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Research Output 2010 2019

  • 222 Citations
  • 10 h-Index
  • 19 Conference contribution
  • 10 Article
2019

FEA-net: A deep convolutional neural network with physics prior for efficient data driven pde learning

Yao, H., Ren, Y. & Liu, Y., Jan 1 2019, AIAA Scitech 2019 Forum. American Institute of Aeronautics and Astronautics Inc, AIAA, (AIAA Scitech 2019 Forum).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Physics
Neural networks
Finite element method
Convolution
Partial differential equations
1 Citation (Scopus)

One-shot generation of near-optimal topology through theory-driven machine learning

Cang, R., Yao, H. & Ren, Y., Apr 1 2019, In : CAD Computer Aided Design. 109, p. 12-21 10 p.

Research output: Contribution to journalArticle

Learning systems
Supervised learning
Topology
Students
Neural networks
2018
7 Citations (Scopus)

An indirect design representation for topology optimization using variational autoencoder and style transfer

Guo, T., Lohan, D. J., Allison, J. T., Cang, R. & Ren, Y., Jan 1 2018, AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials. 210049 ed. American Institute of Aeronautics and Astronautics Inc, AIAA

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shape optimization
Topology
Computational efficiency
Heat conduction
Scattering
10 Citations (Scopus)
Heterogeneous Materials
Generative Models
Physical property
Physical properties
physical properties

Optimal stiffness design for an exhaustive parallel compliance matrix in multiactuator robotic limbs

Cahill, N. M., Sugar, T., Ren, Y. & Schroeder, K., Jun 1 2018, In : Journal of Mechanisms and Robotics. 10, 3, 031014.

Research output: Contribution to journalArticle

Robotics
Stiffness
Robots
Trajectories
Dynamic models
2017
1 Citation (Scopus)

Mechanical specialization of robotic limbs

Cahill, N. M., Ren, Y. & Sugar, T., Jul 21 2017, ICRA 2017 - IEEE International Conference on Robotics and Automation. Institute of Electrical and Electronics Engineers Inc., p. 4187-4192 6 p. 7989482

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Robotics
Geometry
Subroutines
Gears
Electric power utilization
1 Citation (Scopus)

Scalable microstructure reconstruction with multi-scale pattern preservation

Cang, R., Vipradas, A. & Ren, Y., Jan 1 2017, 43rd Design Automation Conference. American Society of Mechanical Engineers (ASME), Vol. 2B-2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Preservation
Microstructure
Training Samples
Feature Space
Material Design

Topology optimization of structural systems considering both compliance and input observability

Ren, Y., Yao, H. & Lin, X., Jan 1 2017, Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications. American Society of Mechanical Engineers, Vol. 2.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Observability
Shape optimization
Topology
Controllability
3D printers

Towards understanding human decisions in human-robot interactions

Zhang, W., Yang, Y. & Ren, Y., Jan 1 2017, Aerospace Applications; Advances in Control Design Methods; Bio Engineering Applications; Advances in Non-Linear Control; Adaptive and Intelligent Systems Control; Advances in Wind Energy Systems; Advances in Robotics; Assistive and Rehabilitation Robotics; Biomedical and Neural Systems Modeling, Diagnostics, and Control; Bio-Mechatronics and Physical Human Robot; Advanced Driver Assistance Systems and Autonomous Vehicles; Automotive Systems. American Society of Mechanical Engineers, Vol. 1.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Human robot interaction
Robots
Grippers
Feedforward control
Real time control
2016
18 Citations (Scopus)

EcoRacer: Game-Based Optimal Electric Vehicle Design and Driver Control Using Human Players

Ren, Y., Bayrak, A. E. & Papalambros, P. Y., Jun 1 2016, In : Journal of Mechanical Design, Transactions of the ASME. 138, 6

Research output: Contribution to journalArticle

Electric vehicles
Powertrains
Global optimization
13 Citations (Scopus)

Improving Design Preference Prediction Accuracy Using Feature Learning

Burnap, A., Pan, Y., Liu, Y., Ren, Y., Lee, H., Gonzalez, R. & Papalambros, P. Y., Jul 1 2016, In : Journal of Mechanical Design, Transactions of the ASME. 138, 7, 071404.

Research output: Contribution to journalArticle

Principal component analysis
Automobiles
Visualization
Decomposition
12 Citations (Scopus)

Public investment and electric vehicle design: A model-based market analysis framework with application to a USA-China comparison study

Kang, N., Ren, Y., Feinberg, F. M. & Papalambros, P. Y., Jan 1 2016, In : Design Science. 2, e6.

Research output: Contribution to journalArticle

Electric Vehicle
Electric vehicles
China
Model-based
Profitability
16 Citations (Scopus)

Topology Generation for Hybrid Electric Vehicle Architecture Design

Bayrak, A. E., Ren, Y. & Papalambros, P. Y., Aug 1 2016, In : Journal of Mechanical Design, Transactions of the ASME. 138, 8, 081401.

Research output: Contribution to journalArticle

Powertrains
Hybrid vehicles
Topology
Hybrid powertrains
Passenger cars
2015
2 Citations (Scopus)

A framework for quantitative analysis of government policy influence on electric vehicle market

Kang, N., Emmanoulopoulos, M., Ren, Y., Feinberg, F. M. & Papalambros, P. Y., 2015, In : Unknown Journal. 5, DS 80-05, p. 1-10 10 p.

Research output: Contribution to journalArticle

Electric Vehicle
Policy Making
Electric vehicles
Quantitative Analysis
Chemical analysis
5 Citations (Scopus)

EcoRacer: Game-based optimal electric vehicle design and driver control using human players

Ren, Y., Bayrak, A. E. & Papalambros, P. Y., 2015, 41st Design Automation Conference. American Society of Mechanical Engineers (ASME), Vol. 2A-2015.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Electric Vehicle
Electric vehicles
Driver
Game
Control Problem
31 Citations (Scopus)

When crowdsourcing fails: A study of expertise on crowdsourced design evaluation

Burnap, A., Ren, Y., Gerth, R., Papazoglou, G., Gonzalez, R. & Papalambros, P. Y., 2015, In : Journal of Mechanical Design, Transactions of the ASME. 137, 3, 031101.

Research output: Contribution to journalArticle

2014

Enhanced adaptive choice-based conjoint analysis incorporating engineering knowledge

Ren, Y. & Papalambros, P. Y., 2014, 40th Design Automation Conference. American Society of Mechanical Engineers (ASME), Vol. 2A.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Conjoint Analysis
Knowledge Engineering
Knowledge engineering
Questionnaire
Active Learning
1 Citation (Scopus)

Improving preference prediction accuracy with feature learning

Burnap, A., Ren, Y., Lee, H., Gonzalez, R. & Papalambros, P. Y., 2014, 40th Design Automation Conference. American Society of Mechanical Engineers (ASME), Vol. 2A.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Prediction
Passenger cars
High-dimensional
Boltzmann Machine
Consumer Behaviour
9 Citations (Scopus)

Optimal dual-mode hybrid electric vehicle powertrain architecture design for a variety of loading scenarios

Bayrak, A. E., Ren, Y. & Papalambros, P. Y., 2014, 16th International Conference on Advanced Vehicle Technologies; 11th International Conference on Design Education; 7th Frontiers in Biomedical Devices. American Society of Mechanical Engineers (ASME), Vol. 3.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hybrid Electric Vehicle
Powertrains
Hybrid vehicles
Scenarios
Military applications
2013
3 Citations (Scopus)

A scalable preference elicitation algorithm using group generalized binary search

Ren, Y., Scott, C. & Papalambros, P. Y., 2013, 39th Design Automation Conference. American Society of Mechanical Engineers, Vol. 3 B. V03BT03A005

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Binary search
Elicitation
Query
Global optimization
Global Optimization
12 Citations (Scopus)

A simulation based estimation of crowd ability and its influence on crowdsourced evaluation of design concepts

Burnap, A., Ren, Y., Papalambros, P. Y., Gonzalez, R. & Gerth, R., 2013, 39th Design Automation Conference. American Society of Mechanical Engineers, Vol. 3 B. V03BT03A004

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Bayesian networks
Evaluation
Bayesian Model
Bayesian Networks
Network Model
28 Citations (Scopus)

Design of hybrid-electric vehicle architectures using auto-generation of feasible driving modes

Bayrak, A. E., Ren, Y. & Papalambros, P. Y., 2013, 15th International Conference on Advanced Vehicle Technologies; 10th International Conference on Design Education; 7th International Conference on Micro- and Nanosystems. American Society of Mechanical Engineers, Vol. 1. V001T01A005

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hybrid Electric Vehicle
Hybrid vehicles
Engines
Cycle
Powertrains
15 Citations (Scopus)

Quantification of perceptual design attributes using a crowd

Ren, Y., Burnap, A. & Papalambros, P., 2013, Proceedings of the International Conference on Engineering Design, ICED. Vol. 6 DS75-06. p. 139-148 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Quantification
Attribute
Railroad cars
Shape Design
Statistical Learning
2012
6 Citations (Scopus)

On design preference elicitation with crowd implicit feedback

Ren, Y. & Papalambros, P. Y., 2012, Proceedings of the ASME Design Engineering Technical Conference. PARTS A AND B ed. Vol. 3. p. 541-551 11 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Elicitation
Query
Feedback
Interaction
Black-box Optimization

On the use of active learning in engineering design

Ren, Y. & Papalambros, P. Y., 2012, Proceedings of the ASME Design Engineering Technical Conference. PARTS A AND B ed. Vol. 3. p. 89-98 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Active Learning
Conjoint Analysis
Engineering Design
D-optimal Design
Marketing
2011
18 Citations (Scopus)

A design preference elicitation query as an optimization process

Ren, Y. & Papalambros, P. Y., 2011, In : Journal of Mechanical Design, Transactions of the ASME. 133, 11, 111004.

Research output: Contribution to journalArticle

Global optimization
Human computer interaction
Support vector machines
Feedback
Problem-Based Learning
5 Citations (Scopus)

Design preference elicitation: Exploration and learning

Ren, Y. & Papalambros, P., 2011, ICED 11 - 18th International Conference on Engineering Design - Impacting Society Through Engineering Design. PART 2 ed. Vol. 10. p. 149-158 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Human computer interaction
Evolutionary algorithms
Automobiles
Feedback
5 Citations (Scopus)

Design preference elicitation using efficient global optimization

Ren, Y. & Papalambros, P. Y., 2011, Proceedings of the ASME Design Engineering Technical Conference. PARTS A AND B ed. Vol. 5. p. 591-600 10 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Elicitation
Global optimization
Global Optimization
Merit Function
User Preferences
2010
3 Citations (Scopus)

Design preference elicitation, derivative-free optimization and support vector machine search

Ren, Y. & Papalambros, P. Y., 2010, Proceedings of the ASME Design Engineering Technical Conference. PARTS A AND B ed. Vol. 1. p. 335-343 9 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Derivative-free Optimization
Elicitation
Support vector machines
Support Vector Machine
Derivatives