School of Engineering
Showing 1-50 of 447 Results
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Naël M'nasri
Masters Student in Management Science and Engineering, admitted Spring 2022
BioWorking at Google and currently taking part-time MS&E courses.
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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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Erin MacDonald
Assistant Professor of Mechanical Engineering
Current Research and Scholarly InterestsResearch Focus
Research projects in Dr. MacDonald's IRIS Design lab have three foci: (1) Modeling the role of the public's decisions in effective large-scale sustainability implementation; (2) Improving engineering designers' abilities to address complex customer preference for sustainability; and (3) Using data on how consumers perceive products, especially visually, to understand how products are evaluated and subsequently improve those evaluations. These foci represent three corresponding design vantage points: (1) system-level; (2) human-scale or product-level, and (3) single-decision-level, as shown in the Figure. The exploration of these different vantage points is fundamental to performing insightful design research on complex design issues, such as sustainability.
Sustainable design readily spreads across many disciplines and necessarily requires an interdisciplinary and system-based design approach. At the heart of this system is the relationship between product engineering and human behavior. The designer must include this relationship in the product's design along with other sustainability concerns such as technology advancement, life cycle assessment, policy compliance, larger societal impact, and economic viability. As behavior is difficult for engineers to quantify, it can be lost in engineering analysis. The resulting sustainable products and technologies may not be used and/or purchased, may not be as efficient as predicted, and thus may not have the beneficial impact that they were designed to have. The relationship between the sustainable product engineering and human behavior can be quantified, for example by modeling decision-making, and incorporated into engineering analysis. Often, the reformulation of the engineering system problem required to accommodate human behavior is beneficial to other elements of the design. We perform research at the intersection of analytical design methods, conceptual design methods, and decision-making theory to design successful sustainable products and energy technologies. -
Kazuki Maeda
Physical Sci Res Scientist
BioMaeda's research combines high-performance computing, modeling, data analysis, control, and companion experiments to address complex flow phenomena. He actively works on biomedical, energy, and propulsion applications, and on interdisciplinary research.
His current major research and teaching activities are conducted in the Center for Turbulence Research (https://ctr.stanford.edu) and the Predictive Science Academic Alliance Program Center (https://insieme.stanford.edu).
Maeda obtained his BS from the University of Tokyo in 2013, and MS and PhD from Caltech in 2014 and 2018, all in Mechanical Engineering. He was a postdoctoral fellow in the Center for Turbulence Research from 2019 to 2020. -
Akshay Maheshwari
MD Student, expected graduation Spring 2023
Ph.D. Student in Bioengineering, admitted Summer 2016
MSTP StudentCurrent Research and Scholarly InterestsArtificial intelligence, machine learning, synthetic biology, and genomics
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Danielle Mai
Assistant Professor of Chemical Engineering
BioDanielle J. Mai joined the Department of Chemical Engineering at Stanford in January 2020. She earned her B.S.E. in Chemical Engineering from the University of Michigan and her M.S. and Ph.D. in Chemical Engineering from the University of Illinois at Urbana-Champaign under the guidance of Prof. Charles M. Schroeder. Danielle was an Arnold O. Beckman Postdoctoral Fellow in Prof. Bradley D. Olsen's group at MIT, where she engineered materials with selective biomolecular transport properties, elucidated mechanisms of toughness and extensibility in entangled associative hydrogels, and developed high-throughput methods for the discovery of polypeptide materials. The Mai Research Group integrates precise biopolymer engineering with multiscale experimental characterization to advance biomaterials development and to enhance fundamental understanding of soft matter physics.
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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.
