News

Paper on adaptive sampling for multi-task Gaussian processes published in JMS

Our paper titled “Adaptive sampling design for multi-task learning of Gaussian processes in manufacturing” has been published in the Journal of Manufacturing Systems. The paper was co-authored by Manan Mehta and Prof. Chenhui Shao. Multi-task learning (MTL) is a machine learning technique used to enhance learning performance in similar-but-not-identical tasks. However, the accuracy of MTL […]

Paper on Hybrid Multi-Task Learning-Based Response Surface Modeling Published in JMS

A paper entitled “hybrid multi-task learning-based response surface modeling in manufacturing” is recently published in the Journal of Manufacturing Systems. The paper was co-authored by Yuhang Yang and Chenhui Shao. This paper developed a hybrid multi-task learning-based method tocost-effectively model the response surfaces of multiple similar-but-not-identical manufacturing processes. The method was evaluated using a simulation-based numerical […]

ADML Wins New NSF Project on Digital Biomanufacturing

The project is titled, “Collaborative Research: A Digital Manufacturing Platform to Democratize Biological Tissue Access Using Smart Two-Photon Polymerization.” The funding comes from the NSF’s Advanced Manufacturing (AM) program within the Division of Civil, Mechanical and Manufacturing Innovation (CMMI). Working with our collaborators at Brown University, we will create a digital manufacturing platform for cloud-based […]

ADML Receives Funding from AIFS

The Artificial Intelligence Institute for Next Generation Food Systems, or AIFS, was launched October 1, 2020 to solve the world’s biggest challenges to crop and food production facing our planet. For more information about AIFS, please see this news article and the AIFS website. In the first year of the Institute, we will work on […]

ADML Receives Funding from DOE

The group receives funding from the Advanced Manufacturing Office of the U.S. Department of Energy (DOE). The project, entitled “Novel Energy-Efficient Drying Technologies for Food, Pulp and Paper, and other Energy Intensive Manufacturing Industries,” aims to develop innovative dryer platforms for the food and forest products industry to reduce energy consumption and to improve product […]

Review Paper on Data-Driven Intelligent 3D Surface Measurement Published in Machines

A feature article titled “data-driven intelligent 3D surface measurement in smart manufacturing: review and outlook” has been published in Machines recently. The paper was co-authored by Yuhang Yang, Zhiqiao Dong, Yuquan Meng and Chenhui Shao. This paper reviewed and summarized existing research in interpolation and sampling design techniques in various manufacturing scenarios, which can potentially […]

Sixian Receives Fellowship From Ronald Kee-Young Chao Fund

Ronald Kee- Young Chao acted as Novel Enterprises’ Managing Director from 1987-1996, and has served as vice-chairman and director since. He is committed to investing in future generations of leaders through education and established the Asian Future Leaders Scholarship program. Sixian is a first-year Ph.D. student working on the nano Manufacturing project in the Automation […]

Paper on Multi-Task Learning of Spatiotemporal Processes Published in JMS

A paper entitled “multi-task learning for data-efficient spatiotemporal modeling of tool surface progression in ultrasonic welding” is recently published in the Journal of Manufacturing Systems. The paper was co-authored by Haotian Chen, Yuhang Yang, and Chenhui Shao. This paper developed a multi-task learning method to enable data-efficient spatiotemporal modeling. The method was evaluated using tool […]

Yuquan’s Work on Multi-Objective Optimization Published in AIMS MBE

Ultrasonic metal welding (UMW) is a solid-state joining method with various industrial applications including battery assembly, automotive body construction, and electronic packaging. Among the advantages of UMW over conventional fusion welding are the ability to join dissimilar metals, reduced energy consumption and short welding time. Despite of its numerous advantages, this technique has a relative […]