Amanda Savage is a postdoctoral researcher in the newly established Cellular Intelligence and BioAnalytics (CIBA) Lab in Berkeley Lab’s Advanced BioProcess Development Unit (ABPDU). As CIBA’s inaugural postdoc, Amanda architected the wet-lab facility from the ground up and leads research on transforming traditional benchtop biology workflows into agentic, self-driving wet-labs. Amanda specializes in the end-to-end systems integration of wet-lab biology, hardware automation, and Artificial Intelligence (AI)/Machine Learning (ML). Leveraging this deep multidisciplinary expertise from her Ph.D., Amanda leads the rapid prototyping of closed-loop, cyber-physical systems that enable real-time, non-invasive, and autonomous in-line cellular control during live bioprocessing. By extracting single-cell phenomics from active bioreactors and feeding biological telemetry into custom-built cellular digital twins and physics-informed soft sensors, her work at CIBA-ABPDU is redefining how bioreactors are controlled and how bioprocessing is conducted to maximize the biosynthesis of high-value bioproducts.
Highlighting her leadership at the intersection of AI, robotics and wet-lab bioprocessing, Amanda has authored five first-author scientific peer-reviewed journal publications as of 2026, has showcased physical prototypes of her self-driving bioreactors at the prestigious Google AI Summit co-hosted by Purdue’s Institute for Physical AI in 2025, and has earned two regional awards from the Department of Energy (DOE) EnergyTech UP competitions in 2024-2023.
Education
- Ph.D. in Environmental and Ecological Engineering, Purdue University
- M.S. in Interdisciplinary Ecological Sciences and Engineering, Purdue University
- B.S. in Environmental Engineering, San Francisco de Quito University (USFQ)
Notable Papers and Publications
- Savage, A., Savage, S., Zhou, Z., “Artificial Intelligence-enabled real-time monitoring of intracellular lipid dynamics in microalgae via optical sensors and kinetic early-warning differentiation,” Bioresource Technology (2026).
- Savage, A., Savage, S., Zhou, Z., “Novel machine learning unlocks high lipid productivity and resolves trade-offs in algal biofuel production,” Renewable Energy (2025).
- Savage, A., Choi, Y., Zhou, Z., “Enhanced biomimetic algal lipid enrichment for improved biofuel production driven by non-stress viral lysis,” Bioresource Technology (2025).
- Savage, A., Choi, Y., Zhou, Z., “Dataset for investigating triacylglycerol accumulation in PBCV-1 infected Chlorella,” Data in Brief (2025).