Christopher McComb

发表

Capturing Human Sequence-Learning Abilities in Configuration Design Tasks through Markov Chains

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2017 .

Data on the design of truss structures by teams of engineering students

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2018, Data in brief.

Using Hidden Markov Models to Uncover Underlying States in Neuroimaging Data for a Design Ideation Task

Christopher McComb, Kosa Goucher-Lambert, K. Goucher-Lambert, 2019, Proceedings of the Design Society: International Conference on Engineering Design.

A Review of Part Filtering Methods for Additive Manufacturing

Christopher McComb, Timothy W. Simpson, Kathryn Weed Jablokow, 2020, Design Automation Conference.

Towards an Ontology of Cognitive Assistants

Christopher McComb, Jessica Menold, Torsten Maier, 2019, Proceedings of the Design Society: International Conference on Engineering Design.

Designing Improved Teams for Crowdsourced Competitions

Christopher McComb, Torsten Maier, 2018 .

Comparison of Exams and Design Practica for Assessment in First Year Engineering Design Courses

Christopher McComb, Jessica Menold, Catherine G.P. Berdanier, 2020 .

MODELING A STRATEGIC HUMAN ENGINEERING DESIGN PROCESS: HUMAN-INSPIRED HEURISTIC GUIDANCE THROUGH LEARNED VISUAL DESIGN AGENTS

Christopher McComb, Jonathan Cagan, Lucas Puentes, 2020, Proceedings of the Design Society: DESIGN Conference.

Helping Teams Expand the Breadth of Their Solution Space Through Product Dissection: A Simulation Based Investigation

Christopher McComb, Scarlett R. Miller, Samuel Todd Hunter, 2018 .

Collaborating With Style: Using an Agent-Based Model to Simulate Cognitive Style Diversity in Problem Solving Teams

Christopher McComb, Kathryn Weed Jablokow, Samuel Lapp, 2019 .

Pulling at the Digital Thread: Exploring the Tolerance Stack Up Between Automatic Procedures and Expert Strategies in Scan to Print Processes

Christopher McComb, Jessica Menold, Nicholas Alexander Meisel, 2019 .

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

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

Expanding the Solution Space in Engineering Design Education: A Simulation-Based Investigation of Product Dissection

Christopher McComb, Scarlett R. Miller, Samuel Todd Hunter, 2019, Journal of Mechanical Design.

Heuristic-Guided Solution Search Through a Two-Tiered Design Grammar

Christopher McComb, Jonathan Cagan, Lucas Puentes, 2020, J. Comput. Inf. Sci. Eng..

Image collection of 3D-printed prototypes and non-3D-printed prototypes

Christopher McComb, Jessica Menold, Matthew Li, 2019, Data in brief.

Automated Heuristic Induction From Human Design Data

Christopher McComb, Jonathan Cagan, Lucas Puentes, 2020, Volume 9: 40th Computers and Information in Engineering Conference (CIE).

A Differential Game Approach to Dynamic Competitive Decisions Toward Human-Computer Collaboration

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2019, Volume 7: 31st International Conference on Design Theory and Methodology.

Validating a Tool for Predicting Problem-Specific Optimized Team Characteristics

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2017 .

Improving Irrigation in Remote Areas: Multi-Objective Optimization of a Treadle Pump

Christopher McComb, Kenji Shimada, Nathan G. Johnson, 2014, DAC 2014.

Towards an understanding of semantic memory during idea generation

Christopher McComb, Attakias T. Mertens, Christine A. Toh, 2020 .

Rolling with the punches: An examination of team performance in a design task subject to drastic changes

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2015 .

Data on the configuration design of internet-connected home cooling systems by engineering students

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2017, Data in brief.

Linking Properties of Design Problems to Optimal Team Characteristics

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2016 .

A Comparative Study of Virtual Reality and Computer-Aided Design to Evaluate Parts for Additive Manufacturing

Christopher McComb, Timothy W. Simpson, Nicholas A. Meisel, 2019, Volume 2A: 45th Design Automation Conference.

Learning to design from humans: Imitating human designers through deep learning

Christopher McComb, Jonathan Cagan, Ayush Raina, 2019, Journal of Mechanical Design.

Quantitative Comparison of High- and Low-Performing Teams in a Design Task Subject to Drastic Changes

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2014 .

“Thus, I Had to Go With What I Had”: A Multiple Methods Exploration of Novice Designers’ Articulation of Prototyping Decisions

Christopher McComb, Jessica Menold, Lisa Gardner, 2018 .

Studying Human Design Teams via Computational Teams of Simulated Annealing Agents

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2015 .

Utilizing Markov Chains to Understand Operation Sequencing in Design Tasks

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2017 .

Stochastic Stackelberg Games for Agent-Driven Robust Design

Christopher McComb, Jonathan Cagan, Sean C. Rismiller, 2020, Volume 11A: 46th Design Automation Conference (DAC).

Mining Design Heuristics for Additive Manufacturing Via Eye-Tracking Methods and Hidden Markov Modeling

Christopher McComb, Guha Manogharan, Catherine G. P. Berdanier, 2020 .

Toward the Rapid Design of Engineered Systems Through Deep Neural Networks

Christopher McComb, Christopher McComb, 2018, Design Computing and Cognition '18.

Drawing Inspiration From Human Design Teams for Better Search and Optimization: The Heterogeneous Simulated Annealing Teams Algorithm

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2016 .

Scenario-Based Robustness Analysis of Optimized I.D.E.-Style Treadle Pump Designs

Christopher McComb, Nathan G. Johnson, Brandon T. Gorman, 2016 .

KABOOM: an agent-based model for simulating cognitive style in team problem solving

Christopher McComb, Samuel Lapp, Kathryn Jablokow, 2019, Design Science.

Complexity Reduction in Mass Customization to Facilitate Better Decision Support

Christopher McComb, Jai Nath Banerjee, Madhura Mundale, 2019, DAC 2019.

A Two-Tiered Grammatical Approach for Agent-Based Computational Design

Christopher McComb, Jonathan Cagan, Lucas Puentes, 2018, Volume 2A: 44th Design Automation Conference.

Data-Driven Heuristic Induction From Human Design Behavior

Christopher McComb, Jonathan Cagan, Lucas Puentes, 2020, J. Comput. Inf. Sci. Eng..

Design Strategy Transfer in Cognitively-Inspired Agents

Christopher McComb, Jonathan Cagan, Ayush Raina, 2018, Volume 2A: 44th Design Automation Conference.

Learning to design from humans: Imitating human designers through deep learning pdf

Christopher McComb, Jonathan Cagan, Ayush Raina, 2019, Journal of Mechanical Design.

Predicting Part Mass, Required Support Material, and Build Time via Autoencoded Voxel Patterns

Christopher McComb, Timothy W. Simpson, Christian Murphy, 2018 .

Using Deep Image Colorization to Predict Microstructure-Dependent Strain Fields

Christopher McComb, Saurabh Basu, Pranav Milind Khanolkar, 2020, Procedia Manufacturing.

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.

HETEROGENEOUS SIMULATED ANNEALING TEAMS: AN OPTIMIZING SEARCH ALGORITHM INSPIRED BY ENGINEERING DESIGN TEAMS

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2015 .

Deriving Metamodels to Relate Machine Learning Quality to Design Repository Characteristics in the Context of Additive Manufacturing

Christopher McComb, Timothy W. Simpson, Glen Williams, 2020, DAC 2020.

Using Adaption-Innovation Theory to Simulate Robustness in Design Teams

Christopher McComb, Noriana Radwan, 2020, ICCC.

Optimizing Design Teams Based on Problem Properties: Computational Team Simulations and an Applied Empirical Test

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2017 .

Design Practica as Authentic Assessments in First-year Engineering Design Courses

Christopher McComb, Jessica Menold, Catherine G.P. Berdanier, 2018 .

An analysis of design process and performance in distributed data science teams

Christopher McComb, Joanna DeFranco, Torsten Maier, 2019 .

Transferring Design Strategies From Human To Computer And Across Design Problems

Christopher McComb, Jonathan Cagan, Ayush Raina, 2019 .

Lifting the Veil: Drawing insights about design teams from a cognitively-inspired computational model

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2015 .

Design Repository Effectiveness for 3D Convolutional Neural Networks: Application to Additive Manufacturing

Christopher McComb, Timothy W. Simpson, Nicholas Alexander Meisel, 2019, Journal of Mechanical Design.

Opportunities for Natural Language Processing in Qualitative Engineering Education Research: Two Examples

Christopher McComb, Eric Baker, Catherine G. P. Berdanier, 2018, 2018 IEEE Frontiers in Education Conference (FIE).

Mining Process Heuristics From Designer Action Data via Hidden Markov Models

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2017 .

Identifying technical and economic improvements to the MoneyMaker Hip pump through multi-objective optimization

Christopher McComb, Kenji Shimada, Nathan G. Johnson, 2014, IEEE Global Humanitarian Technology Conference (GHTC 2014).

Multi-objective optimization and scenario-based robustness analysis of the MoneyMaker Hip Pump

Christopher McComb, Kenji Shimada, Nathan G. Johnson, 2018 .

Eliciting configuration design heuristics with hidden Markov models

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2017 .

Towards Enhanced Creativity in Interface Design through Automated Usability Evaluation

Christopher McComb, Farzaneh Oghazian, Xiaomei Tan, 2020, ICCC.

Evaluating Idea Quantity and Variety When Using Digital Collaboration Tools to Support Brainstorming in Non-Collocated Teams

Christopher McComb, Jessica Menold, Sarah Ritter, 2019 .

Goal-Directed Design Agents: Integrating Visual Imitation with One-Step Lookahead Optimization for Generative Design pdf

Christopher McComb, Jonathan Cagan, Lucas Puentes, 2021, Journal of Mechanical Design.

Human Versus Artificial Intelligence: A Data-Driven Approach to Real-Time Process Management During Complex Engineering Design

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2021, Journal of Mechanical Design.

An Adversarial Agent-Based Design Method Using Stochastic Stackelberg Game Conditions

Christopher McComb, Jonathan Cagan, Sean C. Rismiller, 2021 .

Design Strategy Network: A deep hierarchical framework to represent generative design strategies in complex action spaces pdf

Christopher McComb, Jonathan Cagan, Ayush Raina, 2021, Journal of Mechanical Design.

A Query Conundrum: The Mental Challenges of Using a Cognitive Assistant

Christopher McComb, Jessica Menold, Saeed Abdullah, 2021, SN Computer Science.

COMPARING DESIGN OUTCOMES ACHIEVED BY TEAMS OF EXPERT AND NOVICE DESIGNERS THROUGH AGENT-BASED SIMULATION

Christopher McComb, Gaetano Cascini, Harshika Singh, 2021, Proceedings of the Design Society.

A cautionary tale about the impact of AI on human design teams

Christopher McComb, Jonathan Cagan, Ayush Raina, 2021 .

A MULTI-AGENT REINFORCEMENT LEARNING FRAMEWORK FOR INTELLIGENT MANUFACTURING WITH AUTONOMOUS MOBILE ROBOTS

Christopher McComb, Tushar Sharma, Akash Agrawal, 2021, Proceedings of the Design Society.

Lost in Translation: Examining the Complex Relationship Between Prototyping and Communication

Christopher McComb, Jessica Menold, Catherine G. P. Berdanier, 2021 .

Influencers in design teams: a computational framework to study their impact on idea generation

Christopher McComb, Gaetano Cascini, Harshika Singh, 2021, Artificial Intelligence for Engineering Design, Analysis and Manufacturing.

NOVICE DESIGNERS' USE OF PROTOTYPES AS COMMUNICATION TOOLS

Christopher McComb, Jessica Menold, Carlye Lauff, 2021, Proceedings of the Design Society.

COMMUNICATION IN AI-ASSISTED TEAMS DURING AN INTERDISCIPLINARY DRONE DESIGN PROBLEM

Christopher McComb, Jonathan Cagan, Joshua T. Gyory, 2021, Proceedings of the Design Society.

A strategic decision-making architecture toward hybrid teams for dynamic competitive problems

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky, 2021, Decis. Support Syst..

When faced with increasing complexity: The effectiveness of AI assistance for drone design

Christopher McComb, Jonathan Cagan, Hannah Nolte, 2021 .

FAIRNESS AND MANIPULATION: AN EMPIRICAL STUDY OF ARROW’S IMPOSSIBILITY THEOREM

Christopher McComb, Jonathan Cagan, Kosa Goucher-Lambert, 2015 .

Impossible by design? Fairness, strategy, and Arrow’s impossibility theorem

Christopher McComb, Jonathan Cagan, Kosa Goucher-Lambert, 2017, Design Science.

Topic Modeling and Sentiment Analysis of Social Media Data to Drive Experiential Redesign

Christopher McComb, Akash Agrawal, Binyang Song, 2020, Volume 11A: 46th Design Automation Conference (DAC).