22.10.2024
SEMINAR:Leveraging AI for Data Extraction and Broader Applications...
Artificial intelligence is rapidly becoming a transformative tool in scientific discovery, playing a crucial role in accelerating research across various fields. In materials science, it has shown the potential to significantly augment traditional methods by providing insights that might have been unattainable using conventional approaches alone. However, the success of machine learning models in materials science is highly dependent on the availability and quality of data. Collecting high-quality datasets remains a major challenge, especially in materials science, where experimental data is often sparse and buried in the unstructured language of scientific literature. AI offers promising solutions for automating data extraction from these vast text resources. Beyond data extraction, it is also being applied to predict material properties, optimize experimental design, and accelerate the discovery of new materials. In this seminar, I will elaborate on how I am integrating AI to address the challenges of data mining from scientific literature.
