News

Paper on Multi-Object Tracking in Videos published on IEEE Access

Our paper titled “Efficient Online Tracking-by-Detection With Kalman Filter” has been published on IEEE Access. The paper was co-authored by Siyuan Chen and Prof. Chenhui Shao. Visual Multi-Object Tracking (MOT) has a promisingly broad application in manufacturing, construction, traffic, logistics, etc., especially in large-scale applications where it is not feasible to attach markers to many […]

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 […]