Summary
Eric Chen is a Senior Bioinformatics Research Scientist in Austin with a decade of experience building GPU-accelerated AI systems and advanced statistical models for spatial and structural biology. He has driven impactful, open-source tooling at Carnegie Mellon for HuBMAP that automated segmentation QA/QC and improved segmentation across thousands of tissue images, and he translates 2D methods to 3D imaging to overcome limited-data bottlenecks. His PhD work produced generative models that synthesize realistic tissue images and an unsupervised framework that distinguished normal from metastatic cells with a 0.9 AUC-ROC on cryo-ET data, demonstrating a rare combination of theory and practical deployment. Now at St. Jude, he applies scalable ML and GPU engineering to biomedical problems, blending deep learning, interpretable models, and production-focused software design. He often leverages interpretable network motifs and weak supervision to extract biological insight, making complex model outputs actionable for researchers.
10 years of coding experience
8 years of employment as a software developer
MS Electrical Engineering, MS Electrical Engineering at Texas A&M University
PhD Computational Biology, PhD Computational Biology at Carnegie Mellon University School of Computer Science
BE Electrical Engineering, BE Electrical Engineering at South China University of Technology