Merging Predictive Data Mining with Multilevel Optimization", ASME Journal of Mechanical Design, 130(4), 041103.

Peer Reviewed Conference Publications

Tuarob, S., Tucker, C., Salathe, M. and Ram, N., "Modeling Individual-Level Infection Dynamics Using Social Network Information", The 24th ACM International Conference on Information and Knowledge Management (CIKM 2015), Oct 19-23, 2015, Melbourne, Australia

S. Tuarob, Strong, R., Blomberg, J., Chandra, A., Chowdhary, P., Oh, S. and Tucker, C.,  “Automatic Discovery of Service Name Replacements using Ledger Data,” in Proceedings of the 2015 IEEE International Conference on Services Computing 2015 (SCC 2015), New York, USA, June 27 - July 2, 2015

Bharathi, A., and Tucker, C., “Investigating the Impact of Interactive Immersive Virtual Reality Environments in Enhancing Online Engineering Design Activities”, Proceedings of the 2015 ASME IDETC/CIE, DETC 2015-47388 (Access the presentation file here)

Dering, M. and Tucker, C., “A Computer Vision Approach for Automatically Mining and Classifying End of Life Products and Components”, Proceedings of the 2015 ASME IDETC/CIE, DETC 2015-47401 (Access the presentation file here)

Dickens, B., Sellers, S., Harms, G., Startle, O., and Tucker, C., “A Proposed Virtual Reality Approach for Minimizing Information Loss in Multi-User, Scalable Environments”, Proceedings of the 2015 ASME IDETC/CIE, DETC 2015-47414 (Access the presentation file here)

Tuarob, S., and Tucker, C., “A Product Feature Inference Model Based For Mining Implicit Customer Preferences Within Large Scale Social Media Networks”, Proceedings of the 2015 ASME IDETC/CIE, DETC 2015-47225 (Access the presentation file here)

Kang, S., and Tucker, C., “Automated Concept Generation Based On Function-Form Synthesis”, Proceedings of the 2015 ASME IDETC/CIE, DETC 2015-47687 (Access the presentation file here)

Singh, A., and Tucker, C., “Investigating the Heterogeneity of Product Feature Preferences Mined Using Online Product Data Streams”, Proceedings of the 2015 ASME IDETC/CIE, DETC 2015-47439 (Access the presentation file here)

Tucker, C. and Kumara, S., “An Automated Object-Task Mining Model for Providing Students with Real Time Performance Feedback”, Proceedings of the 2015 American Society of Engineering Education (Access the poster file here)

Loken, E., Tucker, C., Oravecz, Z. and Linder, F., “Psychometric Analysis of Residence and MOOC Assessments”, Proceedings of the 2015 American Society of Engineering Education

T. Bodnar, Tucker,C., Hopkinson, K., and Bilen, S., “Increasing the Veracity of Event Detection on Social Media Networks Through User Trust Modeling,” in Proceedings of the 2014 IEEE International Conference on Big Data, Washington, D.C., October 27-30

Yin, P., Ram, N., Lee, W., Tucker, C., Khandelwal, S., Salathe, M., “Two sides of a coin: Separating Personal Communication and Public Dissemination Accounts in Twitter”, 2014 The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 13-16 May, 2014, Tainan, Taiwan

Bodnar, T., Barclay, V., Ram, N., Tucker, C., and Salathe, M., “On the Ground Validation of Online Diagnosis with Twitter and Medical Records”, PHDA2014/WWW2014

Tucker, C., St. John, D., Behoora, I. and Marcireau, A., “Open Source 3D Scanning and Printing for Design Conceptualization and Realization”, 2014 ASME IDETC/CIE, DETC2014-34801 (Access the presentation file here)

Munoz, D. and 
Tucker, C., “Assessing Students’ Emotional States: An Approach To Identify Lectures That Provide An Optimal Learning Experience”, 2014 ASME IDETC/CIE, DETC2014-34702 (Access the presentation file here)

Tucker, C., Dickens, B. and Divinsky, A., “Knowledge Discovery of Student Sentiments in MOOCs and their Impact on Course Performance”, 2014 ASME IDETC/CIE, DEC2014-34797 (Access the presentation file here)

Doll, K. and Tucker, C., “Mining End-Of-Life Materials Suitable For Material Resynthesis And Discovering New Application Domains”, 2014 ASME IDETC/CIE, DETC2014 (Access the presentation file here)

Tuarob, S. and Tucker, C., “Discovering Next Generation Product Innovations By Identifying Lead User Preferences Expressed Through Large Scale Social Media Data”, 2014 ASME IDETC/CIE, DETC2014 (Access the presentation file here)

Lewis, K., Moore-Russo, D. Cormier, P., Olewnik, A., Kremer, G., Tucker, C., and Simpson, T., “Assessment of Product Archaeology as a Framework for Contextualizing Engineering Design", Proceedings of the 2014 American Society of Engineering Education

Tucker, C., Jackson, K., Kremer, G., and Schmidt, L. “The Evolution of Tactile and Virtual Learning Preferences in Undergraduate Engineering Education", Proceedings of the 2014 American Society of Engineering Education

John, S. and Tucker, C., “Quantifying The Price And Demand Of Subassemblies In The End Of Life Strategy Of Product Resynthesis”, 2014 ASME IDETC/CIE, DETC2014 (Access the presentation file here)

Tuarob, S., Tucker, C., Salathe, M. and Ram, N., "Discovering Health-Related Knowledge in Social Media Using Ensembles of Heterogeneous Features", The 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013), San Francisco, CA, USA (Access the presentation file here)

Sane, C. and Tucker, C., “Product Resynthesis as a Reverse Logistics Strategy for an Optimal Closed-Loop Supply Chain": Proceedings of the 2013 ASME IDETC/CIE, DETC2013-12587 (Access the presentation file here)

Vasudevan, N. and Tucker, C., " Digital Representation of Physical Artifacts: The Effect of Low Cost, High Accuracy 3D Scanning Technologies on Engineering Education, Student Learning and Design Assessments": Proceedings of the 2013 ASME IDETC/CIE, DETC2013-12651 (Access the presentation file here)

Tuarob, S. and Tucker, C., " Fad or Here to Stay: Predicting Product Market Adoption and Longevity Using Large Scale, Social Media Data": Proceedings of the 2013 ASME IDETC/CIE, DETC2013-12661 (Access the presentation file here)

Han, Y. and Tucker, C., Simpson, T. and Davidson, E. “A Data Mining Trajectory Clustering Methodology for Modeling Indoor Design Space Utilization": Proceedings of the 2013 ASME IDETC/CIE, DETC2013-12690 (Access the presentation file here)

Manohar, G. and Tucker, C., “A Privacy Preserving Data Mining Methodology for Dynamically Predicting Emerging Human Threats": Proceedings of the 2013 ASME IDETC/CIE, DETC2013-13155 (Access the presentation file here)

Lewis, K., Moore-Russo, D. Cormier, P., Olewnik, A., Kremer, G., Tucker, C., Simpson, T. and Ashour, O., “The Assessment Of Product Archaeology As A Platform For Contextualizing Engineering Design": Proceedings of the 2013 ASME IDETC/CIE, DETC2013-12587

Lewis, K., Moore-Russo, D. Cormier, P., Olewnik, A., Kremer, G., Tucker, C., and Simpson, T., “The Development of Product Archaeology as a Platform for Contextualizing Engineering Design": Proceedings of the 2013 ASEE

Jackson, K., Tucker, C. and Kremer, G., “Student Perceptions of Tactile and Virtual Learning Approaches: What Can We Learn from their Viewpoint": Proceedings of the 2013 ASEE

Tucker, C. and Kang, S. “A Bisociative Design Framework For Knowledge Discovery Across Seemingly Unrelated Product Domains”, Proceedings of the 2012 ASME IDETC/CIE, DETC2012-70764 (Access the presentation file here)

Crespo, J., Kremer, G., Tucker, C. and Medina, L. “An Analysis of Complexity Measures in Product Design and Development”: Proceedings of the 2012 ASME IDETC/CIE, DETC2012-1309

Tucker, C. and Kim, H. M. “Predicting Emerging Product Design Trends by Mining Publicly Available Customer Review Data”, Proceedings of the 18th International Conference on Engineering Design (ICED11), Vol. 6 2011

Tucker, C., Kim, H. M., “Trending Mining for Predictive Product Design”, 2010 ASME IDETC/CIE, DETC2010-28364

Tucker, C., Hoyle, C., Kim, H. M., and Chen, W., “A Comparative Study of Data-Intensive Demand Modeling Techniques In Relation To Product Design and Development”, Proceedings of the 2009 ASME IDETC/CIE, DETC2009-87049 

Tucker, C., Kim, H., Barker, D., & Zhang, Y. (2008). "Data-Mining Driven Reconfigurable Product Family Design Framework for Aerodynamic Particle Separators". In 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference (p. 6065)

Tucker, C. and Kim, H. M., “Product Family Concept Generation and Validation through Predictive Decision Tree Data Mining and Multi-level Optimization”, Proceedings of the 2007 ASME Design Automation Conference, 2007

Tucker, C. and Kim, H. M., “Optimal Product Portfolio Formulation: Merging Predictive Data Mining with Analytical Target Cascading,” Proceedings of the 11th AIAA/MAO Conference, Portsmouth, VA, USA, September, 2006