Raman Rao is a postdoctoral researcher at North Carolina State University studying microbial processes in municipal waste, with implications for improving real-time sorting and characterization. In this Postdoc Portrait interview, he shares how he transformed his interest in microbiology into real-world actionable insights.
Harnessing AI and Hyperspectral Imaging for Waste Valorization
Q | What drew you to the interplay between microbes and waste management?
As a student, I was amazed the first time I observed microorganisms under a microscope. Seeing tiny, invisible lifeforms actively moving and functioning sparked a deep curiosity about how much unseen work was happening at microscopic scales. That curiosity pushed me to explore microbiology beyond textbooks. As I learned more, I became particularly interested in how microbes drive large-scale processes, especially in bioenergy and bioconversion. Today, my research connects microbial processes with material and waste characterization.
Q | What scientific problem are you trying to solve?
My favorite research project started with a simple problem I kept seeing repeatedly. We design sophisticated conversion microbes, but we feed them waste we barely understand. Municipal solid waste arrives as a complex mixture of materials, moisture levels, and contaminants, yet it is often treated as a single, averaged feedstock. That disconnect leads to poor performance and failed scale-up. To address this, I am working on a project that uses hyperspectral imaging combined with AI to see what the human eye cannot see. Watching raw data turn into actionable insight reminds me why I entered research in the first place.
From Microscopic Curiosity to Large-Scale Sustainability
Q | What has been the most rewarding part of your research journey?
The most exciting part began when I started working with a research team from different backgrounds and began applying hyperspectral imaging and AI in waste management. Earlier in my career, my research focused on individual processes such as microbial conversion, typically studied under controlled laboratory conditions. That perspective changed when I began working with landfill-bound municipal solid waste. The moment this transition became real was seeing hyperspectral and visual data collected from moving waste streams translate into meaningful material identification including real-time waste classification.
Q | If you could be a laboratory instrument, which one would you be and why?
I would be a hyperspectral camera, because it sees what human eyes miss. While most instruments give a single number or a narrow view, a hyperspectral camera captures both spatial and chemical information at once.
Responses have been edited for length and clarity.
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