Fig. 04 — About
The person behind the models
Biography
I'm a civil engineer working at the point where materials science meets data science — training machine learning models on real experimental data so structural and geotechnical performance can be predicted, not just guessed.
My work sits across three connected areas: high-performance and sustainable concrete (UHPC, GGBS, silica fume, fibre and FRP reinforcement), geotechnical soil-reinforcement systems, and the machine learning pipelines — gradient boosting, ANN, AdaBoost, KNN, MARS — used to model them. I'm especially interested in explainable AI: models that don't just predict a number, but tell an engineer why.
I currently work as a Postdoctoral Researcher in the Department of Civil Engineering at Chulalongkorn University, Bangkok. Before this, I taught and supervised undergraduate capstone projects as an Assistant Professor in the Department of Civil Engineering at Dayananda Sagar College of Engineering, Bengaluru, and completed my doctoral research at the National Institute of Technology, Patna.
Outside the lab, I mentor student project teams through to competition and Open Day presentations — several of which have gone on to win departmental awards for design and social relevance.
Fig. 05 — Education
Academic background
Ph.D., Civil Engineering
National Institute of Technology, Patna, IndiaDoctoral research in civil engineering, with a focus that carried forward into applied machine learning for materials performance.
M.Tech / Postgraduate Studies, Civil Engineering
IndiaSpecialised coursework and research preceding doctoral study.
B.Tech, Civil Engineering
IndiaFoundational training in structural, geotechnical and construction engineering.
Exact years and institute names can be refined — see note in the delivery message.
Fig. 06 — In the Field
