AI & Environment Resource HubHayder Zghair and Rushi Ganesh Konathala · 2025-07-04
This research explores how artificial intelligence (AI) can be leveraged to optimize packaging design, reduce operational costs, and enhance sustainability in e-commerce. As packaging waste and shipping inefficiencies grow alongside global online retail demand, traditional methods for determining box size, material use, and logistics planning have become economically and environmentally inadequate.
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Hayder Zghair and Rushi Ganesh Konathala. 2025-07-04. Using AI for Optimizing Packing Design and Reducing Cost in E-Commerce. https://www.mdpi.com/2673-2688/6/7/146 (AI & Environment Resource Hub; record paper-355; collection snapshot 2026-10-04).
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Shared topics: Materials and critical minerals; E-waste and circularity
Matbench Discovery is a benchmarking framework for machine learning models used in materials discovery, highlighting the importance of task-specific metrics and demonstrating that universal interatomic potentials can effectively pre-screen stable inorganic materials in high-throughput workflows.
Shared topics: Materials and critical minerals; E-waste and circularity
Adaptis is a diverse team of carbon reduction experts supercharged by a proprietary software platform for evaluating and optimizing building performance, whole-life carbon, and capex. We generate and recommend decarbonization scenarios, build project sequences, and keep all the data live in real-time so financial decision-makers can find answers in 15 minutes, not 15 days.
Shared topics: Materials and critical minerals; E-waste and circularity
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Shared topics: Materials and critical minerals; E-waste and circularity
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