We are continuing to hire positions to support our on-going work in Ghana and Kenya. These positions will be critical in helping us execute our vision of improving infrastructure around the world. Please reach out to our team if you want to join us!
CEO & Founder
Noah loves tech designed to inform policy decisions, monitor the longterm impact of those decisions, and hold underperforming systems and stakeholders accountable. Here he can be seen leftmost, deploying PowerWatch in Accra with Pat, Josh, and Kwame.
He started working on the ideas behind nLine 8 years ago during his PhD in Electrical Engineering at the University of California, Berkeley. He has spoken in India, Ghana, Kenya, and the United States on issues related to energy monitoring, and most recently, based on his work developing the technology underpinning nLine, was the recipient of the Sevin Rosen Funds Award for Innovation, given by UC Berkeley EECS based on outstanding technical achievement in Computer Sciences or Electrical Engineering research.
CTO & Founder
Josh is passionate about architecting systems that make data and the sensors that collect that data more accessible to non-experts. He joined Noah three years ago to help build early versions of what are now nLine's core technologies, and has since focused on ensuring nLine's technology and technical culture will lead to on-the-ground improvements for everyday users of the critical infrastructure we monitor.
He is a PhD student in Electrical Engineering at the University of California, Berkeley who has been instrumental in the publishing of 6 conference papers, and is the recipient of an NSF GRFP fellowship and a departmental teaching award.
CSO & Founder
Prabal is an associate professor in the Electrical Engineering Department at the University of California, Berkeley. His research interests include design, deployment, and scaling of wireless, embedded, networked, and sensory systems for applications in health, energy, and the environment. He received a PhD in computer science from UC Berkeley, and he is the recipient of an Alfred P. Sloan Research Fellowship, an NSF CAREER Award, a Popular Science Brilliant Ten Award, and an Intel Early Career Award.
Prabal has been helping to guide this project since its inception as a research idea over 8 years ago, and continues to ensure the integrity of nLine's conclusions as it's Chief Science Officer.
Emily is passionate about increasing data accessibility and conducting analyses that allow for more informed decision making. She joined the nLine team just over a year ago, and works to develop power outage detection algorithms and methods of outage evaluation. She is completing her undergraduate degree in Industrial Engineering and Operations Research at the University of California, Berkeley.
Joyce is data scientist with a background in electrical engineering, embedded systems and IoT. She is passionate about improving the energy reliability challenges faced in most sub-Saharan African countries. Joyce dreams about a developed Africa and she believes accessible and reliable energy systems will contribute to making this a reality.
She is currently pursuing a Master of Science in Electrical and Computer Engineering at Carnegie Mellon University Africa. Her focus is on machine learning and energy systems. With this, she aims at using different machine learning algorithms to improve on the accuracy of predictive analysis in energy systems and as a result improving energy reliability. Her research interests are smart energy systems, energy reliability and machine learning.
Margaret is passionate about using technology for positive impact especially in optimizing systems on the African continent. She has a background in Network Engineering and Data Science and is continually improving her tech knowledge to be able to solve pertinent problems that affect socio-economic lives of people. At nLine, she does research work on estimating the number of people impacted when a power outage occurs. She is currently pursuing a master's degree in Electrical and Computer Engineering at Carnegie Mellon University.
Molly is a data scientist with a background in anticipatory intelligence, specifically crowdsourced predictions. She is pursuing a Master's in Computer Science at Virginia Tech, where she researches methods of automated discovery and causal inference.