Her Story
About Sayane
Sayane (Shayoni) Shome is a computational biologist and AI researcher specializing in the intersection of artificial intelligence, multi-omics, and clinical data science. She has over 12 years of experience in research and bioinformatics, building computational models and machine learning solutions to address complex biological and healthcare challenges. Her expertise lies in developing bioinformatics frameworks and AI-driven algorithms that integrate genomics, transcriptomics, and clinical data to generate actionable insights for translational medicine.
She is currently a Bioinformatics Programmer III at the University of California, San Francisco (UCSF), where she focuses on HIV research and uses advanced data science methods to analyze clinical outcomes following treatment in HIV-related patient populations. At UCSF, she works with large-scale multi-modal biomedical datasets, applying reproducible bioinformatics pipelines and statistical learning approaches to better understand disease progression and therapeutic response. Her work is centered on transforming complex clinical and genomic data into insights that can support improved decision-making in healthcare.
Previously, during her postdoctoral training at Stanford University, she developed AI models for biomedical imaging analysis in newborn health, including deep learning approaches for interpreting neonatal imaging data. She also designed and applied bioinformatics methods to study bronchopulmonary dysplasia, a severe lung disease affecting premature infants, integrating transcriptomic and multi-omics datasets to investigate disease mechanisms. Originally from a small town in India, she has built her academic and research career through PhD and postdoctoral training with a strong commitment to impactful science. Her long-term vision is to become a healthcare deep-tech entrepreneur, building innovative solutions that advance medicine and create meaningful global impact.
Her Interview
Ten minutes with Sayane
01What do you attribute your success to?
I attribute my success to determination, perseverance, and my support system. I've been very lucky to have friends, my partner, and my family who have been incredibly supportive throughout my journey. It definitely takes a village - you cannot do it all alone. Having people around me who believe in me and support me has helped me tremendously as I've pursued my goals in research and worked toward my long-term vision of becoming an entrepreneur in healthcare.
02What’s the best career advice you’ve ever received?
The best career advice I ever received came from a very successful professional who has worked at Google and Apple. She told me that women don't need mentors as much as they need good opportunities. She advised me to strive for those opportunities and show the confidence that I can do it. This advice really resonates with me even today and has shaped how I approach my career. It reminds me to be bold in seeking opportunities rather than waiting for someone to guide me every step of the way.
03What advice would you give to young women entering your industry?
I would say that this field of bioinformatics and AI has always been very fast evolving. When bioinformatics first emerged, there was a boom. Then AI and deep learning came and there was another boom. Now large language models are creating a huge boom, and currently it's all about Agent AI in the field of bioinformatics. The field evolves very fast, so you need to keep up with the pace and be passionate about or excited about learning new things. That is a very key quality one should have. It's not like you can just get exhausted or tired - you have to be curious about knowing about new things. That's what I would advise anybody who is going to start ahead in this field.
04What values are most important to you in your work and personal life?
The most important value to me is keeping my focus on the bigger picture and my long-term goals. I always look at my long-term vision, which is to become a successful entrepreneur in the field of healthcare, particularly in deep tech. Thinking about that long-term goal helps me coordinate everything and manage my time and productivity across all the different things I do. I've also learned the importance of not taking on too much deadweight for too long. I would advise my younger self to let go of things quicker and learn to say no where needed. You should focus on the things you are truly passionate about and happy to do, rather than reducing your efficiency by holding onto things that don't serve you. Taking care of what really matters to you is essential.
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