From Data to Insights: Applying Advanced Analytics to Railroad Maintenance Diagnostics and Prognostics
7 May 2026, 17:00 (CEST)
7 May 2026
Railroad, Railway, Track, Maintenance of Way, Big Data, Analytics, Diagnostics, Prognostics, Machine Learning
Welcome from the Chairs
We are excited to invite you to a panel discussion on "From Data to Insights: Applying Advanced Analytics to Railroad Maintenance Diagnostics and Prognostics.” This webinar will feature four presentations from leading experts in advanced analytics, focusing on improving how railroads gather and analyze data to enhance safety and reduce costs. The presentations will cover a wide range of important topics in railroad operations, including early detection of failed bearings, track stability assessment, effective lubrication strategies, and the seamless integration of manual and automated track inspections.
Date: 7 May 2026
Time: 5:00 pm CEST | 11:00 am EDT
Webinar ID: 894 7768 3152
Webinar Secretariat: journal.webinar@mdpi.com
Event Chairs
Department of Mechanical Engineering, Virginia Tech, USA,
Center for Vehicle Systems and Safety (CVeSS), Virginia Tech, USA
Mehdi Ahmadian is the J. Bernard Jones Chair of Mechanical Engineering at Virginia Tech, where he also serves as Director of the Center for Vehicle Systems and Safety (CVeSS) and the Railway Technologies Laboratory (RTL). He has co-authored eight books, four book chapters, and more than 500 journal and conference papers. He has delivered over 400 technical presentations, including numerous major keynote and plenary lectures and invited talks. He holds 12 U.S. and international patents, with an additional patent application pending. He is a Fellow of the American Society of Mechanical Engineers (ASME), SAE International, the International Society for Condition Monitoring (ISCM), and the International Institute of Acoustics and Vibration (IIAV), and an Associate Fellow of the American Institute for Aeronautics and Astronautics (AIAA). Some of Mehdi’s most recent professional awards include the 2024 SAE Medal of Honor, the highest recognition of lifetime achievement given to one SAE member each year; the 2023 Virginia Tech Alumni Award for Research Excellence, regarded as the most prestigious Virginia Tech award for significant lifelong research contributions; the 2019 SAE Magnus Hendrickson Innovation Award; and the 2014 SAE International L. Ray Buckendale Award.
Dr. Ahmad Radmehr is a Machine Learning Engineer at Progress Rail, where he develops deep reinforcement learning systems for autonomous train operations. Previously, he served as a Research Scientist at Virginia Tech’s Center for Vehicle Systems and Safety, leading projects on unsupervised learning and sensor-based analysis to assess rail track stability. Ahmad holds a Ph.D. in Mechanical Engineering from Virginia Tech and offers extensive expertise in railroad engineering and maintenance, programming, algorithms, and applied machine learning.
Invited Speakers
University Transportation Center for Railway Safety, College of Engineering and Computer Science, University of Texas Rio Grande Valley, USA
Data-Driven Proactive Rolling Stock Condition Monitoring Technology
Constantine Tarawneh is a Professor of Mechanical Engineering at the University of Texas Rio Grande Valley (UTRGV) where he worked since 2003. He obtained his MS and Ph.D. degrees from the University of Nebraska-Lincoln (UNL) in 1999 and 2003, respectively. He founded the University Transportation Center for Railway Safety (UTCRS) in 2013 and the NSF CREST Center for Multidisciplinary Research Excellence in Cyber-Physical Infrastructure System (MECIS) in 2021 and serves as the Founding Director for both Centers. He also serves as the Sr. Associate Dean for the College of Engineering and Computer Science since 2016. His various research and educational activities have resulted in $48 Million in funding from federal, industry, state, private, and local sources. He has more than 23 years of experience conducting a variety of railroad research with emphasis on advanced bearing condition monitoring techniques. He received 36 teaching, mentoring, and research awards highlighted by the UT System Regents’ Outstanding Teaching Award in 2009. In Fall of 2017, he was appointed as the Louis A. Beecherl, Jr. Endowed Professor in Engineering, and in Fall 2023, he was inducted into the UTRGV Academy of Distinguished Teachers. To date, he has mentored and supervised over 1300 undergraduate and graduate students.
Department of Civil and Environmental Engineering, University of Delaware, USA
The Link Between Track Geometry Degradation and Inspection Frequency; A Risk-Based Approach
Dr. Zarembski is an internationally recognized authority in fields of track and vehicle/track system analysis. He is Professor and Director of Railroad Engineering and Safety Program at University of Delaware. He was President of ZETA-TECH, an independent railway technical consulting company, from 1984 through 2007 when it was acquired by Harsco Rail. He was also Director R&D for Pandrol and Speno Rail Services and Manager, Track Research for AAR. Dr. Zarembski has a PhD in Civil Engineering from Princeton University, and M.S. and B.S. from NYU. He is a registered Professional Engineer in five states. He is an Honorary Member of AREMA and Fellow of ASME. He received the ASME's Rail Transportation Award in 1992 and FRA’s Special Act Award in 2001. He has authored over 200 technical papers and two books.
Department of Civil and Environmental Engineering, University of South Carolina, USA
Onboard Vibration-Based System for In-Motion Track Stiffness Change Detection
Dr. Dimitris C. Rizos is a Professor in the Department of Civil and Environmental Engineering (CEE) at the University of South Carolina and the Associate Chair of the Department. He is the Director of the Advanced Railroad Technology Group, the Railway Infrastructure Laboratory and the Railway Engineering curriculum at USC. He serves as the Associate Director of the University Transportation Center for Railway Safety. His background is in Structural Mechanics, and his research focuses on the development and implementation of smart technologies for the railway infrastructure, including monitoring and condition assessment of track and structures, remote sensing and non-contact methods, train dynamics and train-track interaction. He is the recipient of the ASCE SC section Technical Merit award, the ASME Railway Division Award, and the Bert Storey Innovative Research Award, among others, for his contributions in research and education in railway engineering. He is the past chair of ASCE TDI Rail Transport Committee; he has been selected as a voting member of the NAE ad-hoc committee on safe transportation of LNG by rail and he is a voting member of the AREMA Committee 24, and TRB Committee AR050. He has served as the principal and co-investigator in numerous transportation infrastructure research projects. His research activities are funded by Federal Agencies and the private industry, including FRA, NSF, FHWA, USDOT, SCDOT, DOD, DOE, and CSX, among others.
Department of Mechanical Engineering, Virginia Tech, USA,
Center for Vehicle Systems and Safety (CVeSS), Virginia Tech, USA
Detecting Flange Grease in Revenue Service: From Data to Actionable Insight
Mehdi Ahmadian is the J. Bernard Jones Chair of Mechanical Engineering at Virginia Tech, where he also serves as Director of the Center for Vehicle Systems and Safety (CVeSS) and the Railway Technologies Laboratory (RTL). He has co-authored eight books, four book chapters, and more than 500 journal and conference papers. He has delivered over 400 technical presentations, including numerous major keynote and plenary lectures and invited talks. He holds 12 U.S. and international patents, with an additional patent application pending. He is a Fellow of the American Society of Mechanical Engineers (ASME), SAE International, the International Society for Condition Monitoring (ISCM), and the International Institute of Acoustics and Vibration (IIAV), and an Associate Fellow of the American Institute for Aeronautics and Astronautics (AIAA). Some of Mehdi’s most recent professional awards include the 2024 SAE Medal of Honor, the highest recognition of lifetime achievement given to one SAE member each year; the 2023 Virginia Tech Alumni Award for Research Excellence, regarded as the most prestigious Virginia Tech award for significant lifelong research contributions; the 2019 SAE Magnus Hendrickson Innovation Award; and the 2014 SAE International L. Ray Buckendale Award.
Registration
This is a FREE webinar. After registering, you will receive a confirmation email containing information on how to join the webinar.
Registrations with academic institutional email addresses will be prioritized.
Certificates of attendance will be delivered to those who attend the live webinar.
Can't attend? Register anyway and we'll let you know when the recording is available to watch.
Programme
| Speaker | Presentation | Time in CEST | Time in EDT |
|---|---|---|---|
| Marko Stojadinov | Machines Journal Introduction | 17:00–17:10 | 11:00–11:10 |
| Prof. Dr. Mehdi Ahmadian | Webinar Opening and Introduction to Special Issue | 17:10–17:20 | 11:10–11:20 |
| Prof. Dr. Constantine Tarawneh | Data-Driven Proactive Rolling Stock Condition Monitoring Technology | 17:20–17:40 | 11:20–11:40 |
| Prof. Dr. Allan M. Zarembski | The Link Between Track Geometry Degradation and Inspection Frequency: A Risk-Based Approach | 17:40–18:00 | 11:40–12:00 |
| Prof. Dr. Dimitris C. Rizos | Onboard Vibration-Based System for In-Motion Track Stiffness Change Detection | 18:00–18:20 | 12:00–12:20 |
| Prof. Dr. Mehdi Ahmadian | Detecting Flange Grease in Revenue Service: From Data to Actionable Insight | 18:20–18:40 | 12:20–12:40 |
| Q&A | 18:40–18:55 | 12:40–12:55 | |
| Prof. Dr. Mehdi Ahmadian | Closing of Webinar | 18:55–19:00 | 12:55–13:00 |
Relevant Special Issue
"From Data to Insights: Applying Advanced Analytics to Railroad Maintenance Diagnostics and Prognostics"
Guest Editors: Dr. Ahmad Radmehr and Prof. Dr. Mehdi Ahmadian
Deadline for manuscript submissions: 30 December 2026
