My Research

Title: Intuitive UI and Cloud pipeline design for AI-enabled computational materials design
PI: Mingjie Liu, University of Florida Assistant Professor, Department of Chemistry
May 2023 - Present
My research focuses on enhancing the AI-driven platform, CarbonHTP, developed by Dr. Liu’s group. The project aims to create an intuitive user interface that simplifies the data upload process, making computational data on carbon-based materials accessible to researchers and students without requiring specialized computational skills. This work is designed to facilitate the discovery of new molecules that can serve as electrocatalysts for CO2 reduction, fuel cells, ammonia synthesis, and membranes for water purification and organic solar cells. By improving user interaction with the platform and employing cutting-edge AI and machine learning tools, the research seeks to accelerate the design and discovery of new carbon materials for energy applications. Ultimately, this automated pipeline will lay the groundwork for AI-guided carbon materials design, advancing sustainable energy solutions.

In this project, I am responsible for developing a web-based user interface that simplifies the process of uploading computational data on carbon-based materials. This includes creating template-based input forms, real-time validation checks, and user-customization features to streamline data submission. Additionally, I am implementing advanced visualization tools within the UI, such as interactive 3D models and customizable data plots, to make complex data more accessible and understandable. My role also involves enhancing data retrieval and analysis capabilities by integrating machine learning tools directly into the UI, enabling users to run predictive models and simulations. By focusing on user experience and accessibility, I aim to empower researchers and students to actively engage in AI-guided materials design, contributing to advancements in sustainable energy applications.