School of Engineering
Showing 1-20 of 52 Results
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Ade Mabogunje
Sr Research Engineer
BioAde Mabogunje conducts research on the design thinking process with a view to instrumenting and measuring the process and giving feedback to design thinking teams on ways to improve their performance. He works in collaboration with partners in the engineering education, design practice and investment community as a participant-observer in the practice of building and developing ecosystems that support accelerated and continuous innovation in products and services. Prior to this he was the associate director of the Stanford Center for Design Research (CDR). He was also the lead of the Real-time Venture Design Lab program (ReVeL) in the school of Humanities and Sciences. His industry experience includes engineering positions at the French Oil Company Elf (now Total) and research collaboration with Artificial Intelligence Scientists at NASA Ames. He has publications in the areas of design theory and methodology, knowledge management, emotions in engineering, design protocol analysis, and engineering-design education.
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Jennifer Maier
Postdoctoral Scholar, Mechanical Engineering
BioMy research interests include a broad variety of topics, ranging from medical image analysis and signal processing, machine learning and artificial intelligence, which I mainly focused on during my Ph.D. research. As a member of the Digital Athlete project of the Wu Tsai Performance Allience, I am now pursuing research to investigate how we can use wearable sensors, machine learning and biomechanical simulations to improve athlete performance, prevent injuries and support rehabilitation after injury.
I completed my Bachelor of Science and Master of Science degrees in medical engineering from Friedrich-Alexander-University Erlangen-Nuernberg (FAU). In 2015, I worked on my master’s thesis under the supervision of Prof. Kamiar Aminian during a research stay in the Laboratory of Movement Analysis and Measurement (LMAM), École Polytechnique Fédérale de Lausanne (EPFL), supported by a DAAD Scholarship. Afterwards, I pursued my Ph.D. at FAU in the Pattern Recognition Laboratory under the supervision of Prof. Andreas Maier and in the Machine Learning and Data Analytics Lab under the supervision of Prof. Bjoern Eskofier. I worked on projects in collaboration with Stanford University and the Universidade do Vale do Rio dos Sinos (UNISINOS) and conducted several short-term research stays at the partner universities. After finishing my Ph.D. in 2021, I joined Stanford University as a postdoctoral scholar advised by Prof. Ellen Kuhl. -
Dr. Arun Majumdar
Dean, Stanford Doerr School of Sustainability, Jay Precourt Professor, Professor of Mechanical Engineering, of Energy Science & Engineering, of Photon Science, by courtesy, of Materials Sci & Eng and Senior Fellow, by courtesy, at Hoover
BioDr. Arun Majumdar is the inaugural Dean of the Stanford Doerr School of Sustainability. He is the Jay Precourt Provostial Chair Professor at Stanford University, a faculty member of the Departments of Mechanical Engineering and Energy Science and Engineering, a Senior Fellow and former Director of the Precourt Institute for Energy and Senior Fellow (courtesy) of the Hoover Institution. He is also a faculty in Department of Photon Science at SLAC.
In October 2009, Dr. Majumdar was nominated by President Obama and confirmed by the Senate to become the Founding Director of the Advanced Research Projects Agency - Energy (ARPA-E), where he served until June 2012 and helped ARPA-E become a model of excellence and innovation for the government with bipartisan support from Congress and other stakeholders. Between March 2011 and June 2012, he also served as the Acting Under Secretary of Energy, enabling the portfolio of Office of Energy Efficiency and Renewable Energy, Office of Electricity Delivery and Reliability, Office of Nuclear Energy and the Office of Fossil Energy, as well as multiple cross-cutting efforts such as Sunshot, Grid Modernization Team and others that he had initiated. Furthermore, he was a Senior Advisor to the Secretary of Energy, Dr. Steven Chu, on a variety of matters related to management, personnel, budget, and policy. In 2010, he served on Secretary Chu's Science Team to help stop the leak of the Deep Water Horizon (BP) oil spill.
Dr. Majumdar serves as the Chair of the Advisory Board of the US Secretary of Energy, Jennifer Granholm. He led the Agency Review Team for the Department of Energy, Federal Energy Regulatory Commission and the Nuclear Regulatory Commission during the Biden-Harris Presidential transition. He served as the Vice Chairman of the Advisory Board of US Secretary of Energy, Dr. Ernest Moniz, and was also a Science Envoy for the US Department of State with focus on energy and technology innovation in the Baltics and Poland. He also serves on numerous advisory boards and boards of businesses, investment groups and non-profit organizations.
After leaving Washington, DC and before joining Stanford, Dr. Majumdar was the Vice President for Energy at Google, where he assembled a team to create technologies and businesses at the intersection of data, computing and electricity grid.
Dr. Majumdar is a member of the US National Academy of Sciences, US National Academy of Engineering and the American Academy of Arts and Sciences. His research in the past has involved the science and engineering of nanoscale materials and devices, especially in the areas of energy conversion, transport and storage as well as biomolecular analysis. His current research focuses on redox reactions and systems that are fundamental to a sustainable energy future, multidimensional nanoscale imaging and microscopy, and an effort to leverage modern AI techniques to develop and deliver energy and climate solutions.
Prior to joining the Department of Energy, Dr. Majumdar was the Almy & Agnes Maynard Chair Professor of Mechanical Engineering and Materials Science & Engineering at University of California–Berkeley and the Associate Laboratory Director for energy and environment at Lawrence Berkeley National Laboratory. He also spent the early part of his academic career at Arizona State University and University of California, Santa Barbara.
Dr. Majumdar received his bachelor's degree in Mechanical Engineering at the Indian Institute of Technology, Bombay in 1985 and his Ph.D. from the University of California, Berkeley in 1989. -
Ali Mani
Associate Professor of Mechanical Engineering
BioAli Mani is an associate professor of Mechanical Engineering at Stanford University. He is a faculty affiliate of the Institute for Computational and Mathematical Engineering at Stanford. He received his PhD in Mechanical Engineering from Stanford in 2009. Prior to joining the faculty in 2011, he was an engineering research associate at Stanford and a senior postdoctoral associate at Massachusetts Institute of Technology in the Department of Chemical Engineering. His research group builds and utilizes large-scale high-fidelity numerical simulations, as well as methods of applied mathematics, to develop quantitative understanding of transport processes that involve strong coupling with fluid flow and commonly involve turbulence or chaos. His teaching includes the undergraduate engineering math classes and graduate courses on fluid mechanics and numerical analysis.
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Alison Marsden
Douglass M. and Nola Leishman Professor of Cardiovascular Diseases, Professor of Pediatrics (Cardiology) and of Bioengineering and, by courtesy, of Mechanical Engineering
Current Research and Scholarly InterestsThe Cardiovascular Biomechanics Computation Lab at Stanford develops novel computational methods for the study of cardiovascular disease progression, surgical methods, and medical devices. We have a particular interest in pediatric cardiology, and use virtual surgery to design novel surgical concepts for children born with heart defects.
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Russell Martin
Ph.D. Student in Mechanical Engineering, admitted Autumn 2020
BioPhD student with the Stanford Biomechatronics Lab (biomechatronics.stanford.edu).
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Michaëlle Ntala Mayalu
Assistant Professor of Mechanical Engineering and, by courtesy, of Bioengineering
BioDr. Michaëlle N. Mayalu is an Assistant Professor of Mechanical Engineering. She received her Ph.D., M.S., and B.S., degrees in Mechanical Engineering at the Massachusetts Institute of Technology. She was a postdoctoral scholar at the California Institute of Technology in the Computing and Mathematical Sciences Department. She was a 2017 California Alliance Postdoctoral Fellowship Program recipient and a 2019 Burroughs Wellcome Fund Postdoctoral Enrichment Program award recipient. She is also a 2023 Hypothesis Fund Grantee.
Dr. Michaëlle N. Mayalu's area of expertise is in mathematical modeling and control theory of synthetic biological and biomedical systems. She is interested in the development of control theoretic tools for understanding, controlling, and predicting biological function at the molecular, cellular, and organismal levels to optimize therapeutic intervention.
She is the director of the Mayalu Lab whose research objective is to investigate how to optimize biomedical therapeutic designs using theoretical and computational approaches coupled with experiments. Initial project concepts include: i) theoretical and experimental design of bacterial "microrobots" for preemptive and targeted therapeutic intervention, ii) system-level multi-scale modeling of gut associated skin disorders for virtual evaluation and optimization of therapy, iii) theoretical and experimental design of "microrobotic" swarms of engineered bacteria with sophisticated centralized and decentralized control schemes to explore possible mechanisms of pattern formation. The experimental projects in the Mayalu Lab utilize established techniques borrowed from the field of synthetic biology to develop synthetic genetic circuits in E. coli to make bacterial "microrobots". Ultimately the Mayalu Lab aims to develop accurate and efficient modeling frameworks that incorporate computation, dynamical systems, and control theory that will become more widespread and impactful in the design of electro-mechanical and biological therapeutic machines.
