Prof. Chenhui Shao has won an NSF Faculty Early Career Development (CAREER) award for his project “Dynamic Process-Attribute-Data-Performance Modeling to Enable Smart Ultrasonic Metal Welding.” The CAREER Program offers NSF’s most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances […]
ADM Lab currently has multiple openings for Graduate students. Full scholarships (RA or TA) will be provided. Working on both fundamental methodologies and application-oriented research related to the automation and intelligence of manufacturing, our members are multi-skilled (modeling, simulation, data analytics, hardware, experiment, etc.) We are very proud of our accomplishments over the years as […]
Yuhang has received and accepted an internship offer from Facebook in this coming summer. He will work with the “Probability” team to conduct engineering projects and cutting-edge research in the fields of machine learning, Bayesian statistics, and stochastic optimization and build the next generation of machine learning systems behind Facebook’s products that can scale through […]
We are pleased to announce that Shichen and Kuan-Chieh join our ADM Lab this semester. Shichen Li is an M.S student in the Department of Mechanical Science and Engineering at UIUC. She received her B.S. Degree in Aerospace Engineering from Beihang University in 2019. Her research interests include data science, machine learning, and their applications […]
High-resolution spatiotemporal data is crucial for characterizing, modeling, and monitoring the space-time dynamics of complex systems in manufacturing. However, the acquisition of such data is generally expensive and time-consuming. Spatiotemporal interpolation aims to predict the values at unmeasured locations using measured data, and emerges as a promising solution to cost-effectively characterizing spatiotemporal processes. Since the […]
During this year’s North American Research Conference (NAMRC), on behalf of a MechSE team, Dr. Shao presented a project “Manufacturing of an Innovative Hybrid Heat Exchanger” in the Reusable Abstractions of Manufacturing Processes (RAMP) 2019 competition, and won the 2nd prize. The purpose of the RAMP competition is to create a venue to foster interest […]
The project “A Multi-Scale Computational Platform for Predictive Modeling of Corrosion in Al-steel Joints,” funded by the Vehicle Technologies Office of U.S. Department of Energy (DOE), started recently. We are working in collaboration with researchers from the University of Michigan, the University of Georgia, Pennsylvania State University, General Motors, Optimal Process Technologies, and Livermore Software Technology […]
The project “Quantitative Non-Destructive Evaluation of Fatigue Damage Based on Multi-Sensor Fusion,” funded by the Reducing EMbodied-Energy And Decreasing Emissions (REMADE) Institute, is starting soon. We will work with Professor Katie Matlack from UIUC and Prof. Professor Jingjing Li from Penn State to develop an innovative non-destructive evaluation (NDE) methodology for the quantification and prognostics […]
High-speed electric multiple units have numerous advantages. However, a number of critical maintenance issues arise in the operation of high-speed electric multiple units. The previous researches about rail profile design usually take only a single type of wheel profile into account, which would cause some other problems such as severe increase of hollow wear on […]
ADM Lab currently has two openings for Ph.D. students. Full scholarships (RA or TA) will be provided. Working on both fundamental methodologies and application-oriented research related to the automation and intelligence of manufacturing, our members are multi-skilled (modeling, simulation, data analytics, hardware, experiment, etc.) We are very proud of our accomplishments over the years as […]