Stanford University
Showing 13,681-13,700 of 36,315 Results
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Patrick Hynes
Senior Manager of Research Communities, Institute for Human-Centered Artificial Intelligence (HAI)
Current Role at StanfordSenior Manager of Research Communities at Stanford HAI
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Gianluca Iaccarino
Robert Bosch Chair of the Department of Mechanical Engineering and Joseph L. and Roberta M. Rodgers Professor
Current Research and Scholarly InterestsComputing and data for energy, health and engineering
Challenges in energy sciences, green technology, transportation, and in general, engineering design and prototyping are routinely tackled using numerical simulations and physical testing. Computations barely feasible two decades ago on the largest available supercomputers, have now become routine using turnkey commercial software running on a laptop. Demands on the analysis of new engineering systems are becoming more complex and multidisciplinary in nature, but exascale-ready computers are on the horizon. What will be the next frontier? Can we channel this enormous power into an increased ability to simulate and, ultimately, to predict, design and control? In my opinion two roadblocks loom ahead: the development of credible models for increasingly complex multi-disciplinary engineering applications and the design of algorithms and computational strategies to cope with real-world uncertainty.
My research objective is to pursue concerted innovations in physical modeling, numerical analysis, data fusion, probabilistic methods, optimization and scientific computing to fundamentally change our present approach to engineering simulations relevant to broad areas of fluid mechanics, transport phenomena and energy systems. The key realization is that computational engineering has largely ignored natural variability, lack of knowledge and randomness, targeting an idealized deterministic world. Embracing stochastic scientific computing and data/algorithms fusion will enable us to minimize the impact of uncertainties by designing control and optimization strategies that are robust and adaptive. This goal can only be accomplished by developing innovative computational algorithms and new, physics-based models that explicitly represent the effect of limited knowledge on the quantity of interest.
Multidisciplinary Teaching
I consider the classical boundaries between disciplines outdated and counterproductive in seeking innovative solutions to real-world problems. The design of wind turbines, biomedical devices, jet engines, electronic units, and almost every other engineering system requires the analysis of their flow, thermal, and structural characteristics to ensure optimal performance and safety. The continuing growth of computer power and the emergence of general-purpose engineering software has fostered the use of computational analysis as a complement to experimental testing in multiphysics settings. Virtual prototyping is a staple of modern engineering practice! I have designed a new undergraduate course as an introduction to Computational Engineering, covering theory and practice across multidisciplanary applications. The emphasis is on geometry modeling, mesh generation, solution strategy and post-processing for diverse applications. Using classical flow/thermal/structural problems, the course develops the essential concepts of Verification and Validation for engineering simulations, providing the basis for assessing the accuracy of the results. -
Andrei Iagaru
Professor of Radiology (Nuclear Medicine)
Current Research and Scholarly InterestsCurrent research projects include:
1) PET/MRI and PET/CT for Early Cancer Detection
2) Targeted Radionuclide Therapy
3) Clinical Translation of Novel PET Radiopharmaceuticals; -
Dan Iancu
Associate Professor of Operations, Information and Technology at the Graduate School of Business
BioDan Iancu is an Associate Professor of Operations, Information and Technology at the Stanford Graduate School of Business. His research and teaching interests are in responsible analytics and AI and data-driven optimization, with applications in supply chain management, FinTech, and healthcare. His work is aimed both at improving existing methodological tools (e.g., by making them more robust, fair, or transparent) and at applying these to design more effective, more equitable, and more sustainable solutions for complex operational problems. An area of particular focus in his recent research has been the design of better procurement, payment, and financing solutions in global supply chains, where material and financial flows carry both immediate and long-term impact on the lives of millions of people and on the environment.
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Assel Ibadulla
Ph.D. Student in Health Policy, admitted Autumn 2025
BioAssel Ibadulla is a PhD student in Health Policy, specializing in Decision Sciences, and a Knight-Hennessy Scholar. She graduated with honors in Biological Sciences from Nazarbayev University and earned a Master of Public Health in Health Policy from Yale University as a Horstmann Scholar. Assel aims to leverage decision sciences to support policymakers in making cost-effective and equitable health decisions, with a focus on strengthening health systems in low- and middle-income countries.
Previously, Assel worked at Yale’s Equity Research and Innovation Center, where she focused on healthcare equity for ethnic minorities, and at the Harvard Health Systems Innovation Lab, where she contributed to research on transitioning to high-value health systems, and additionally, assisted with WHO global health projects.
She also placed in the top 10 at the Asian Universities Alliance Social Entrepreneurship Competition at Tsinghua University for her mental health app, Mind Matters. -
Andrea J Ibarra
Instructor, Anesthesiology, Perioperative and Pain Medicine
BioDr. Ibarra is a board-certified anesthesiologist with a focused research interest in preeclampsia and brain health. She completed her anesthesiology training at the University of Pittsburgh in 2019. Committed to bridging clinical excellence with rigorous scientific inquiry, Dr. Ibarra earned a master's degree in clinical research at Pitt. In 2023, her research promise was recognized with the prestigious SOAP-FAER Mentored Research Training Grant, which investigated the long-term neurological implications of preeclampsia. Her research portfolio centers on the intersection of anesthesia, women's health outcomes, and cognitive function, contributing to the growing body of evidence in perioperative neuroscience.
Outside of her clinical and academic pursuits, Dr. Ibarra is passionate about cooking and travel, drawing inspiration from diverse cultures around the world.
