Poornima Padmanabhan

Dr. Poornima Padmanabhan serves as Associate Professor in the Department of Chemical Engineering at Rochester Institute of Technology's Kate Gleason College of Engineering, with additional faculty appointment in the School of Mathematics and Statistics.

Her academic credentials include:

• B.Tech. in Chemical Engineering from Indian Institute of Technology, Madras (India)
• Ph.D. from Cornell University

Research centers on computational thermodynamics of soft materials, particularly polymer-colloid systems where her group develops rational design approaches to manipulate hierarchical structures through self-assembly. Key investigations address chirality amplification mechanisms, thermodynamic frustration in block copolymers, and non-equilibrium phase separation phenomena using molecular simulations and statistical mechanics frameworks. This work bridges fundamental physics with materials engineering applications.

Recent publications (2017-2023) reveal consistent methodological focus on computational soft matter physics, with evolving emphasis from colloidal gel mechanics toward chiral polymer systems. Articles demonstrate strong disciplinary integration across polymer science, statistical thermodynamics, and rheology, increasingly incorporating chirality as a design parameter for next-generation materials.

Major recognitions include:

• NSF CAREER Award (2022) for "Chirality and polymer thermodynamics: frustration and amplification" supporting both materials research and spatial cognition pedagogy
• ACS PMSE Early Investigator Award (2024) recognizing outstanding contributions to polymer materials science

Her grant portfolio features the NSF CAREER award enabling dual-track research on chiral self-assembly and engineering education innovation. She actively mentors undergraduate and graduate students through the Poornima Research Group while leading STEM outreach initiatives to increase women's participation in engineering fields.

The Poornima Research Group employs advanced computational techniques to investigate fundamental soft matter problems, currently focusing on chirality-driven self-assembly in polymers and colloidal systems, with applications spanning biomaterials design and nanofabrication.