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IDEAL Attends IDETC 2024

IDEAL members and alumni attended the International Design Engineering Technical Conferences (IDETC) 2024 in Washington, DC, and collected several awards. Congratulations to all of the awardees!

  • Harrison Kim (UIUC), Design Automation Award
  • Hongyi Xu (U of Conn), DAC Young Investigator Award
  • Faez Ahmed (MIT), DTM Young Investigator Award
  • Liwei Wang (CMU), the DAC Dissertation Award
  • Anton Von Beek (UCD, Ireland), DAC Best Paper Award
  • Christopher Luey, Undergraduate Student Design Essay Competition Award
  • Vispi Karkaria, Graduate Student Research Design Essay Competition Award

Prof. Chen Elected to The Academy

Congratulations to Prof. Chen for being elected as a member of the American Academy of Arts and Sciences, one of the nation’s oldest and most prestigious honorary societies. The Academy celebrates the importance of knowledge and the belief that the arts and sciences are vital to a free, independent, and virtuous society. We are proud of Prof. Chen’s achievements and her contributions to the field of engineering design.

More details can be found at: Three McCormick Faculty Elected to American Academy of Arts and Sciences

Vispi Receives Best Presentation Award at NAMRC

Vispi Neville Karkaria receives the first prize Presentation Award at the annual North American Manufacturing Research Conference (NAMRC) 2024 for his paper titled, “Towards a Digital Twin Framework in Additive Manufacturing: Machine Learning and Bayesian Optimization for Time Series Process Optimization” (Karkaria, V., Goeckner, A., Zha, R., Chen, J., Zhang, J., Zhu, Q., Cao, J., Gao, R.X. and Chen, W.). This research advances Additive Manufacturing Process by integrating real-time monitoring, machine learning, and process optimization within a Digital Twin framework. Nine first-authored students were invited to compete for the prize based on the reviews of 300+ papers received by the conference. Vispi Karkaria was selected as the winner based on the competition of oral presentations, judged based on clarity, originality, and scientific merit by a panel from the NAMRI/SME Honors Committee.

IDEAL Attends REMADE Conference 2024

Our lab member Vispi Karkaria presented a pioneering digital twin technology at the 2024 REMADE Circular Economy Technology Summit & Conference, hosted in Washington, D.C., from April 10-11. The technology, designed for predictive maintenance, specifically targets tire health monitoring to improve automotive safety and efficiency.

Our team’s predictive digital twin concept functions through three crucial steps. Initially, we tackle data complexity by employing reduction techniques to concisely represent physical tires using historical usage and telematics data. This foundation allows us to train a transformer-based model offline, predicting future tire health while quantifying uncertainties to provide confident predictions. In the second step, we integrate real-time data updates into the digital twin, using a hybrid modeling approach to maintain accuracy over the tire’s lifecycle. Finally, we implement a Tire State Decision Algorithm, which strategically uses the model’s forecasts to determine the most effective times for tire maintenance or replacement. This method not only predicts the state of tire health but also continually refines its representation and maintenance decisions, optimizing operations and prolonging tire life.

Doksoo Defends his Ph.D. Dissertation

Our lab member Doksoo Lee successfully defended his Ph.D. thesis on November 9th under the title Data-Driven Inverse Design of Metamaterials: Exploring Complex Physical Fields Beyond Homogenization Assumptions. Congratulations, Doksoo! He will be continuing in our lab as a Postdoc!

IDEAL Attends SES Conference 2023

We attended the Society of Engineering Science (SES) Conference at University of Minnesota, Minneapolis. The conference was held between October 8-11, 2023. In total, IDEAL members participated with 7 presentation which are named below.

SES 2023 Presentations
  • Doksoo Lee, Lu Zhang (Lehigh), Wei Chen,  Yue Yu (Lehigh). “A Neural Operator Approach to Learning Drastically Varying Spatial Behavior in Photonic Metamaterials.
  • Akash Pandey, Wei Chen, Sinan Keten. “Primary sequence-based interpretable machine learning model for the mechanical property prediction in spider silk”.
  • Tuba Dolar, Jie Chen, Wei Chen. “Uncertainty Quantification Driven Dataset Balancing for Improving Machine Learning Accuracy”.
  • Yi-Ping Chen, Liwei Wang, Yigitcan Comlek, Wei Chen. “A Unified Adaptive Sampling Framework for Multi-Fidelity Modeling and Bayesian Optimization via Latent Variable Gaussian Process”.
  • Liwei Wang, Yilong Chang (Stanford), Shuai Wu (Stanford), Ruike Zhao (Stanford), Wei Chen. “Physics-aware differentiable inverse design of magnetically actuated kirigami for shape morphing”.
  • Wei (Wayne) Chen (Texas A&M), Yu-Chin Chan (Siemens), Daicong Da (Boise State), Wei Chen . “Generative Design of Multiscale Heterostructures with Blended Multiclass Metamaterials”.
  • Prajakta Prabhune (Duke), Yigitcan Comlek, Cate Brinson (Duke), Linda Schadler (Vermont), Ravishankar Sundararaman (RPI), Wei Chen . “Tailoring Microstructures and interfaces to design polymer nanodielectrics for capacitive energy storage”.

IDEAL Attends IDETC 2023

We attended the International Design Engineering Technical Conferences (IDETC) 2023 in Boston Park Plaza, Boston, Massachusetts. The conference was held between August 20-23, 2023. In total, IDEAL members presented 3 papers which are shown below. Our members also collected few awards during the conference. Yigitcan received the “Paper of Distinction” recognition,  Jie and Joy received the 3rd place in the ASME-CIE Data Hackathon on “Automating Material Selection for Product Design”,  and Tuba received the Broadening Participation (BPart) Fellowship and Mentorship award.

Prof. Chen participated in a panel under the topic “Digital Twin for Smart Manufacturing”, which aimed to  discuss challenges and technical approaches in the digital twin area.

IDETC 2023 Papers
  • Yigitcan Comlek Liwei Wang, Wei Chen. “Mixed-Variable Global Sensitivity Analysis With Applications to Data Driven Combinatorial Materials Design” (DETC2023-110756).
  • Jie Chen, Yongming Liu, Wei Chen. “Neural Optimization Machine for Design With Neural Network Based Objectives” (DETC2023-114605).
  • Tuba Dolar, Doksoo Lee, Wei Chen. “Interpretable Neural Network Analyses for Understanding Complex Physical Interactions in Engineering Design” (DETC2023-115103).