Rate My Professor Sneha Goenka

Sneha Goenka is an Assistant Professor of Electrical and Computer Engineering in the Engineering faculty at Princeton University, with associated faculty appointments in the Computer Science Department, Princeton Institute for Computational Science and Engineering (PICSciE), and Princeton Precision Health Initiative. She joined the Princeton faculty in January 2025 after serving as a Postdoctoral Research Scholar at Stanford School of Medicine under Professor Euan Ashley. Goenka received her Ph.D. in Electrical Engineering from Stanford University in 2024, advised by Professor Mark Horowitz, with a focus on hardware-software systems for high-performance evolutionary and clinical genomics. She holds a dual B.Tech. and M.Tech. degree in Electrical Engineering from the Indian Institute of Technology Bombay, awarded in 2017. Earlier experiences include internships at NVIDIA Research in 2022 and D. E. Shaw Research in 2018, as well as her Master's thesis in the High-Performance Computing lab at IIT Bombay.

Goenka's research centers on computer systems architecture and computational genomics, developing specialized hardware and software to accelerate large-scale genomic data analysis for clinical diagnostics and research applications. Her contributions include leading the computational development for the world's fastest whole-genome diagnosis technique, achieving genetic diagnosis within eight hours using nanopore sequencing and identifying pathogenic variants in 42% of critical care patients. She created SegAlign, a scalable GPU-based whole-genome aligner offering up to 14x speedup and 2.3x cost reduction, and Darwin-WGA, a co-processor that boosts whole-genome alignment performance per dollar by up to 24x and sensitivity. Key publications are 'Accelerated identification of disease-causing variants with ultra-rapid nanopore genome sequencing' (Nature Biotechnology, 2022), 'Ultrarapid nanopore genome sequencing in a critical care setting' (New England Journal of Medicine, 2022), 'SegAlign: A scalable GPU-based whole genome aligner' (SC, 2020), and 'Darwin-WGA: A co-processor provides increased sensitivity in whole genome alignments with high speedup' (HPCA, 2019). Her honors include MIT Technology Review Innovator of the Year (2025), Forbes 30 Under 30 in Science (2023), NVIDIA Graduate Fellowship (2022), ACM Heidelberg Laureate Forum Young Researcher (2024), Stanford Centennial TA Award (2024), and Cadence Women in Technology Scholar (2021).