Conrad S. Tucker

发表

Semantic Network Differences Across Engineering Design Communication Methods

Christian E. Lopez, Zixuan V. Zhao, Conrad S. Tucker, 2019, Volume 1: 39th Computers and Information in Engineering Conference.

An Investigation of Surrogate Models for Efficient Performance-Based Decoding of 3D Point Clouds

Timothy W. Simpson, James Cunningham, Conrad S. Tucker, 2019, Journal of Mechanical Design.

An Automated Object-Task Mining Model for Providing Students with Real Time Performance Feedback

Soundar Kumara, Conrad S. Tucker, S. Kumara, 2015 .

Towards co-robot navigation in manufacturing environments through machine learning of human movement patterns

Conrad S. Tucker, A. Mohammed, T. Viola, 2017 .

Comparing Attribute- and Form-Based Machine Learning Techniques for Component Prediction

Christopher McComb, Jacob Nelson, Jessica Menold, 2020, DAC 2020.

Automatic Facial Feature Extraction for Predicting Designers' Comfort With Engineering Equipment During Prototype Creation

Conrad S. Tucker, Allison Gray, Timothy R. Brick, 2017 .

Multi-Context Generation in Virtual Reality Environments Using Deep Reinforcement Learning

Conrad S. Tucker, Omar Ashour, James Cunningham, 2020, Volume 9: 40th Computers and Information in Engineering Conference (CIE).

Immersive Distributed Design Through Real-Time Capture, Translation, and Rendering of Three-Dimensional Mesh Data1

Conrad S. Tucker, Kevin Lesniak, Sven G. Bilén, 2017, J. Comput. Inf. Sci. Eng..

Pixel to Stroke Sketch Generation Using Reinforcement Learning

Haizhou Wang, Conrad S. Tucker, Haizhou Wang, 2019, Volume 1: 39th Computers and Information in Engineering Conference.

Spatial Grammar-Based Recurrent Neural Network for Design Form and Behavior Optimization

Timothy W. Simpson, Gary Michael Stump, Mike Yukish, 2019, Journal of Mechanical Design.

Reinforcement Learning Content Generation for Virtual Reality Applications

Conrad S. Tucker, Christian E. Lopez, Omar Ashour, 2019, Volume 1: 39th Computers and Information in Engineering Conference.

A sparsity preserving genetic algorithm for extracting diverse functional 3D designs from deep generative neural networks

Dule Shu, Timothy W. Simpson, Conrad S. Tucker, 2020, Design Science.

Deep Reinforcement Learning for Transfer of Control Policies

Timothy W. Simpson, Conrad S. Tucker, Michael Andrew Yukish, 2019, Design Automation Conference.

Deep Reinforcement Learning for Procedural Content Generation of 3D Virtual Environments

Christian E. Lopez, Conrad S. Tucker, James Cunningham, 2020, J. Comput. Inf. Sci. Eng..

Capturing Emergent Behavior In Multi-Response Systems Through Data Trend Mining

Conrad S. Tucker, Harrison Hyung Min Kim, 2010 .

Detection of System Compromise in Additive Manufacturing Using Video Motion Magnification

Christopher McComb, Jessica Menold, Conrad S. Tucker, 2020 .

On the Analysis of a Compromised Additive Manufacturing System Using Spatio-Temporal Decomposition

Christopher McComb, Jessica Menold, Conrad S. Tucker, 2019, DAC 2019.

Mobile Based Real-Time Occlusion Between Real and Digital Objects in Augmented Reality

Conrad S. Tucker, Pranav Jain, 2019 .

Encrypted rich-data steganography using generative adversarial networks

Dule Shu, Conrad S. Tucker, Weilin Cong, 2020, WiseML@WiSec.

Generative adversarial attacks against intrusion detection systems using active learning

Dule Shu, Charles A. Kamhoua, Conrad S. Tucker, 2020, WiseML@WiSec.

A Pilot Study Investigating STEM Learners' Ability to Decipher AI-generated Video

Dule Shu, Conrad S. Tucker, Christopher Joseph Doss, 2021 .

Node classification using kernel propagation in graph neural networks

Conrad S. Tucker, Sakthi Kumar Arul Prakash, 2021, Expert Syst. Appl..

Adaptive Gamification and Its Impact on Performance

Conrad S. Tucker, Christian E. López, C. López, 2021, HCI.

The Evolution of Tactile and Digital Learning Preferences in Undergraduate Engineering Education

Linda C. Schmidt, Kathy Schmidt-Jackson, Peifeng Yin, 2014 .

Assessing causal claims about complex engineered systems with quantitative data: internal, external, and construct validity

David A. Broniatowski, Conrad S. Tucker, Conrad S. Tucker, 2017, Syst. Eng..

Predicting emerging product design trend by mining publicly available customer review data

Conrad S. Tucker, Harrison M. Kim, 2011 .

How are you feeling?: A personalized methodology for predicting mental states from temporally observable physical and behavioral information

C. Lee Giles, Conrad S. Tucker, Conrad S. Tucker, 2017, J. Biomed. Informatics.

Fad or Here to Stay: Predicting Product Market Adoption and Longevity Using Large Scale, Social Media Data DETC2013-12661

Conrad S. Tucker, 2013 .

On the ground validation of online diagnosis with Twitter and medical records pdf

Marcel Salathé, Todd J. Bodnar, Conrad S. Tucker, 2014, WWW.

Trend Mining for Predictive 1 Product Design 1

Conrad S. Tucker, Harrison M. Kim, 2011 .

The CLICK Approach and its Impact on Learning Introductory Probability Concepts in an Industrial Engineering Course

Conrad S. Tucker, Omar M. Ashour, Christian E. López, 2020 .

Exploring Biases Between Human and Machine Generated Designs

Conrad S. Tucker, Scarlett R. Miller, Christian Enmanuel Lopez, 2019, Journal of Mechanical Design.

Evaluating the cost-effectiveness of an early detection of Parkinson's disease through innovative technology

Conrad S. Tucker, Xuemei Huang, H. Nembhard, 2017, The Engineering economist.

The Pennsylvania State University The Graduate School Department of Industrial and Manufacturing Engineering A QUANTITATIVE ASSESSMENT OF PRODUCT FORM AND ITS IMPACT ON CUSTOMER PERCEPTION AND DESIGN EDUCATION

Conrad S. Tucker, Yixiang Han, N. Vasudevan, 2013 .

Board # 146 : Early Predicting of Student Struggles Using Body Language

Matthew L. Dering, Conrad S. Tucker, 2017 .

Quantifying Product Favorability

Conrad S. Tucker, 2015 .

From Mining Affective States to Mining Facial Keypoint Data: The Quest Towards Personalized Feedback

Conrad S. Tucker, Conrad S. Tucker, Christian Enmanuel Lopez, 2017 .

Evaluating the Use of Virtual Reality to Teach Introductory Concepts of Additive Manufacturing

Timothy W. Simpson, Conrad S. Tucker, Conrad S. Tucker, 2020, Journal of Mechanical Design.

3D Design Using Generative Adversarial Networks and Physics-Based Validation

Dule Shu, Timothy W. Simpson, Gary Michael Stump, 2020 .

A Physics-Based Virtual Environment for Enhancing the Quality of Deep Generative Designs

Matthew L. Dering, Timothy W. Simpson, Conrad S. Tucker, 2018, Volume 2A: 44th Design Automation Conference.

Product Resynthesis: Knowledge Discovery of the Value of End-of-Life Assemblies and Subassemblies

Conrad S. Tucker, Conrad S. Tucker, Sung Woo Kang, 2014 .

Thank You for Your Cooperation a Relieff Attribute Weighting and X-means Clustering Methodology for Top-down Product Family Optimization 1 Q1

Conrad S. Tucker, Douglas E. Barker, Harrison M. Kim, 2009 .

A data mining driven approach to real-time classroom feedback through multimodal sensing

Conrad S. Tucker, David A. Muñoz, Alexander J. W. Richert, 2013 .

ning classification of design Machine lear team members ’ body language patterns for real time emotional state detection

Conrad S. Tucker, Ishan Behoora, 2015 .

Automated Mapping of Product Features Mined From Online Customer Reviews to Engineering Product Characteristics

Conrad S. Tucker, Conrad S. Tucker, Sung Woo Kang, 2016 .

A Deep Learning Model for Mining Object-Energy Correlations Using Social Media Image Data

Matthew L. Dering, Kenneth M. Hopkinson, Conrad S. Tucker, 2018, Volume 1B: 38th Computers and Information in Engineering Conference.

Product Resynthesis : Knowledge 1 Discovery of the Value of 2 End-of-Life Assemblies

Conrad S. Tucker, N. Vasudevan, Sung woo Kang, 2016 .

An unsupervised machine learning method for discovering patient clusters based on genetic signatures

Conrad S. Tucker, Conrad S. Tucker, Scott Tucker, 2018, J. Biomed. Informatics.

Data trend mining for predictive systems design

Conrad S. Tucker, Conrad S. Tucker, 2011 .

Data-driven optimization of dynamic reconfigurable systems of systems.

Conrad S. Tucker, Conrad S. Tucker, John P. Eddy, 2010 .

A ReliefF attribute weighting and X-means clustering methodology for top-down product family optimization

Yuanhui Zhang, Conrad S. Tucker, Conrad S. Tucker, 2010, Engineering Optimization.

Data-Mining Driven Reconfigurable Product Family Design Framework for Aerodynamic Particle Separators

Yuanhui Zhang, Conrad S. Tucker, Conrad S. Tucker, 2008 .

Machine learning classification of medication adherence in patients with movement disorders using non-wearable sensors

Harriet Black Nembhard, Conrad S. Tucker, Xuemei Huang, 2015, Comput. Biol. Medicine.

An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages

Marcel Salathé, Conrad S. Tucker, Conrad S. Tucker, 2014, J. Biomed. Informatics.

The effects of player type on performance: A gamification case study

Conrad S. Tucker, Conrad S. Tucker, Christian E. Lopez, 2019, Comput. Hum. Behav..

Dynamic Rendering of Remote Indoor Environments Using Real-Time Point Cloud Data

Conrad S. Tucker, Conrad S. Tucker, Kevin Lesniak, 2018, J. Comput. Inf. Sci. Eng..

Investigating the Impact of Interactive Immersive Virtual Reality Environments in Enhancing Task Performance in Online Engineering Design Activities

Conrad S. Tucker, Conrad S. Tucker, Ajay Karthic B. Gopinath Bharathi, 2015 .

Random Forest Modeling for Survival Analysis of Cancer Recurrences

Conrad S. Tucker, Farhad Imani, Conrad Tucker, 2019, 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE).

Evaluation of biases in remote photoplethysmography methods

László A. Jeni, Conrad S. Tucker, Sakthi Kumar Arul Prakash, 2021, npj Digital Medicine.

A Data Mining Trajectory Clustering Methodology for Modeling Indoor Design Space Utilization

Timothy W. Simpson, Conrad S. Tucker, Conrad S. Tucker, 2013, Design Automation Conference.

Quantifying the Relevance of Product Feature Classification in Product Family Design

Conrad S. Tucker, Conrad S. Tucker, 2014 .

Optimal Product Portfolio Formulation by Merging Predictive Data Mining With Multilevel Optimization

Conrad S. Tucker, Conrad S. Tucker, Harrison Hyung Min Kim, 2008 .

An Analysis of Complexity Measures for Product Design and Development

Gül E. Okudan Kremer, Lourdes A. Medina, Conrad S. Tucker, 2012, DAC 2012.

Instantaneous Physiological Estimation using Video Transformers

László A. Jeni, Conrad S. Tucker, Ambareesh Revanur, 2022, ArXiv.

Mining Facial Keypoint Data: The Quest Toward Personalized Engineering Applications

Conrad S. Tucker, Conrad S. Tucker, Christian Enmanuel Lopez, 2019, Emotional Engineering, Vol.7.

Automated Concept Generation Based on Function-Form Synthesis

Conrad S. Tucker, Conrad S. Tucker, Sung Woo Kang, 2015, DAC 2015.

A quantitative method for evaluating the complexity of implementing and performing game features in physically-interactive gamified applications

Conrad S. Tucker, Conrad S. Tucker, Christian E. Lopez, 2017, Comput. Hum. Behav..

Modeling Individual-Level Infection Dynamics Using Social Network Information

Marcel Salathé, Conrad S. Tucker, Conrad S. Tucker, 2015, CIKM.

Quantifying Product Favorability and Extracting Notable Product Features Using Large Scale Social Media Data

Conrad S. Tucker, Conrad S. Tucker, Suppawong Tuarob, 2015, J. Comput. Inf. Sci. Eng..

Data-Driven Decision Tree Classification for Product Portfolio Design Optimization

Conrad S. Tucker, Conrad S. Tucker, Harrison Hyung Min Kim, 2009, J. Comput. Inf. Sci. Eng..

Mitigating Online Product Rating Biases Through the Discovery of Optimistic, Pessimistic, and Realistic Reviewers

Conrad S. Tucker, Conrad S. Tucker, Sunghoon Lim, 2017 .

A semantic network model for measuring engagement and performance in online learning platforms

Sung Hoon Lim, Conrad S. Tucker, Conrad S. Tucker, 2018, Comput. Appl. Eng. Educ..

Automated Discovery of Lead Users and Latent Product Features by Mining Large Scale Social Media Networks

Conrad S. Tucker, Conrad S. Tucker, Suppawong Tuarob, 2015 .

An automated approach to quantifying functional interactions by mining large-scale product specification data

Conrad S. Tucker, Conrad S. Tucker, Sung Woo Kang, 2016 .

Evaluating the Impact of Idea Dissemination Methods on Information Loss

Conrad S. Tucker, Conrad S. Tucker, Zixuan Victoria Zhao, 2019, J. Comput. Inf. Sci. Eng..

A Bayesian Sampling Method for Product Feature Extraction From Large-Scale Textual Data

Conrad S. Tucker, Conrad S. Tucker, Sunghoon Lim, 2016 .

An unsupervised machine learning model for discovering latent infectious diseases using social media data

Sung Hoon Lim, Conrad S. Tucker, Conrad S. Tucker, 2017, J. Biomed. Informatics.

Modeling the Semantic Structure of Textually Derived Learning Content and its Impact on Recipients' Response States

Conrad S. Tucker, Conrad S. Tucker, David Munoz, 2016 .

Automated Discovery of Product Feature Inferences Within Large-Scale Implicit Social Media Data

Conrad S. Tucker, Conrad S. Tucker, Suppawong Tuarob, 2018, J. Comput. Inf. Sci. Eng..

Automated discovery of product preferences in ubiquitous social media data: A case study of automobile market

Conrad S. Tucker, Suppawong Tuarob, Conrad S Tucker, 2016, 2016 International Computer Science and Engineering Conference (ICSEC).

A Product Feature Inference Model for Mining Implicit Customer Preferences Within Large Scale Social Media Networks

Conrad S. Tucker, Conrad S. Tucker, Suppawong Tuarob, 2015 .

TwittDict: Extracting Social Oriented Keyphrase Semantics from Twitter

Conrad S. Tucker, Conrad S. Tucker, Suppawong Tuarob, 2015, Proceedings of the ACL 2015 Workshop on Novel Computational Approaches to Keyphrase Extraction.

Discovering Next Generation Product Innovations by Identifying Lead User Preferences Expressed Through Large Scale Social Media Data

Conrad S. Tucker, Conrad S. Tucker, Suppawong Tuarob, 2014 .

Discovering health-related knowledge in social media using ensembles of heterogeneous features

Marcel Salathé, Conrad S. Tucker, Conrad S. Tucker, 2013, CIKM.

Special Issue: Artificial Intelligence and Engineering Design

James T. Allison, Conrad S. Tucker, M. Cardin, 2021, Journal of Mechanical Design.

Mining Twitter data for causal links between tweets and real-world outcomes

Conrad S. Tucker, Conrad S. Tucker, Sunghoon Lim, 2019, Expert Syst. Appl. X.

Exposure to Digital and Hands-on Delivery Modes in Engineering Design Education and Their Impact on Task Completion Efficiency

Gül E. Okudan Kremer, Conrad S. Tucker, Conrad S. Tucker, 2017, J. Integr. Des. Process. Sci..

An Introduction to the CLICK Approach: Leveraging Virtual Reality to Integrate the Industrial Engineering Curriculum

Conrad S. Tucker, Conrad S. Tucker, Christian Enmanuel Lopez, 2019 .

Quantifying the Price and Demand of Subassemblies in the End of Life Strategy of Product Resynthesis

Conrad S. Tucker, Conrad S. Tucker, Suja Rose John, 2014 .

Automatic Discovery of Service Name Replacements Using Ledger Data

Sechan Oh, Ray Strong, Conrad S. Tucker, 2015, 2015 IEEE International Conference on Services Computing.

Graph network for learning bi-directional physics

Conrad S. Tucker, Sakthi Kumar Arul Prakash, 2021, 2112.07054.

Graph network for simultaneous learning of forward and inverse physics pdf

Conrad S. Tucker, Sakthi Kumar Arul Prakash, Conrad Tucker, 2021, ArXiv.

A data mining methodology for predicting early stage Parkinson's disease using non-invasive, high-dimensional gait sensor data

Wang-Chien Lee, Conrad S. Tucker, Xuemei Huang, 2015, IIE transactions on healthcare systems engineering.

Mining Student-Generated Textual Data In MOOCS And Quantifying Their Effects on Student Performance and Learning Outcomes

Conrad S. Tucker, Conrad S. Tucker, Anna Divinsky, 2014 .

Toward Personalized Adaptive Gamification: A Machine Learning Model for Predicting Performance

Conrad S. Tucker, Conrad S. Tucker, Christian Enmanuel Lopez, 2020, IEEE Transactions on Games.

Increasing the veracity of event detection on social media networks through user trust modeling

Sven G. Bilen, Kenneth M. Hopkinson, Todd J. Bodnar, 2014, 2014 IEEE International Conference on Big Data (Big Data).

Machine learning classification of design team members' body language patterns for real time emotional state detection

Conrad S. Tucker, Conrad S. Tucker, Ishan Behoora, 2015 .

Trend Mining for Predictive Product Design

Conrad S. Tucker, Conrad S. Tucker, Harrison Hyung Min Kim, 2011 .

When to provide feedback? Exploring human-co-robot interactions in engineering enviroments

Conrad S. Tucker, Conrad S. Tucker, Christian Enmanuel Lopez, 2017 .

Data-Throughput Enhancement Using Data Mining-Informed Cognitive Radio

Khashayar Kotobi, Sven G. Bilen, Conrad S. Tucker, 2015 .

Discovering Discontinuity in Big Financial Transaction Data

Ray Strong, Conrad S. Tucker, Conrad S. Tucker, 2018, ACM Trans. Manag. Inf. Syst..

Bounded Kalman filter method for motion-robust, non-contact heart rate estimation.

Conrad S. Tucker, Conrad S Tucker, Sakthi Kumar Arul Prakash, 2018, Biomedical optics express.

A Comparative Study of Data-Intensive Demand Modeling Techniques in Relation to Product Design and Development

Christopher Hoyle, Conrad S. Tucker, Conrad S. Tucker, 2009, DAC 2009.

Knowledge discovery of game design features by mining user-generated feedback

Harriet Black Nembhard, Abhinav Singh, Conrad S. Tucker, 2016, Comput. Hum. Behav..

Classification of unlabeled online media

Conrad S. Tucker, Sakthi Kumar Arul Prakash, 2020, Scientific Reports.

Psychometric Analysis of Residence and MOOC Assessments

Conrad S. Tucker, E. Loken, Fridolin Linder, 2015 .

A Deep Learning Game Theoretic Model for Defending Against Large Scale Smart Grid Attacks

Conrad S. Tucker, Alexander J. Aved, James Cunningham, 2023, IEEE Transactions on Smart Grid.

Generative adversarial networks for increasing the veracity of big data

Matthew L. Dering, Conrad S. Tucker, Conrad S. Tucker, 2017, 2017 IEEE International Conference on Big Data (Big Data).

Student Perceptions of Tactile and Virtual Learning Approaches: What Can We Learn from their Viewpoint?

Conrad S. Tucker, Conrad S. Tucker, Kathy Schmidt Jackson, 2013 .

The development of product archaeology as a platform for contextualizing engineering design

Wei Chen, Gül E. Okudan Kremer, Steven B. Shooter, 2013 .

Digital Representation of Physical Artifacts: The Effect of Low Cost, High Accuracy 3D Scanning Technologies on Engineering Education, Student Learning and Design Evaluation

Conrad S. Tucker, Conrad S. Tucker, Nitish Vasudevan, 2013 .

Using Large-Scale Social Media Networks as a Scalable Sensing System for Modeling Real-Time Energy Utilization Patterns

Matthew L. Dering, Kenneth M. Hopkinson, Todd J. Bodnar, 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Implications of Generative Models in Government

Matthew L. Dering, Conrad S. Tucker, Conrad S. Tucker, 2017, AAAI Fall Symposia.