Hire Aayush S. - AI Engineer

* Spearheading the development of innovative GenAI-based methodologies aimed at extracting and mapping critical information from research papers, thereby enhancing data accessibility and usability * Conducted exploratory data analysis, performed data cleaning, and prepared datasets for model development to predict material properties. Built and evaluated machine learning models using XGBoost, leveraging Python libraries (PyTorch and Sklearn) and Jupyter Notebook. * Transformed the raw extracted data, which was then loaded (ETL) into the Total Materia database, ensuring compliance with specified standards * Engineered and deployed web automation scripts leveraging Python, Selenium, and Pandas for data extraction and automated PDF downloads. * Designed and optimized a solution utilizing Artificial Intelligence-based Python libraries such as Camelot and PDFQuery for concurrent data parsing from thousands of PDFs. * Experience in developing graphical user interfaces (GUIs) for software applications.

* Worked with time-series data to train Recurrent Neural Networks, including Gated Recurrent Units (GRU) and Feed-Forward Neural Networks. Conducted in-depth analysis and study to recommend effective approaches for predicting stress behaviour in materials, providing data-driven solutions to achieve accurate predictions. Gained immense experience in applying packages such as TensorFlow, ML Flow, Scikit-learn, NumPy, Pandas, Matplotlib, and many others Automated the generation of simulation data by utilising algorithms programmed in Python. These algorithms have been instrumental in generating data from the FEM software LS-Dyna, contributing to the training and validation of Machine Learning models