Széchenyi István University, Germany.
Ali Saleh is a dedicated Syrian 🇸🇾 Civil Engineer and Ph.D. researcher specializing in road engineering and sustainable asphalt technology. With years of hands-on experience in both academia and infrastructure development, Ali blends practical engineering skills with cutting-edge research. He is particularly focused on asphalt mixture optimization using AI and neural networks. Currently based in Germany 🇩🇪, Ali seeks to contribute to advanced civil engineering innovations worldwide.
Profile
🎓 Education
Dr. Ali Saleh holds a Ph.D. in Engineering Sciences from Széchenyi István University, Hungary (2020–2024), where he engaged in cutting-edge research within the field of civil engineering. Prior to his doctoral studies, he completed both a Master of Science in Civil Engineering (2015–2019) and a Bachelor of Science in Civil Engineering (2007–2013) at Tishreen University, Syria. Dr. Saleh’s academic background showcases a strong foundation in structural analysis, a deep commitment to infrastructure development, and a progressive trajectory in engineering sciences.
💼 Experience
In addition to his academic achievements, Dr. Ali Saleh brings valuable professional and teaching experience in the field of civil engineering. He worked as a Civil Engineer at Latakia Port, Syria (2014–2020), where he managed and supervised major infrastructure projects from design through execution, ensuring strict adherence to deadlines and quality standards. Alongside his engineering role, he served as a Lecturer at Tishreen University (2016–2019), where he delivered core civil engineering lectures and guided students academically. He also contributed to technical education as an Instructor at Omega Institute (2018–2019), teaching AutoCAD and Civil 3D to aspiring engineers, bridging theoretical knowledge with practical application.
🔬 Research Interests
♻️ Reclaimed Asphalt Pavement (RAP)
🧠 Machine Learning & Neural Networks in Civil Engineering
🌱 Sustainable Road Construction
🛣️ Bitumen Foaming and Asphalt Performance
📊 Pavement Testing and ITS/HWTT Data Modeling
🏆 Awards & Innovations
🛠️ Invention: Designed a bitumen foaming machine
🏅 Recognized for contributions in road project sustainability and environmental research at various international conferences.
📚 Selected Publications
🛣️ Warm Mix Asphalt (WMA) & Reclaimed Asphalt Pavement (RAP) Research
1. Machine Learning Modelling the Rut Depth of WMA Mixtures with Variable RAP and Foamed Bitumen Content
Journal: Dorogi i mosti (October 9, 2024)
DOI: 10.36100/dorogimosti2024.30.138
Highlights:
Utilizes machine learning models to predict rutting behavior in WMA.
Investigates performance effects of variable RAP and foamed bitumen levels.
Promotes data-driven pavement design and performance prediction.
2. Modelling Indirect Tensile Strength of Warm Mix Asphalt with Variable RAP Content
Journal: Dorogi i mosti (October 9, 2024)
DOI: 10.36100/dorogimosti2024.30.157
Highlights:
Focuses on indirect tensile strength (ITS) behavior of WMA mixtures.
Models mechanical performance under different RAP inclusion rates.
Supports RAP optimization for maintaining structural integrity.
3. Environmental Impacts of Using Foamed Asphalt
Journal: Dorogi i mosti (April 25, 2023)
DOI: 10.36100/dorogimosti2023.27.296
Highlights:
Evaluates environmental implications of foamed asphalt in road construction.
Considers emissions, energy savings, and recyclability.
Lays groundwork for greener road-building practices.