School of Engineering
Showing 101-150 of 540 Results
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Lynette Cegelski
Professor of Chemistry and, by courtesy, of Chemical Engineering
Current Research and Scholarly InterestsOur research program is inspired by the challenge and importance of elucidating chemical structure and function in complex biological systems and the need for new strategies to treat infectious diseases. The genomics and proteomics revolutions have been enormously successful in generating crucial "parts lists" for biological systems. Yet, for many fascinating systems, formidable challenges exist in building complete descriptions of how the parts function and assemble into macromolecular complexes and whole-cell factories. We have introduced uniquely enabling problem-solving approaches integrating solid-state NMR spectroscopy with microscopy and biochemical and biophysical tools to determine atomic- and molecular-level detail in complex macromolecular assemblies and whole cells and biofilms. We are uncovering new chemistry and new chemical structures produced in nature. We identify small molecules that influence bacterial assembly processes and use these in chemical genetics approaches to learn about bacterial cell wall, amyloid and biofilm assembly.
Translationally, we have launched a collaborative antibacterial drug design program integrating synthesis, chemical biology, and mechanistic biochemistry and biophysics directed at the discovery and development of new antibacterial therapeutics targeting difficult-to-treat bacteria. -
Anthony Cesnik
Postdoctoral Scholar, Bioengineering
BioI am advancing the vision of enabling an understanding of biology at the proteoform level, peering into the cellular machinery in a way that reveals precisely which molecule is acting in the biological system. Recently, I have been working in Emma Lundberg’s lab on understanding how the expression of these molecules varies between individual cells in space and time. Emma Lundberg’s group has a wealth of experience in using microscopy to yield biological images that paint a picture of this cell-to-cell heterogeneity of protein expression information, and joining her lab has deepened my expertise in integrating datasets to perform innovative analyses of single-cell protein expression. I hope to extend this towards analyzing single-cell proteoform expression, understanding the heterogeneity and flux between these proteoforms in space and time, and digging into the fundamental insights about human biology these data may reveal.
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Rahul Chajwa
Postdoctoral Scholar, Bioengineering
Current Research and Scholarly InterestsMy HFSP project is focussed on understanding the birth, life and death of marine snow. A predictive understanding of the hydrodynamic, biotic, and non-equilibrium aspects of this sinking microbial ecosystem is a notoriously challenging and globally relevant problem and is the central theme of my research at Stanford University. I’m applying my training as a physicist to shed light on the dynamical aspects of microbial life in the ocean, and to contribute insights that can help mitigate the negative impact of human activities on global climate; something I feel strongly about.
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Edward Y. Chang
Acting Professor, Computer Science
BioEdward Chang, a pioneer working on data-centric parallel machine learning since 2005. He is an adjunct professor at Stanford CS department. He also serves as the CTO of AILLY.ai. Prior to his current posts, Ed was the president of HTC Healthcare BU (DeepQ) from 2012 to 2021. Between 2006 and 2012 he served as a director of research at Google, leading research and development in areas including scalable machine learning, indoor localization, Google Q&A, and recommendation systems. Between 1999 and 2006, Ed was a full professor of Electrical & Computer Engineering at the University of California, Santa Barbara. He joined UCSB in 1999 after receiving his MS in CS and PhD in EE degrees, both from Stanford University. He is a recipient of the NSF Career award, Google Innovation award, US$1M Tricorder XPRIZE (AI for disease diagnosis) award, and ACM SIGMM test-of-time award. Ed is a Fellow of ACM and IEEE for his contributions to scalable machine learning and healthcare.
For further details, please visit https://en.wikipedia.org/wiki/Edward_Y._Chang -
Fu-Kuo Chang
Professor of Aeronautics and Astronautics
BioProfessor Chang's primary research interest is in the areas of multi-functional materials and intelligent structures with particular emphases on structural health monitoring, intelligent self-sensing diagnostics, and multifunctional energy storage composites for transportation vehicles as well as safety-critical assets and medical devices. His specialties include embedded sensors and stretchable sensor networks with built-in self-diagnostics, integrated diagnostics and prognostics, damage tolerance and failure analysis for composite materials, and advanced multi-physics computational methods for multi-functional structures. Most of his work involves system integration and multi-disciplinary engineering in structural mechanics, electrical engineering, signal processing, and multi-scale fabrication of materials. His recent research topics include: Multifunctional energy storage composites, Integrated health management for aircraft structures, bio-inspired intelligent sensory materials for fly-by-feel autonomous vehicles, active sensing diagnostics for composite structures, self-diagnostics for high-temperature materials, etc.
