Hello, my name is Ian, and welcome to my portfolio. The future of therapeutic R&D is based on more efficient and effective assessment earlier in the product pipeline, facilitated by artificial intelligence. Computational modeling will support scientists in identifying novel targets and dissecting laboratory data to prioritize the end result in the clinic. We get there by ceaselessly questioning everything we think we know about life itself. I am a passionate immunology and machine learning researcher based in Boston, Massachusetts. As a scientist, my mantra is to rapidly iterate on projects solving real-world problems. See below for examples.
Associate Scientist at Factor Bioscience
▪️ map of the General Index & modeling scientific ontology: https://github.com/hayitsian/General-Index-Visualization
▪️ predicting CRISPR gRNA activity a priori by sequence: https://github.com/hayitsian/Gene-Editing-Guide-LLM
▪️ graph neural networks modeling localized inflammation
Rapid M. Tuberculosis Diagnostic Test for Limited Resource Settings
Efficient mRNA Delivery Enables Rapid Prototyping of Gene-Edited Macrophages for Immunotherapy
Delivery Strategies for STING Agonists
Class Schedule Optimization Using Algorithmic Pathfinding: High School Capstone Project