$altText

Photo by Tecnológico de Monterrey - tec.mx

Construction Management Technology Projects

Tecnológico de Monterrey students interested in the program, please address any questions about the application process to Crockett Sewell, sewellc@purdue.edu.

Automation and Intelligent Construction

Faculty Name: Jiansong Zhang

E-Mail: zhan3062@purdue.edu

Project Term: Fall 2026

Project Description:

We are investigating the future of construction by integrating internet of things (IoT), building information modeling (BIM), robotics, and cyber-physical systems (CPS) into our cutting-edge D. Dorsey Moss Construction Lab (take a peek at the lab facility here: https://www.youtube.com/watch?v=HJ5O2bo8Z74).

Several federal and state sponsored research projects are underway at the Automation and Intelligent Construction (AutoIC) Lab, such as the following:
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2418688&HistoricalAwards=false
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2348213&HistoricalAwards=false
https://rip.trb.org/View/2410439

We are glad to host students who have a passion in construction automation and sustainable built environment, and would like to work on research topics related to any of the above mentioned areas.

Requirements:

Programming Skills (e.g., Python, Java, C++)
Experience Working with Robots (e.g., Kuka, ABB, Universal)
Self Motivated
Independent
Good Collaborator
Communication Skills (Written and Oral)
AI-Driven Vision Inspection Analytics to Assist with Quality Control of Bridge Inspection Documentation

Faculty Name: Kyu Kang

E-Mail: kyukang@purdue.edu

Project Term: Fall 2026 or Fall 2026/Spring 2027 (Full Academic Year Preferred)

Project Description:

By leveraging the Indiana Department of Transportation (INDOT)'s extensive archive of bridge inspection images and reports, the study will develop and validate an AI-driven system to support defect detection, condition assessment, and verification of inspector documentation. The deliverables include a calibrated AI model, technical reports, training materials, and a system ready for integration into INDOT's workflow. The expected outcomes are enhanced inspection reliability, improved asset management, and reduced safety risks - advancing INDOT's goals in innovation, safety, quality assurance, and infrastructure sustainability.

Requirements:

- Civil Engineering / Construction Management or related degree
- understanding of bridge inspection
- understanding of AI models (object detection and language model)