Sustainability Research

The growing global reliance on digital infrastructures has led to significant energy consumption, raising concerns about sustainability. While initiatives such as Environmental, Social, and Governance (ESG), Socially Responsible Investing (SRI), and Green Artificial Intelligence (GreenAI) aim to address these concerns, they are hindered by unreliable data for performance assessment. Transparent and trustworthy data is crucial to evaluating these initiatives’ effectiveness and establishing policies that drive impactful environmental actions. A decentralized approach leveraging interdisciplinary AI technologies can bridge these gaps, contributing to the broader goal of achieving carbon neutrality through innovative IT solutions. By implementing AI, blockchain, and token economics, this project seeks to improve energy efficiency, promote data reliability, and drive sustainability through decentralized innovations. The research will culminate in theoretical models, empirical analyses, and real-world applications, reinforcing DKU’s contributions to international higher education and global sustainability efforts.

Project Description
Blockchain-Based Solar Energy Management Platform: Integration of SolarSave

SolarSave is developed to explore how distributed technologies can enhance transparency, efficiency, and engagement in solar energy systems. SolarSave is designed as a modular platform that enables individuals, communities, and institutions to participate in sustainable energy management. The system empowers users to monitor solar panel output, predict future efficiency, trade digital solar assets, and receive SolarToken rewards for eco-friendly behavior. The primary goals of the system are: (1) Enable decentralized solar panel registration and tracking through blockchain. (2) Use AI forecasting models to predict solar production. (3) Visualize solar performance metrics through an interactive dashboard. (4) Incentivize sustainable behavior with a token economy.

Fossil Fuel Prices and Capital Cost: A Machine Learning Driven Study on Energy Transition

This research explores the long-term financial implications of fossil fuel price volatility on the Weighted Average Cost of Capital (WACC) in energy transition projects. In response to global efforts to reduce greenhouse gas emissions and fulfill the 1.5°C climate target, the project employs advanced artificial intelligence techniques to forecast fossil fuel prices and analyze their effects on capital costs across a diverse range of clean energy technologies, including nuclear, hydro, biomass, and wind. By coupling predictive modeling with financial analysis, this work supports more robust investment planning and policy development for sustainable energy transitions in both importing and exporting regions.

Digital Technology for Sustainability Symposium and the Finance Forum 2025

On April 18, 2025, Duke Kunshan University hosted the Digital Technology for Sustainability Symposium and the Finance Forum 2025, bringing together leading scholars, industry pioneers, and innovative students from institutions and organizations including Westlake University, NYU Shanghai, XJTLU, McKinsey Global Institute, Intel Labs, Amazon Web Services, and Goldman Sachs. These events embodied DKU’s interdisciplinary ethos and its commitment to advancing sustainable development through digital innovation. By facilitating knowledge exchange across academia, industry, and the public sector, the symposium underscored the critical role of digital tools in shaping a sustainable and equitable future. It also empowered DKU students to take active leadership in the intersection of technology, society, and the environment.

Faculty Leads
MCH

Prof. Ming-Chun Huang

Associate Professor, Duke Kunshan University

luyao

Prof. Luyao Zhang

Assistant Professor, Duke Kunshan University

Contributors
WHP

Haipeng Wang

Research Fellow, Duke Kunshan University

CDS

Dongsheng Cheng

Research Fellow, Duke Kunshan University

non

Shilin Ou

Undergrad Student, Duke Kunshan University

non

Zhenshan Zhang

Undergrad Student, Duke Kunshan University

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