Stanford Doerr School of Sustainability
Showing 1,211-1,220 of 1,469 Results
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Nicholas Siemons
Research Engineer, Precourt Institute for Energy
Postdoctoral Scholar, Materials Science and EngineeringBioNicholas began his academic career by studying integrated Masters at University College, London. During this time he published his first article, "Multiple exciton generation in nanostructures for advanced photovoltaic cells" - a review of how to produce photovoltaics with greater than 100% internal efficiencies. Following this Nicholas began research into solar voltaics and organic batteries in the group of Prof. Jenny Nelson at Imperial College, London. During this time Nicholas developed his keen interest in how to relate the chemical design of polymers to their ability to function as battery electrode materials. To achieve this goal, Nicholas applies atomistic simulation methods to such polymer systems, and relates the simulated findings to experimental results, bridging the gap between chemistry and device properties. As well as linking molecular chemical design to device performance, Nicholas applies novel simulation and analysis methodologies to study these systems, including Molecular Dynamics, Density Functional Theory, Molecular Metadynamics and Network Analysis.
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Harshit Singh
Research Assistant, Woods Research Natural Capital Project
Staff, Woods Research Natural Capital ProjectBioHarshit Singh is an AI Researcher and Engineer working across generative AI, agentic systems, and environmental modeling. He is currently working on the Natural Capital Project at Stanford, where he develops LLM-driven workflows for the InVEST ecosystem to enhance automation, data integration, and sustainable development research. He is also building HarshanAI, an emotionally intelligent voice-AI companion.
Previously, he worked at Amazon Web Services, contributing to Bedrock Flows and AgentCore for large-scale generative AI systems and at the MIT-IBM Watson AI Lab, leading DiffuseKronA as first author and advancing parameter-efficient methods for personalized diffusion models. He has also supported climate and energy research at the Center for Global Sustainability, University of Maryland through the development of G-MAST, a global methane abatement solutions database. His work emphasizes practical innovation, scalable AI systems, and applying machine learning to real-world societal and sustainability challenges.
