AI for Sustainability: What Companies Say and What They Do for the Environment

2026 Projects

AI for Sustainability: What Companies Say and What They Do for the Environment

Format: On Campus or Online
Number of Students: 4 high school students
Project Duration: July 1, 2026 – July 31, 2026
Application Deadline: June 5, 2026
Project Supervisor: Asst. Prof. Dr. Ayşe Çetinel (Faculty of Business)
Research Areas: Sustainability, Artificial Intelligence, Large Language Models (LLMs), Natural Language Processing (NLP), Data Analysis, European Union Regulations
Daily Supervisor: Dr. Barlas Armatlı

Project Description:
Have you ever wondered if companies really do what they say about helping the environment? In this project, you will work with real company reports and public documents to explore how businesses talk about sustainability. You will help collect, clean, organize, and document this information to build high-quality datasets that can later be used in AI-based research.

About the Project:
Today, many companies share information about their sustainability and environmental efforts through reports, disclosures, and public announcements. Researchers study these materials to better understand how companies communicate their environmental commitments. In this project, students will help prepare structured, reliable, and well-documented datasets from these sources so that the information can later be used in AI-based research.

Project Objectives

Introduce students to sustainability reporting, ESG indicators, and corporate environmental communication.
Teach students how to collect, clean, organize, standardize, and document data in a systematic way.
Build structured datasets from company reports, disclosures, news items, and ESG indicators.
Produce high-quality, well-documented datasets ready for future AI-supported research.
Help students develop attention to detail and strong data management skills.

Project Tasks

Collect sustainability reports, annual reports, corporate disclosures, and ESG-related metrics from company websites and campus library databases such as Bloomberg and LSEG.
Extract relevant text and indicators into structured spreadsheets or tables using consistent formats.
Clean and standardize company names, years, dates, units, file names, and duplicate or missing entries.
Organize files and datasets using clear folder structures, naming conventions, and version control rules.
Check the dataset for completeness, consistency, and traceability to the original sources.
Assist in preparing small labeled or tagged data samples that may later support AI, NLP, or validation tasks.
Prepare a clear data dictionary describing variables, sources, formats, and coding rules.
Document all cleaning decisions, assumptions, and workflow steps so the dataset can be reliably reused by future researchers and AI tools.

Deliverables

A structured corpus of corporate sustainability documents with source metadata
A cleaned and standardized dataset of ESG and related firm-level indicators
A data dictionary describing variables, formats, and coding decisions
A log of data cleaning, organization, and quality-control steps
A clearly organized folder and file structure for the final dataset
Project documentation explaining how the dataset was prepared for future AI use

Benefits for the Student

Hands-on experience in building high-quality datasets for academic and AI-related research
Training in data collection, cleaning, organization, and documentation workflows
Exposure to sustainability, ESG reporting, and the responsible use of AI in research
Improved attention to detail, digital literacy, and structured research skills
Close mentorship from academic faculty

Requirements

Strong attention to detail and commitment to accuracy
Ability to work in a structured, careful, and responsible manner
Intermediate computer skills, especially in Excel and Word
At least intermediate English reading proficiency
Ability to work independently or as part of a team

Ethics & Confidentiality

Students are expected to handle research data responsibly and follow basic academic integrity and confidentiality principles.

2026 Projects

AI for Sustainability: What Companies Say and What They Do for the Environment

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