Maya Venkatraman
An intro to me and my work :)
About Me
I’m Maya Venkatraman, a Research Software Engineer at the AlQuraishi Laboratory.
In the past, I worked at Google Research, applying computer vision to dermatologic image classification (Derm on Lens). I also contributed on a 20% basis to genomics projects, including DeepVariant and DeepNull.
Before that, I worked at YouTube Trust and Safety, building infrastructure for ML-based spam detection.
Publications
Scholar
Ginsberg, M., Venkatraman, M., Esposito, D., & Fthenakis, V. (2022). Minimizing the cost of hydrogen production through dynamic polymer electrolyte membrane electrolyzer operation. Cell Reports Physical Science, 3(6).
Ginsberg, M., Zhang, Z., Atia, A., Venkatraman, M., et al. (2022). Integrating solar energy, desalination, and electrolysis. Solar RRL, 6(5).
Sayres, R., Jain, A., Venkatraman, M., et al. (Expected 2025). Impact of a consumer-facing, AI-powered informational tool on retrospective evaluation of skin concerns. In Progress.
Interests
Sex-mediated differences in disease pathogenesis – how do Xi and Y differentially affect genomic regulation on autosomal chromosomes? How does this explain some of the sex-biases we observe in disease?
Diverse representation in genomic datasets. Expanding diversity in genomic datasets can (1) increase statistical power (provided that sample size increase outweighs standard error), (2) uncover population-specific variants, and (3) enhance the generalizability of findings, driving equitable precision medicine and deeper insights into disease mechanisms.
Developing selective learning methods to enhance the efficiency and accuracy of training models for genome-related prediction tasks.
News & Media
Innovation & Enhancement in Teaching
U.S. Presidential Scholars Program Semifinalist
National Merit Scholarship Recipient
Contact
You can reach me in a couple different ways - Linkedin or at maya.venkatraman1@gmail.com. NOTE: do not omit the “1” in the email address, or you will reach a different woman with a comparable cultural background.
Favorite Books
- Howl’s Moving Castle by Diana Wynne Jones – significantly better, though far less famous than the movie, with a much more coherent plot.
- Invisible Women – the chapter on disparities in the medical system profoundly reshaped my understanding of the research and funding landscape in the United States, illuminating systemic biases present at nearly every stage of biomedical discovery.
- This is How You Lose Her by Junot Diaz – a heart-rending last chapter that captures some of the most profound sentiments expressed by humanity.