Ishita Shah

Papers

Total Citations

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About

Ishita Shah is a researcher at the forefront of leveraging artificial intelligence for environmental sustainability, with a primary focus on intelligent waste management systems. Her most impactful work, the 2019 paper "AGDC: Automatic Garbage Detection and Collection," has garnered 25 citations and proposes a hygienic, cost-effective solution to the pressing challenge of urban solid waste. By integrating AI algorithms into automated detection and collection processes, Shah addresses the inefficiencies of contemporaneous waste management methods, offering a scalable approach for growing urban populations. Her contributions lie at the intersection of computer vision, robotics, and environmental engineering, demonstrating how smart technologies can tackle real-world infrastructural problems. Beyond this flagship study, Shah’s research continues to explore the deployment of machine learning in civic applications, aiming to reduce human exposure to unsanitary conditions while optimizing resource allocation. Her work stands as a compelling example of applied AI for social good, inspiring students and researchers to consider how computational innovation can drive cleaner, more sustainable cities.