Dr. Ratna Saripalli, PhD in artificial intelligence and machine learning, is a research line manager with Pacific Northwest National Laboratory (PNNL) and the chief data officer in PNNL’s Environmental Molecular Sciences Division and the Environmental Molecular Sciences Laboratory (EMSL). As a technology leader and software engineer, she has industry experience in conceiving, implementing, and managing artificial intelligence, machine learning, data engineering, and analytics products and platforms. Before rejoining PNNL, she served as the vice president of technology at Berkeley Lights, in charge of developing computational methods for large datasets such as gene expression, metabolomics, and proteomics. Before that, she was a senior global director of data science at GE HealthCare for three years, developing world-class artificial intelligence products to revolutionize health care and improve clinical outcomes. She won the GE HealthCare Key Innovator award twice and has contributed to several patents and publications. She served at Microsoft for 11 years in various lead roles, helping ship Bing AdCenter, Office365, and Windows data science and engineering products. Before joining Microsoft, she was a research scientist at PNNL for six years, contributing to global research projects pivotal to genomics and life sciences.
- Scalable, efficient deep reinforcement learning methods for health care and life sciences
- Artificial intelligence/machine learning model compression methods
- High-performance computing and distributed big data management platforms
- MBA, University of California
- PhD in artificial intelligence and machine learning, Colorado State University
- MS in biomedical informatics, Stanford University
- Michael D. Grafham, Kent D. Mitchell, Pei Li, and Venkata Ratnam Saripalli. Attribute Collection and Tenant Selection for Onboarding to a Workload. U.S. Patent US10387212B2, filed 15 June 2017, and issued 20 August 2019. https://patents.google.com/patent/US10387212B2/en.
- Venkata Ratna Saripalli, Gopal Avinash, Min Zhang, Ravi Soni, Jiahui Guan, Dibyajyoti PATI, and Zili Ma. Medical Machine Time-Series Event Data Processor. U.S. Patent US11404145B2, filed 27 November 2019, and issued 02 August 2022. https://patents.google.com/patent/US11404145B2/en.
Dong, X., T. Tan, M. Potter, Y.-C. Tsai, G. Kumar, and V. R. Saripalli. 2021. "To raise or not to raise: The autonomous learning rate question." arXiv preprint arXiv:2106.08767. https://doi.org/10.48550/arXiv.2106.08767.
Dong, X., M. Potter, G. Kumar, Y.-C. Tsai, and V. R. Saripalli. 2021. "Automating Augmentation Through Random Unidimensional Search." arXiv preprint arXiv:2106.08756. https://doi.org/10.48550/arXiv.2106.08756.
Saripalli, V. R., D. Pati, M. Potter, G. Avinash, and C. W. Anderson. 2020. "Ai-assisted annotator using reinforcement learning." S.N. Computer Science 1 (6): 1–8. https://doi.org/10.48550/arXiv.1910.02052.
Soni, R., J. Guan, G. Avinash, and V. R. Saripalli. 2019. "HMC: a hybrid reinforcement learning based model compression for healthcare applications." In 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE). Vancouver, BC, Canada, August 22–26, 2019. https://doi.org/10.1109/COASE.2019.8843047.
Pati, D., C. Favart, P. Bahl, V. Soni, Y.-C. Tsai, M. Potter, J. Guan, X. Dong, and V. R. Saripalli. 2019. "Impact of Inference Accelerators on hardware selection." arXiv preprint arXiv:1910.03060. https://doi.org/10.48550/arXiv.1910.03060.
Dong, X., J. Hong, H.-M. Chang, M. Potter, A. Chowdhury, P. Bahl, V. Soni, Y.-C. Tsai, R. Tamada, G. Kumar, C. Favart, V. R. Saripalli, G. Avinash. 2019. "FastEstimator: A Deep Learning Library for Fast Prototyping and Productization." arXiv preprint arXiv:1910.04875. https://doi.org/10.48550/arXiv.1910.04875.