Sneha Goenka, an assistant professor of electrical and computer engineering at Princeton and MIT Technology Review’s 2025 Innovator of the Year, helped develop a rapid-sequencing pipeline that can deliver a genetic diagnosis in hours rather than weeks. The effort began five years ago and combined software, hardware and workflow redesign to stream sequencing data from instruments into cloud computation, cut inefficiencies in data transfer and orchestrate base calling and alignment in parallel. The original pipeline reduced the compute time to identify mutations from about 20 hours to 1.5 hours, with downstream filtering and manual curation taking up to three hours, and later refinements shortened the end-to-end time to roughly six hours.
Goenka’s technical contributions included designing a cloud computing architecture that minimized communication overhead between sequencer and cloud, determining the precise number of reusable communication channels, and implementing algorithms to assign data streams directly to dedicated cloud nodes for base calling. She also wrote software to trigger sequence alignment as soon as a batch finished base calling while simultaneously starting base calling for the next batch, ensuring efficient utilization of computational resources. The team worked with genetic counselors and physicians to build filters that flag clinically relevant mutations for final specialist review.
The pipeline has been tested on 26 patients and was put to a critical test in 2021 when a 13-year-old patient named Matthew arrived at Stanford children’s hospital with heart failure. His blood was drawn on a Thursday and the transplant committee met on Friday. The rapid sequencing revealed a genetic mutation that led to the patient being placed on the transplant list and receiving a new heart three weeks later. Goenka is now cofounder and scientific lead of a startup aiming to deploy the technology more broadly, and she is adapting filters to use more diverse reference genomes from the Human Pangenome Project to reduce bias toward people of European descent. The work grew out of personal motivation and Goenka’s education in Mumbai and at the Indian Institute of Technology Bombay, and it is already influencing care in neonatal and pediatric intensive care units.
