DEPARTMENT.FACULTY
- DEPARTMENT_STAFF.QUALIFICATION
Ph.D in Civil Engineering, B.Tech in Civil Engineering (AMU), M.Tech in Structural Engineering (AMU)
- DEPARTMENT_STAFF.DESIGNATION
Assistant Professor (Contractual)
- DEPARTMENT_STAFF.THRUST_AREA
Sustainable Cementitious Composites, Thermo-Structural Behavior, Sustainability, Machine Learning, eXplainable AI (XAI)
- DEPARTMENT_STAFF.ADDRESS
Department of Civil Engineering, Z.H.C.E.T., A.M.U., Aligarh, Uttar Pradesh, India, 202002.
- DEPARTMENT_STAFF.MOBILE
9045133160
- DEPARTMENT_STAFF.EMAIL
ssansari.cv@amu.ac.in
Dr. Saad Shamim Ansari is an Assistant Professor in the Department of Civil Engineering at Zakir Husain College of Engineering and Technology, AMU from the year 2021. He completed his B.Tech in Civil Engineering in 2015, M.Tech in Structural Engineering in 2018, and his Ph.D. in 2025 on the following topic "Characterization and Structural Behavior of Concrete Using Supplementary Cementitious Materials".
His research focuses on sustainable cementitious composites, supplementary cementitious materials, and the application of machine learning and eXplainable AI in civil engineering. He has published more than 25 papers in reputed international journals, including those of Elsevier, Springer, ASCE, and Technopress. He has delivered expert lectures at institutions such as Maulana Azad National Urdu University (Hyderabad), Vivekananda College of Technology and Management (Aligarh), and within AMU on topics ranging from computational intelligence in civil engineering to sustainable concrete technologies.
Dr. Ansari regularly reviews manuscripts for several international journals, including Structures (Elsevier), Environmental Science and Pollution Research (Springer), Engineering Structures (Elsevier), Journal of Structural Design and Construction Practice (ASCE), among others.
Alongside his research and reviewing responsibilities, he has attended various Workshops, Webinars, FDPs, PDPs, Expert Lectures, Training Programs, National and International Conferences. He has also organized training programs and workshops in the department in collaboration with the National Institute of Disaster Management (NIDM), Ministry of Home Affairs, New Delhi on Disaster Preparedness and its mitigation.
- Ansari, S.S., Ibrahim, S.M., Hasan, S.D. and Rehman, A.U., 2025, October. Effect of perforated fly ash cenospheres and nano-silica on the thermo-structural behaviour of sustainable concrete. In Structures (Vol. 80, p. 109800). Elsevier.
- Ansari, S.S., Ibrahim, S.M., Hasan, S.D. and Rehman, A.U., 2025. Experiments and Predictive Modelling on Sustainable Cementitious Mortar with Perforated Fly Ash Cenospheres and Effectively Dispersed Nano Silica. Materials Today Communications, p.113020.
- Ansari, M.A., Shariq, M., Ansari, S.S. and Husain, A., 2024. Technical insights of clean and sustainable photocatalytic concrete: A scientometric analysis–aided review. Environmental Science and Pollution Research, pp.1-39.
- Shaida, M.A., Ansari, S.S., Muhammad, R., Ibrahim, S.M., Farooqi, I.H. and Amhamed, A., 2025. Prediction of CO2 uptake in bio-waste based porous carbons using model agnostic explainable artificial intelligence. Fuel, 380, p.133183.
- Ansari, S.S., Ibrahim, S.M. and Hasan, S.D., 2025. Interpretable machine-learning models to predict the flexural strength of fiber-reinforced SCM-blended concrete composites. Journal of Structural Design and Construction Practice, 30(2), p.04024113.
- Mohammad, T., Ibrahim, S.M., Ansari, S.S. and Rehman, A.U., 2024. Feasibility study and optimization of limestone calcined clay composites for compressive strength using multi-layered explainable artificial intelligence models. Materials Today Communicati
- Ansari, M.A., Shariq, M., Mahdi, F. and Ansari, S.S., 2024. Prediction of modulus of elasticity of FA concrete using crushing strength, UPV and RHN values. Computers and Concrete, 34(1), p.33.
- Ansari, S.S., Azeem, A., Asad, M., Zafar, K. and Ibrahim, S.M., 2024. Comparative analysis of conventional and ensemble machine learning models for predicting split tensile strength in thermal stressed SCM-blended lightweight concrete. Materials Today: Pr
- Ansari, M.A., Ansari, S.S., Ghazi, M.S., Saqib, M., Ibrahim, S.M. and Saquib, M., 2024. Incorporating non-destructive UPV into machine learning models for predicting compressive strength in SCM concrete. Materials Today: Proceedings.
- Ansari, S.S., Ansari, M.A., Saqib, M., Ghazi, M.S. and Ibrahim, S.M., 2024. Impact of thermal loads on silica fume-modified lightweight concrete: machine learning approach to assess compressive strength evolution. Materials Today: Proceedings.
- Ansari, S.S., Ansari, H., Khateeb, A. and Ibrahim, S.M., 2024. Comparative study of machine learning models for predicting the compressive strength of concrete using Non-Destructive Testing methods. Materials Today: Proceedings.
- Mohammad, T., Ansari, S.S., Ibrahim, S.M. and Baqi, A., 2024, December. Scientometric insights into limestone calcined clay cement (LC3): Advancing sustainable construction through low-carbon cementitious composites. In ICSDAWM, AMU.
- Ansari, S.S., Ibrahim, S.M., Hasan, S.D., Ahmed, F., Idris, M., Frogh, I. and Ali, F., 2023, July. Conventional and Ensemble Machine Learning Techniques to Predict the Compressive Strength of Sustainable Concrete. In IACESD, Springer, Singapore.
- Ansari, S.S., Farid, S.A., Abdullah, S.A., Abuzar, M., Ahmad, M.S. and Ibrahim, S.M., 2023, July. Predicting the Porosity of SCM-Blended Concrete Composites Using Ensemble Machine Learning Models. In IACESD, Springer, Singapore.
- Mohammad, T., Ansari, S.S., Ibrahim, S.M. and Baqi, A., 2023, July. Optimizing sustainable construction materials with machine learning algorithms: predicting compressive strength of concrete composites. In IACESD, Springer, Singapore.
- Ansari, S.S., Ansari, M.A., Shariq, M., Mahdi, F. and Ibrahim, S.M., 2023, July. Ensemble machine learning models to predict the compressive strength and ultrasonic pulse velocity of sustainable concrete. In IACESD, Springer, Singapore.
- Tariq, F., Ansari, S.S. and Ibrahim, S.M., 2023, July. Finite Element-Based Dynamic Analysis of a T-Beam Bridge with Skew Supports. In IACESD 2023, Springer, Singapore (pp. 61-69).
- Ansari, S.S., Ibrahim, S.M. and Hasan, S.D., 2023, July. Effect of Sealed Curing on Perforated and Non-perforated Cenospheres-Based Lightweight Cementitious Composites. In IACESD 2023, Springer, Singapore.
- Ansari, M.A., Shariq, M., Ansari, S.S. and Husain, A., 2024. Efficiency assessment of TiO2-based photocatalytic concrete for clean and sustainable construction: a state-of-the-art review. Iranian Journal of Science and Technology, Springer.
- Ibrahim, S.M., Ansari, S.S. and Hasan, S.D., 2023. Towards white box modeling of compressive strength of sustainable ternary cement concrete using explainable artificial intelligence (XAI). Applied Soft Computing, 149, p.110997.
- Mughees, A., Sharma, A., Ansari, S.S. and Ibrahim, S.M., 2023. Prediction of the compressive strength of nano-titanium based concrete composites using machine learning. Materials Today: Proceedings.
- Ansari, S.S., Ibrahim, S.M. and Hasan, S.D., 2023. Conventional and ensemble machine learning models to predict the compressive strength of fly ash based geopolymer concrete. Materials Today: Proceedings.
- Mohammad, Z., Ansari, S.S., Anwar, M. and Baqi, A., 2022. Structural Behaviour of RC Silo under Gravity and Infill Loads. In Recent Trends in Civil Engineering: Select Proceedings of ICRACE 2021 (pp. 231-239). Singapore: Springer Nature Singapore.
- Mohammad, Z., Anwar, M., Ansari, S.S. and Baqi, A., 2022. Finite Element Modelling of RC Silo Subjected to Thermal Loads. In Recent Trends in Civil Engineering: Select Proceedings of ICRACE 2021 (pp. 419-427). Singapore: Springer Nature Singapore.
- Shariq, M., Ansari, S.S., Akhtar, S. and Masood, A., 2019, April. Performance of confined high volume fly ash concrete at elevated temperature. ICEARC'19, Trabzon, Turkey.
- Ansari, S.S., Shariq, M., Akhtar, S. and Masood, A., 2018, March. Effect of elevated temperature on the residual compressive strength of high volume fly ash mortar and concrete. ACMS-2018, IIT Roorkee, Roorkee, Uttarakhand, India.