RISE Lab is actively looking for motivated PhD students, M.Tech students, and highly motivated B.Tech students interested in smart and resilient infrastructure systems.
The group works at the interface of structural engineering, sensing, computer vision, AI/ML, scientific computing, digital twins, structural health monitoring, prognosis, and infrastructure resilience.
Specific project topics are discussed individually after understanding the student’s background, interests, expected time commitment, and available research opportunities.
PhD Students#
I am especially interested in recruiting PhD students who want to work on long-term research problems related to smart infrastructure, structural health monitoring, physics-guided sensing, computer vision, AI/ML, digital twins, scientific machine learning, uncertainty-aware prognosis, and resilient infrastructure systems.
PhD students are expected to develop strong foundations in structural engineering, computational methods, research writing, and independent problem formulation.
As the group is growing, early PhD students will have the opportunity to help shape the research culture, computational tools, experimental directions, and long-term identity of RISE Lab.
M.Tech Students#
M.Tech students can work on focused research problems aligned with the broader directions of the group.
Possible broad areas include structural health monitoring, sensing, computer vision, digital twins, finite element modelling, machine learning for engineering systems, uncertainty-aware monitoring, and infrastructure resilience.
Projects will be scoped according to the available time, student background, and research goals. Students interested in continuing toward PhD-level research are especially welcome.
B.Tech Students#
Motivated B.Tech students can get involved through B.Tech projects, summer/winter projects, or exploratory research assignments.
B.Tech projects are usually introductory or exploratory and may involve coding, simulations, literature review, data analysis, computational demonstrations, or small proof-of-concept studies.
Students who are curious, consistent, and willing to learn are encouraged to reach out even if they do not yet have advanced research experience.
Research Areas#
Smart and Resilient Infrastructure#
Research on civil infrastructure systems that can be monitored, interpreted, and supported through sensing, computation, and data-driven decision support.
Physics-Guided Sensing and Monitoring#
Sensing and signal-processing methods that combine measurements with structural mechanics and engineering knowledge.
Structural Health Monitoring#
Methods for damage detection, condition assessment, prognosis, and infrastructure health monitoring.
Computer Vision and AI#
Image, video, and machine-learning methods for infrastructure monitoring, inspection, and response interpretation.
Digital Twins and System Identification#
Data-informed computational models for understanding, updating, and predicting structural behaviour.
Scientific Machine Learning and Uncertainty#
Physics-guided learning, interpretable AI, uncertainty quantification, and decision support for engineering systems.
Useful Background#
Useful background areas include:
- structural engineering
- applied mechanics
- structural dynamics
- finite element methods
- programming in Python or MATLAB
- machine learning or deep learning
- signal processing
- computer vision
- numerical methods
Prior experience in all these areas is not required. Students can join with strength in one area and develop the remaining skills during the project.
How to Apply#
Interested students may email with the subject line:
Prospective PhD/M.Tech/B.Tech Student – [Your Area of Interest]
Please include:
- CV
- academic transcript
- brief statement of research interests
- relevant project, coding, or research experience
- publications, if any
- whether you are applying through IIT Bombay admissions, external fellowship, or a project-based route
In the email, briefly explain which broad research area interests you and why.
Note to Prospective Students#
You do not need to have prior experience in artificial intelligence, computer vision, or advanced programming before reaching out.
A strong interest in research, willingness to learn, consistency, and curiosity about civil infrastructure problems are the most important qualities.