"Assessing ESG Compliance and Impact: A Zero-Shot Learning Approach to Analyzing Fortune 500 Companies' Sustainability Reports":

Research Abstract: In the evolving landscape of sustainable investing, environment, social, and governance (ESG) metrics are key for assessing companies beyond financial performance. Recognizing the growing relevance of ESG to stakeholders, companies release annual sustainability reports outlining their ESG goals and progress. This paper analyzes how Fortune 500 companies such as Apple, Walmart, Chevron, General Motors, and JP Morgan integrate ESG considerations into their operations and reporting. By extracting text from these reports, classifying them into nineteen ESG subcategories using a zero-shot learning model, and comparing the results to actual data, the analysis reveals that while these companies have made significant strides in environmental sustainability and diversity, progress varies across different areas. This research streamlines the analysis of complex sustainability reports, offering a scalable approach through zero-shot learning, which reduces the need for large labeled datasets. Furthermore, it identifies emerging ESG subcategories without requiring additional labeled data, simplifying the examination of numerous reports and providing key insights into corporate ESG compliance.

Mentorship: I researched under Dr. Mohammad Taher Pilehvar, an associate lecturer and researcher at the University of Cambridge. Dr. Pilehvar provided me with guidance when it came to fine-tuning the technical approach and methods of my project, as well as formulating my findings into the form of a research paper.

Recognition: My research was accepted to the 2025 IEEE International Conference on Data Science and Machine Learning Applications, the 2024 IEEE Global Congress on Emerging Technologies, and the 2024 Johns Hopkins Institute for Data Intensive Engineering and Science

IEEE Xplore Link: https://www.idies.jhu.edu/news-events/events/idies-annual-symposium/