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Christopher McComb
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2020 – today
- 2025
- [j13]Vasvi Agarwal, Kathryn W. Jablokow, Christopher McComb:
Putting the Ghost in the Machine: Emulating Cognitive Style in Large Language Models. J. Comput. Inf. Sci. Eng. 25(2) (2025) - 2024
- [j12]Jiangce Chen, Justin Pierce, Glen Williams, Timothy W. Simpson, Nicholas A. Meisel, Sneha Prabha Narra, Christopher McComb:
Accelerating Thermal Simulations in Additive Manufacturing by Training Physics-Informed Neural Networks With Randomly Synthesized Data. J. Comput. Inf. Sci. Eng. 24(1) (2024) - [c12]Zeda Xu, John Liechty, Sebastian Benthall, Nicholas Skar-Gislinge, Christopher McComb:
GARCH-Informed Neural Networks for Volatility Prediction in Financial Markets. ICAIF 2024: 600-607 - [i13]Jiangce Chen, Wenzhuo Xu, Zeda Xu, Noelia Grande Gutiérrez, Sneha Prabha Narra, Christopher McComb:
Data Scoping: Effectively Learning the Evolution of Generic Transport PDEs. CoRR abs/2405.01319 (2024) - [i12]Kevin Ma, Daniele Grandi, Christopher McComb, Kosa Goucher-Lambert:
Exploring the Capabilities of Large Language Models for Generating Diverse Design Solutions. CoRR abs/2405.02345 (2024) - [i11]Daniele Grandi, Yash Patawari Jain, Allin Groom, Brandon Cramer, Christopher McComb:
Evaluating Large Language Models for Material Selection. CoRR abs/2405.03695 (2024) - [i10]Martha Baldwin, Nicholas A. Meisel, Christopher McComb:
Smooth Like Butter: Evaluating Multi-Lattice Transitions in Property-Augmented Latent Spaces. CoRR abs/2407.08074 (2024) - [i9]Yash Patawari Jain, Daniele Grandi, Allin Groom, Brandon Cramer, Christopher McComb:
MSEval: A Dataset for Material Selection in Conceptual Design to Evaluate Algorithmic Models. CoRR abs/2407.09719 (2024) - 2023
- [j11]Akash Agrawal, Christopher McComb:
Reinforcement Learning for Efficient Design Space Exploration With Variable Fidelity Analysis Models. J. Comput. Inf. Sci. Eng. 23(4) (2023) - [j10]Martha Baldwin, Nicholas A. Meisel, Christopher McComb:
AddLat2D the 2D Lattice Generator. Softw. Impacts 17: 100567 (2023) - [c11]Wenzhuo Xu, Noelia Grande Gutiérrez, Christopher McComb:
MegaFlow2D: A Parametric Dataset for Machine Learning Super-resolution in Computational Fluid Dynamics Simulations. CPS-IoT Week Workshops 2023: 100-104 - [c10]Adam B. Cobb, Anirban Roy, Daniel Elenius, F. Michael Heim, Brian Swenson, Sydney Whittington, James D. Walker, Theodore Bapty, Joseph Hite, Karthik Ramani, Christopher McComb, Susmit Jha:
AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs. NeurIPS 2023 - [c9]Maral Doctorarastoo, Katherine A. Flanigan, Mario Bergés, Christopher McComb:
Modeling Human Behavior in Cyber-Physical-Social Infrastructure Systems. BuildSys@SenSys 2023: 370-376 - [c8]John Martins, Katherine A. Flanigan, Christopher McComb:
Skeleton-based Human Action Recognition in a Thermal Comfort Context. BuildSys@SenSys 2023: 377-384 - [c7]Maral Doctorarastoo, Katherine A. Flanigan, Mario Bergés, Christopher McComb:
Exploring the Potentials and Challenges of Cyber-Physical-Social Infrastructure Systems for Achieving Human-Centered Objectives. BuildSys@SenSys 2023: 385-389 - [i8]Kevin Ma, Daniele Grandi, Christopher McComb, Kosa Goucher-Lambert:
Conceptual Design Generation Using Large Language Models. CoRR abs/2306.01779 (2023) - [i7]Adam D. Cobb, Anirban Roy, Daniel Elenius, F. Michael Heim, Brian Swenson, Sydney Whittington, James D. Walker, Theodore Bapty, Joseph Hite, Karthik Ramani, Christopher McComb, Susmit Jha:
AircraftVerse: A Large-Scale Multimodal Dataset of Aerial Vehicle Designs. CoRR abs/2306.05562 (2023) - [i6]Martha Baldwin, Nicholas A. Meisel, Christopher McComb:
Smoothing the Rough Edges: Evaluating Automatically Generated Multi-Lattice Transitions. CoRR abs/2306.10055 (2023) - [i5]Jiangce Chen, Wenzhuo Xu, Martha Baldwin, Björn Nijhuis, Ton van den Boogaard, Noelia Grande Gutiérrez, Sneha Prabha Narra, Christopher McComb:
Capturing Local Temperature Evolution during Additive Manufacturing through Fourier Neural Operators. CoRR abs/2307.01804 (2023) - 2022
- [j9]Torsten Maier, Jessica Menold, Christopher McComb:
The Relationship Between Performance and Trust in AI in E-Finance. Frontiers Artif. Intell. 5 (2022) - [j8]Glen Williams, Nicholas A. Meisel, Timothy W. Simpson, Christopher McComb:
Design for Artificial Intelligence: Proposing a Conceptual Framework Grounded in Data Wrangling. J. Comput. Inf. Sci. Eng. 22(1) (2022) - [j7]Matthew Li, Christopher McComb:
Using Physics-Informed Generative Adversarial Networks to Perform Super-Resolution for Multiphase Fluid Simulations. J. Comput. Inf. Sci. Eng. 22(4) (2022) - [c6]Sebastian Benthall, Christopher D. Carroll, Zachary David, John Liechty, Alan Lujan, Christopher McComb, Nicholas Skar-Gislinge:
Simulating Heterogeneous Portfolio Choices and Financial Market Outcomes. AMPM@JURIX 2022 - [i4]Ayush Raina, Jonathan Cagan, Christopher McComb:
Learning to design without prior data: Discovering generalizable design strategies using deep learning and tree search. CoRR abs/2211.15068 (2022) - 2021
- [j6]Harshika Singh, Gaetano Cascini, Christopher McComb:
Influencers in design teams: a computational framework to study their impact on idea generation. Artif. Intell. Eng. Des. Anal. Manuf. 35(3): 332-352 (2021) - [j5]Mohammad Alsager Alzayed, Scarlett R. Miller, Christopher McComb:
Empathic creativity: can trait empathy predict creative concept generation and selection? Artif. Intell. Eng. Des. Anal. Manuf. 35(4): 369-383 (2021) - [j4]Alparslan Emrah Bayrak, Christopher McComb, Jonathan Cagan, Kenneth Kotovsky:
A strategic decision-making architecture toward hybrid teams for dynamic competitive problems. Decis. Support Syst. 144: 113490 (2021) - [j3]Lucas Puentes, Jonathan Cagan, Christopher McComb:
Data-Driven Heuristic Induction From Human Design Behavior. J. Comput. Inf. Sci. Eng. 21(2) (2021) - [j2]Torsten Maier, Saeed Abdullah, Christopher McComb, Jessica Menold:
A Query Conundrum: The Mental Challenges of Using a Cognitive Assistant. SN Comput. Sci. 2(3): 194 (2021) - [i3]Ayush Raina, Lucas Puentes, Jonathan Cagan, Christopher McComb:
Goal-Directed Design Agents: Integrating Visual Imitation with One-Step Lookahead Optimization for Generative Design. CoRR abs/2110.03223 (2021) - [i2]Ayush Raina, Jonathan Cagan, Christopher McComb:
Design Strategy Network: A deep hierarchical framework to represent generative design strategies in complex action spaces. CoRR abs/2110.03760 (2021) - 2020
- [j1]Lucas Puentes, Jonathan Cagan, Christopher McComb:
Heuristic-Guided Solution Search Through a Two-Tiered Design Grammar. J. Comput. Inf. Sci. Eng. 20(1) (2020) - [c5]Catherine G. P. Berdanier, Christopher M. McComb, Weiwei Zhu:
Natural Language Processing for Theoretical Framework Selection in Engineering Education Research. FIE 2020: 1-7 - [c4]Snehal Dhengre, Jayant Mathur, Farzaneh Oghazian, Xiaomei Tan, Christopher McComb:
Towards Enhanced Creativity in Interface Design through Automated Usability Evaluation. ICCC 2020: 366-369 - [c3]Noriana Radwan, Christopher McComb:
Using Adaption-Innovation Theory to Simulate Robustness in Design Teams. ICCC 2020: 386-389
2010 – 2019
- 2019
- [i1]Ayush Raina, Christopher McComb, Jonathan Cagan:
Learning to design from humans: Imitating human designers through deep learning. CoRR abs/1907.11813 (2019) - 2018
- [c2]Catherine G. P. Berdanier, Eric Baker, Weiqin Wang, Christopher McComb:
Opportunities for Natural Language Processing in Qualitative Engineering Education Research: Two Examples. FIE 2018: 1-6 - 2014
- [c1]Christopher McComb, Pablo S. Santaeufemia, Nathan G. Johnson, Kenji Shimada:
Identifying technical and economic improvements to the MoneyMaker Hip pump through multi-objective optimization. GHTC 2014: 338-344
Coauthor Index
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