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Welcome to the Automation and Digital Manufacturing (ADM) Lab! The ADM Lab is directed by Dr. Chenhui Shao. To learn more about our research, please visit the research and publications pages.

Recent News

  • Image of the main quad with students sitting in grass
    RA/TA Positions Available to Graduate StudentsMarch 15, 2019

    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 […]

  • An aerial view of campus
    Undergraduate Research Assistant Positions AvailableMarch 14, 2019

    UPDATE: The positions have been filled. Thank you for your attention. If you are still interested in our research, you can consider taking Prof. Shao’s ME 498 “Manufacturing Data and Quality Systems” offered in Fall 2019. ADM Lab is seeking self-motivated undergraduate research assistants to conduct research for a project related to ultrasonic metal welding for […]

  • New Manufacturing Course Prepares Students for the Big Data Era in ManufacturingFebruary 13, 2019

    Dr. Chenhui Shao offered a new course in mechanical engineering—ME 498 Manufacturing Data and Quality Systems—to prepare students for the Big Data era in manufacturing. The course structure introduces students to industrial environments, and its content prepares students for the future of the manufacturing industry. Most current manufacturing courses are more or less outdated, and […]

  • Yuquan and Yuhang’s Review on Sustainability in Smart Manufacturing Published in MDPI SustainabilityDecember 14, 2018

    With the rapid development of sensing, communication, computing technologies, and analytics techniques, today’s manufacturing is marching towards a new generation of sustainability, digitalization, and intelligence. Even though the significance of both sustainability and intelligence is well recognized by academia, industry, as well as governments, and substantial efforts are devoted to both areas, the intersection of […]

  • Siyuan’s Algorithm on Multi-object Tracking Ranked Top in the UA-DETRAC Dataset Tracking ChallengeDecember 6, 2018

    A multi-object tracking algorithm developed by Siyuan Chen is ranked top in the tracking task leaderboard of the UA-DETRAC dataset. UA-DETRAC is a challenging real-world multi-object detection and multi-object tracking benchmark. The dataset consists of 10 hours of videos captured with a Cannon EOS 550D camera at 24 different locations at Beijing and Tianjin in China. […]

  • Yuhang’s Work on Big Data Analytics and Surface Finishing Process Presented in ASME MSEC 2018November 15, 2018

    With the rapid development of sensing, communication, and computing technologies and infrastructure, today’s manufacturing industry is marching towards a big data era and a new generation of digitalization and intelligence. The availability of big data provides us with a golden opportunity to promote smart manufacturing. Nevertheless, the deployment and popularization of big data analytics in manufacturing are still at its nascent stage. […]