I am a prospective PhD student interested in computational materials science methods that use machine learning to accelerate materials discovery and design.

I have a background in materials science and engineering and mathematics and have built Python-based Abaqus pipelines simulating MEMS devices and folded kirigami to visualize energy absorption across thickness, curvature, and fold angles. Currently, I am the lead data scientist at Girl Effect developing generative AI–driven agentic systems.

I am interested in applying existing models to new material systems and designing new materials models whose architectures better represent physical material structures and incorporate stronger physics-based constraints for energy, electronics, and other sustainable technologies.

Research CV

Publications

• Peer-reviewed

  • Xu, L*, Mitra-Behura, S*. et al. (2015). Identifying DNA Methylation Variation Patterns to Obtain Potential Breast Cancer Biomarker Genes. Int. J. Biomed. Data Mining, 4 (1). doi:10.4172/2090-4924.1000115

• Technical Whitepapers

  • Mitra-Behura, S. (2023). Girl Effect’s Artificial Intelligence & Machine Learning Vision for Family Planning Chatbots. Girl Effect, London

  • Mitra-Behura, S. et al. (2025). Building with GenAI: Girl Effect’s Journey to Smarter, Safer Health Chatbots. Girl Effect, London.

Featured Research/Technical Projects

• Simulating kirigami structures

• Developing GenAI agentic systems for health-focused chatbots

• Simulating building energy and lighting to evaluate alternative, sustainable materials

• Identifying 26 novel biomarker genes for breast cancer

An exhaustive list of research and technical projects I’ve worked on can be found here.