Summary
Aditya Lahiri is a Bioinformatics Scientist II and postdoctoral-trained researcher with eight years of experience applying AI, probabilistic graphical models, and statistical learning to cancer and plant genomics. He specializes in harmonizing unstructured biomedical text using transformer-based embeddings and LLM-derived text embeddings to enable data integration across clinical trials and tumor nomenclature. His background in Bayesian and Markov networks informs mechanistic simulations of signaling pathways, while practical skills in ML, R/Bioconductor, and Python have supported projects from CRISPR analysis to UAV-based phenotyping. Based in Philadelphia at CHOP, he builds scalable pipelines and mentors collaborators to translate complex models into usable tools. Notably, he blends rigorous engineering training (PhD in EEE) with entrepreneurial experience from an NSF I-Corps winning team, giving him a rare product-facing perspective for research-driven solutions.
8 years of coding experience
7 years of employment as a software developer
High School Diploma Natural Sciences, High School Diploma Natural Sciences at Delhi Private School, Sharjah
Doctor of Philosophy - PhD Electrical and Electronics Engineering, Doctor of Philosophy - PhD Electrical and Electronics Engineering at Texas A&M University
Bachelor of Science (B.S.) Electrical Electronics and Communications Engineering, Bachelor of Science (B.S.) Electrical Electronics and Communications Engineering at Purdue University
Bengali, Hindi, Marathi, Sanskrit, Arabic, Urdu, German