Dr. Anish Poudel is a Scientist for Nondestructive Evaluation (NDE) in the Research and Innovation department at MxV Rail. He holds B.S., M.S., and Ph.D. degrees in Mechanical Engineering with a focus on Experimental Mechanics and NDE. With over 15 years of research, development, and testing experience in NDE for railroad and aerospace applications, Dr. Poudel has played a key role in advancing inspection technologies that enhance efficiency and safety across the North American railway industry. At MxV Rail, he serves as a program manager, team leader, and subject matter expert, guiding projects in NDE, wayside inspection, and data analytics. He has authored more than 150 technical publications and holds one patent. Dr. Poudel is deeply involved in professional organizations, serving as Secretary of the ASNT Engineering Council and leading its AI/ML committee, in addition to holding leadership roles on multiple ASNT councils and committees. He is also the General Secretary of Academia NDT International and an active member of AREMA Committee 4-Rail. Recognized as an ASNT Fellow, Dr. Poudel has received numerous honors, including the 2024 ASNT Research Award for Innovation, the 2019 International Heavy Haul Association Emerging Railway Professionals Award, the 2018 ASNT Mentoring Award, and the 2014 ASNT Young NDT Professional Award. Known for his leadership, technical excellence, and dedication to innovation, Dr. Poudel continues to push the boundaries of NDE technology, advancing the safety, reliability, and performance of the railway industry.
The U.S. rail network—spanning nearly 140,000 miles of privately owned track and supporting both freight and passenger services—has been central to the nation’s economy for over 150 years. Traditionally, rail inspections have relied on manual, visual assessments using handheld tools, which can be inconsistent, prone to human error, and difficult to digitize or analyze for predictive maintenance. With the adoption of advanced sensing and monitoring technologies, the industry now collects vast amounts of data on infrastructure and mechanical systems, creating a pressing need for automated analysis tools. This seminar explores how artificial intelligence (AI) and machine learning (ML) are being used to meet this need. Leveraging powerful GPUs and advanced algorithms, AI/ML systems can now match or exceed human performance in tasks such as image classification, pattern recognition, and predictive analytics. These technologies enable more accurate anomaly detection, enhancing inspection efficiency, operational safety, and the long-term reliability of railway networks.