Research Areas
The Learning from Data Research Laboratory focuses on developing modern machine learning and artificial intelligence techniques to extract value from data. Our lab conducts research across a wide spectrum, including recommender systems, time-series forecasting, and network analysis, utilizing deep learning, graph theory, and statistical modeling. The focus of these studies is to provide data-driven, innovative, and reliable solutions to complex engineering problems by combining academic excellence with advanced research.
Dedicated to integrating human learning methodologies into computer systems, our laboratory conducts extensive research in data mining, machine learning, and optimization. We develop neural networks, decision support mechanisms, and deep learning-based models utilizing data from diverse environments ranging from web pages and financial records to social networks and text-based content. Our work is further enriched by modern research topics such as Large Language Models and algorithmic fairness, aiming to advance knowledge discovery processes through scientific methods and contribute to global academic literature.
- Fairness in Recommender Systems
- Demand Forecasting in E-commerce and Fashion Industry
- Earthquake Prediction and Detection
- Graph Neural Networks (GNNs) and Applications
- Deep Learning-Based Recommendation Models
- Explainable Artificial Intelligence (XAI) and Anomaly Detection
- Dynamic Pricing for Tourism Industry
- Time-Series Analysis and Forecasting
- Social Media Analysis and Community Detection
- Flash Point Prediction of Petroleum Products
Affiliated Faculty Members