Projects
Project addresses the critical role of Artificial Intelligence (AI) and Machine Learning (ML) in advancing the diagnosis, treatment, and understanding of neurodegenerative diseases such as Alzheimer's, Parkinson's, and multiple sclerosis. AI and ML offer revolutionary benefits in medical research, particularly in neuroimaging, where they can detect subtle brain changes, improve diagnostic accuracy, and personalize treatments. These technologies assist in early disease detection, differentiate overlapping disease features, and aid in theranostics by analyzing neuroimaging data and simulating patient responses to treatments. However, the project also acknowledges significant challenges, particularly the intrinsic biases within AI and ML algorithms, including gender, racial, demographic, and data acquisition biases, which can impact medical decision-making and healthcare outcomes. Addressing these biases is crucial to ensure the optimal application of AI and ML in neurodegenerative disease management.
Project led by Boğaziçi University, focuses on fostering digital innovation in Small and Medium Enterprises (SMEs), hospitals, public sector organizations, and professionals in the fields of healthy living, active aging, Ambient Assisted Living (AAL), and intelligent environments. It emphasizes creating a holistic environment where digital health solutions can thrive, not just through individual technologies, but by building an interconnected system that encourages new ideas and advancements, especially for aging individuals.
It is aimed to contribute to reducing the factors that cause climate change. Therefore, our project includes providing quality and uninterrupted service in the grid network with Transformer Location and Capacity Optimization, Consumption Forecasting, Capacity Optimization work, and reducing both team and fault-maintenance-repair costs with fault prediction and predictive maintenance work. It is evaluated that the intermediate targets will provide various side benefits, causing savings in many expense items and contributing to reducing the carbon footprint.
With the modular software planned to be developed, the category and subcategory information provided by web crawling and other sources within the Turkish Statistical Institute (TUİK), job postings can be stored, processed, and analyzed in the big data ecosystem as batch and stream data. It is aimed to label data with taggers and trained generative language algorithms to classify positions and skills from job postings with Artificial Intelligence algorithms, and to design a web-based system that allows all results to be visualized and used effectively by relevant users on a province-by-province basis for the most advertised occupational groups and skill types.
