This open access textbook introduces the emerging field of Development Engineering, its constituent theories, methods, and applications. It is both a teaching text for students and a resource for researchers and practitioners engaged in the design of technologies for low-resource communities. The scope is broad, ranging from the development of mobile applications for low-literacy users, to hardware and software solutions for providing electricity and water in remote settings. It is also highly interdisciplinary, drawing on methods and theory from the social sciences as well as engineering and the natural sciences. The opening section reviews the history of "technology-for-development" research, and presents a framework that formalizes this body of work and begins its transformation into an academic discipline. It identifies common challenges in development and explains the book's 'innovate, evaluate, scale' approach, integrating it with product development lifecycles. Each of the next six thematic sections focuses on a different sector: water, sanitation and health; governance; energy and resources; information; markets; and human capital. These thematic sections contain case studies from landmark research that directly integrates engineering innovation with technically rigorous methods from the social sciences. Each case study describes the design, evaluation, and/or scaling of a technology in the field and follows a single template, with common headings and questions, to create continuity and pedagogical consistency. Together, they highlight successful solutions to development challenges, while also analyzing the rarely discussed failures. The book concludes by reiterating the core principles of development engineering illustrated in the case studies and highlighting common challenges that engineers and scientists face in designing technology interventions to accelerate economic development. Development Engineering provides, for the first time, a coherent intellectual framework for attacking the challenges of poverty through the design of better technologies. It offers the rigorous discipline necessary to help channel the energy of a new generation of scientists and engineers studying and engaged in advancing social welfare and improving living conditions in low-resource communities.

Temina Madon is on the Professional Faculty of the University of California, Berkeley Haas School of Business and a member of South Park Commons, where she advises early-stage startups. Previously she led business development at machine learning startup Atlas AI. Earlier, Madon was the founding executive director of the Center for Effective Global Action (CEGA), a global research network focused on human and economic development, with headquarters at UC Berkeley. In this role, she managed the Development Impact Lab, a USAID-funded consortium of universities advancing the field of "development engineering". Madon worked with Ashok Gadgil to conceptualize a framework for this book and recruit contributors. Madon began her career in science and technology policy, working first in the U.S. Senate (as a AAAS Science and Technology Policy Fellow) and later at the U.S. National Institutes of Health (NIH). She holds a Ph.D. from UC Berkeley in computational neuroscience and a B.S. from MIT. Ashok Gadgil is a Faculty Senior Scientist and former Director of the Energy and Environmental Technologies Division at Lawrence Berkeley National Laboratory, and a Distinguished Professor of Civil and Environmental Engineering at University of California, Berkeley. Since 2012, Gadgil is the Faculty Director a large multi-campus, multi-disciplinary USAID-funded project, Development Impact Lab, with headquarters at UC Berkeley. Since 2006 he has taught graduate courses at UC Berkeley on inventing, implementing, and scaling up technologies for development. His research and technology inventions have been recognized with several significant awards and honors. Along with Dr. Temina Madon, Gadgil led the conceptualizing this book, shaping its content, framework, and selection of chapter authors. Gadgil holds a Ph.D. in physics from UC Berkeley and an M.Sc. in physics from the Indian Institute of Technology, Kanpur. Richard Anderson is a Professor in the Paul G. Allen School of Computer Science and Engineering at the University of Washington. His research interest is in Computing for the Developing World, with work spanning educational technology, mobile data management tools, global health information systems; and digital financial services. He has conducted research at the Mathematical Sciences Research Institute, the Indian Institute of Science, Microsoft Research, and PATH, a Seattle based NGO working on health technologies for low resource environments. He has been recognized with the NSF Presidential Young Investigator award the University of Washington College of Engineering Faculty Innovator for Teaching Award and the 2020 ACM Eugene L. Lawler Award for Humanitarian Contributions within Computer Science and Informatics. Previously, he worked in the theory and implementation of algorithms, including parallel algorithms, computational geometry, and scientific applications. He graduated with a B.A. in Mathematics from Reed College and a Ph.D. in Computer Science from Stanford University. Lorenzo Casaburi is an Associate Professor in the Department of Economics at the University of Zurich. His main line of research focuses on agricultural markets in Sub-Saharan Africa, with an emphasis on market structure, behavioral insights, and agricultural finance. His research has received funding from the European Research Council, the Swiss National Foundation, the U.S. Agency for International Development, UK Aid, and others. He is a Research Fellow at the Centre for Economic Policy Research and Bureau for Research and Economic Analysis of Development, and a Research Affiliate at the International Growth Centre, Innovations for Poverty Action, and the Abdul Latif Jameel Poverty Action Lab. Lorenzo holds a B.A. from the University of Bologna and a Ph.D. in Economics from Harvard. Before joining the University of Zurich, he was a postdoctoral fellow at Stanford University. Ken