Yuquan Meng has successfully defended his doctoral dissertation titled “Physics-Informed Machine Learning for Smart Decision-Making in Ultrasonic Metal Welding.” The defense was conducted before an esteemed Examination Committee consisting of Prof. Chenhui Shao, Prof. Placid Ferreira, Prof. Srinivasa Salapaka, and Prof. Pingfeng Wang. In his research, Yuquan Meng has made significant contributions to the field […]
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Paper on End-to-end Online Quality Prediction for Ultrasonic Metal Welding published in JMP
Our paper titled “End-to-end online quality prediction for ultrasonic metal welding using sensor fusion and deep learning” has been published on Journal of Manufacturing Processes. The paper was co-authored by Yulun Wu, Yuquan Meng and Prof. Chenhui Shao. In industrial-scale production applications of ultrasonic metal welding (UMW), there is a strong need for predicting joint […]
Kuan-Chieh will start his internship at Intel this summer
Kuan-Chieh will start an internship position at Intel in summer 2023. He will work with the Logic Technology Development Group to analyze epitaxially grown films and develop an AI algorithm to predict the quality based on process conditions. His Ph.D. research focuses on data efficiency in manufacturing quality monitoring and real-time parameter adjustment for disturbance […]
Manan will start his internship at Seagate this Summer
Manan has accepted an internship offer from Seagate Technology for Summer 2023 where he will work as an AI/Machine Learning Intern. He will work in Seagate’s highly dynamic Global Wafer Systems (GWS) Team and collaborate with a global team of Data Scientists and Machine Learning Engineers to shape the future of new data products in […]
Paper on Clustered Federated Learning published in IEEE Transactions on Industrial Informatics
Our paper titled “A greedy agglomerative framework for clustered federated learning” has been published in the IEEE Transactions on Industrial Informatics. The paper was co-authored by Manan Mehta and Prof. Chenhui Shao. Federated learning (FL) has received widespread attention for supporting the training of deep learning models across multiple IoT devices while preserving data privacy. […]
Paper on Federated Learning-based Defect Detection for Additive Manufacturing published in JMS
Our paper titled “Federated learning-based semantic segmentation for pixel-wise defect detection in additive manufacturing” has been published in the Journal of Manufacturing Systems. The paper was co-authored by Manan Mehta and Prof. Chenhui Shao. Federated learning (FL) is an emerging machine learning (ML) paradigm which allows several participants (manufacturers) to collaboratively train a model while […]
Paper on ML-Enabled Geometric Compliance Improvement for Two-Photon Lithography Published in JMP
Our paper titled “Machine-learning-enabled geometric compliance improvement in two-photon lithography without hardware modifications” has been published on Journal of Manufacturing Processes. The paper was co-authored by Yuhang Yang and Prof. Chenhui Shao. In recent years, two-photon lithography (TPL) has emerged as a practical and promising micro- and nano-fabrication technique for a wide range of applications. […]
Paper on Hierarchical Data Models for Additive Manufacturing Published in AM
Our paper titled “Hierarchical data models improve the accuracy of feature level predictions for additively manufactured parts” has been published on Additive Manufacturing. The paper was co-authored by Yuhang Yang and Prof. Chenhui Shao. Industrial-scale production applications of additive manufacturing (AM) are growing rapidly, and scalable AM production requires quality systems that monitor and control […]
Shichen will start her internship at Meta this summer
Shichen has accepted an internship offer from Meta in 2022 Summer. She will work as a Machine learning engineer intern. She will conduct engineering projects and cutting-edge researches in the fields of Machine Learning (ML), Natural Language Processing (NLP). Her PhD research focusing on machine learning in manufacturing processes and her recent involvement in a […]
Siyuan Will Start his Internship at 3M
Siyuan has recently accepted an internship position at 3M as a Data Science intern this summer. He will work with the AI & ML lab at 3M’s Corporate Research Systems Laboratory to design new material structure and geometry using Reinforcement Learning (RL) and Generative Adversarial Networks (GANs). His PhD research focusing on machine learning in […]