pkrishnamoorthy

Preethi is a computer scientist with experience in Artificial Intelligence, particularly LLMs. Her path into computer science was through computational biology, where her first research experience involved developing machine learning models for classifying breast cancer biopsy images using deep neural networks and techniques like K-Means clustering and Random Forest – techniques that are relevant again as we start using protein embeddings for finding candidates and classification. She’s currently continuing to hone her skills as a junior studying CS and Robotics at Carnegie Mellon University’s School of Computer Science, where she’s involved in everything from engineering prosthetic hands to designing wearables. In addition to her academic background, an entire summer spent implementing end to end pipelines for fine-tuning and evaluating LLMs has honed a skillset that is quite valuable for this project. This type of work, writing new differentiable potential functions for diffusion and fine-tuning embedding models for classification, often requires going beyond the documentation and diving into the research papers behind the transformers, so we’re glad to have someone with that skillset on this team.

October 2023