News

Project on Deep Learning and High-Speed Train Funded by CRRC

Posted on October 13, 2017 by

Our project “Research on Key Technology of Rail Transit-Based Wireless Sensor Intelligence Data” is funded by China Railway Rolling Stock Corporation (CRRC). We will work with Professor Niao He‘s lab to develop deep learning and sensor fusion methodologies that will enhance the intelligence and automation of rolling stock, especially high-speed trains. The project (budget $300k) is expected to be completed in one year.

Image result for crrc high speed trains

Project on Big Data in Manufacturing Funded by National Center for Supercomputing Applications (NCSA)

Posted on October 12, 2017 by

The funded project “Big Data Enabled Multi-Level Decision-Making for Smart Manufacturing” aims to establish theoretical foundations and a new paradigm for multi-level decision-making by leveraging big data and high-performance computing (HPC). We will design big data based solutions for manufacturers, including NCSA’s industrial partners, and equip them with toolkits for smart sensing, monitoring, control, diagnosis, prognostics, etc. We will work in collaboration with MechSE Research Associate Professor and Technical Assistant Director at NCSA, Seid Koric, and outstanding researchers at NCSA Industry, Dr. Dora Cai, Dr. Qiyue Lu, and Mr. Yifang Zhang. Dr. Shao will be working as a Scholar-in-Residence at NCSA for the one-year project. The project budget is $25,000 for one year.

For details, please refer to the MechSE news.

NCSA home

Project in Wheel-Track Wear Supported by CRRC

Posted on February 1, 2017 by

China Railway Rolling Stock Corporation (CRRC) has funded for our project “Wheel-Track Wear Indicators, Calculation and Testing Methods for Heavy-Haul Freight Cars.” This one-year project ($132k) will tackle fundamental and technical challenges in evaluating and predicting wheel-track wear for heavy-haul freight cars.

Ph.D. Positions

Posted on October 25, 2016 by

Our group currently has multiple openings for Ph.D. students. Full scholarships (RA or TA) will be provided. Students with a solid background in the areas (some but not necessarily all) of (1) manufacturing (or industrial engineering), (2) control, (3) statistics, and (4) machine learning are encouraged to apply. Research experiences in related fields are preferred. Admissions will be decided by the Departmental Admissions Committee, but applicants are welcome to discuss with Dr. Shao about the positions.

Interested applicants please send your CV and transcript to Dr. Shao at chshao (at) illinois (dot) edu. International applicants please also provide your GRE and TOEFL scores. A score of 24 or higher for speaking of TOEFL is required in order to be considered for a TA position.

UPDATE: The positions have been filled. Thank you for your attention.