Pittsburgh, Pennsylvania, United States
Conducting in-depth studies on the sensitivity of large language models, analyzing their performance and behavior under varying conditions.
Worked on optimizing vector search algorithms to improve the speed and accuracy of Retrieval-Augmented Generation (RAG) systems. Contributed to the development of NetApp’s AI Data Engine, enhancing its data indexing and retrieval capabilities for large-scale AI applications.
Help Professor Tuson with the content and structure of the course "introduction to problem solving in Python".
- Assist Professor Pustejovsky’s Lab to complete domain specific AMR(Abstract Meaning Representation) annotation. - Manually annotate and validate machine generated AMR graphs using AMR-dict and UMR writer. - Design and propose domain specific rules to adopt AMR graphs to suit for recipe data set - Using Python to pre-process jsonlines file and visualize event trigger and entity spans across sentences using spaCy and Flask.