School of Engineering


Showing 461-470 of 709 Results

  • Hae Young Noh

    Hae Young Noh

    Associate Professor of Civil and Environmental Engineering

    BioHae Young Noh is an associate professor in the Department of Civil and Environmental Engineering. Her research introduced the new concept of “structures as sensors” to enable physical structures (e.g., buildings and vehicle frames) to be user- and environment-aware. In particular, these structures indirectly sense humans and surrounding environments through their structural responses (i.e., vibrations) by inferring the desired information (e.g., human behaviors, environmental conditions, heating and cooling system performance), instead of directly measuring the sensing targets with additional dedicated sensors (e.g., cameras, motion sensors). This concept brought a paradigm shift in how we view these structures and how the structures interact with us.
    Traditionally, structures that we inhabit (such as buildings or vehicles) are considered as passive and unchanging objects that we need to monitor and control, utilizing a dense set of sensors to collect information. This has often been complicated by “noise” caused by the occupants and environments. For example, building vibrations induced by indoor and outdoor environmental and operational conditions (e.g., people walking around, traffic outside, heating system running, etc.), have been often seen as noise that needs to be removed in traditional building science and structural engineering; however, they are a rich source of information about structure, users, environment, and resources. Similarly, in vehicle engineering, researchers and engineers have been investigating control and dynamics to reduce vehicle vibration for safety and comfort. However, vibrations measured inside vehicles contain information about transportation infrastructure, vehicle itself, and driver.
    Noh's work utilizes this “noise” to empower the structures with the ability to perceive and understand the information about users and surroundings using their own responses, and actively adopt and/or interact to enhance their sustainability and the occupants’ quality of life. Since she utilizes the structure itself as a sensing medium, information collection involves a simpler set of hardware that can be easily maintained throughout the structural lifetime. However, the analysis of data to separate the desired information becomes more challenging. This challenge is addressed through high-rate dynamic sensing and multi-source inferencing. Ultimately, her work aims to allow structural systems to become general sensing platforms that are easier and more practical to deploy and maintain in a long-term.
    At Stanford University, Noh received her PhD and MS degrees in the CEE department and her second MS degree in Electrical Engineering. Noh earned her BS in Mechanical and Aerospace Engineering at Cornell University.

  • Paul Nuyujukian

    Paul Nuyujukian

    Assistant Professor of Bioengineering and of Neurosurgery and, by courtesy, of Electrical Engineering

    Current Research and Scholarly InterestsOur group explores neuroengineering and its application to both basic and clinical neuroscience. Our goal is to develop brain-machine interfaces as a platform technology for a variety of brain-related medical conditions including stroke and epilepsy.

  • Daniel J O'Shea

    Daniel J O'Shea

    Research Engineer

    Current Research and Scholarly InterestsI study the neural mechanisms that control movement, and more broadly, how neural populations spanning interconnected brain regions perform the distributed computations that drive skilled behavior. I develop experimental and computational tools to understand the neural population dynamics that establish speed and dexterity.

  • Allison Okamura

    Allison Okamura

    Richard W. Weiland Professor in the School of Engineering and Professor of Mechanical Engineering

    Current Research and Scholarly InterestsMy research focuses on developing the principles and tools needed to realize advanced robotic and human-machine systems capable of physical interaction. Application areas include surgery, simulation and training, rehabilitation, prosthetics, neuromechanics, exploration of hazardous and remote environments (e.g. space), design, and education.

  • Kunle Olukotun

    Kunle Olukotun

    Cadence Design Systems Professor, Professor of Electrical Engineering and of Computer Science
    On Partial Leave from 01/01/2025 To 03/31/2025

    BioKunle Olukotun is the Cadence Design Professor of Electrical Engineering and Computer Science at Stanford University. Olukotun is a pioneer in multicore processor design and the leader of the Stanford Hydra chip multiprocessor (CMP) research project. He founded Afara Websystems to develop high-throughput, low-power multicore processors for server systems. The Afara multi-core processor, called Niagara, was acquired by Sun Microsystems and now powers Oracle's SPARC-based servers. In 2017, Olukotun co-founded SambaNova Systems, a Machine Learning and Artificial Intelligence company, and continues to lead as their Chief Technologist.

    Olukotun is the Director of the Pervasive Parallel Lab and a member of the Data Analytics tor What's Next (DAWN) Lab, developing infrastructure for usable machine learning. He is a member of the National Academy of Engineering, an ACM Fellow, and an IEEE Fellow for contributions to multiprocessors on a chip design and the commercialization of this technology. He also received the Harry H. Goode Memorial Award.

    Olukotun received his Ph.D. in Computer Engineering from The University of Michigan.

  • Simona Onori

    Simona Onori

    Associate Professor of Energy Science Engineering, Senior Fellow at the Precourt Institute for Energy and Associate Professor, by courtesy, of Electrical Engineering

    Current Research and Scholarly InterestsModeling, control and optimization of dynamic systems;
    Model-based control in advanced propulsion systems;
    Energy management control and optimization in HEVs and PHEVs;
    Energy storage systems- Li-ion and PbA batteries, Supercapacitors;
    Battery aging modeling, state of health estimation and life prediction for control;
    Damage degradation modeling in interconnected systems

  • Colin Ophus

    Colin Ophus

    Associate Professor of Materials Science and Engineering and Center Fellow at the Precourt Institute for Energy

    BioColin Ophus is an Associate Professor in the Department of Materials Science and Engineering and a Center Fellow at the Precourt Institute for Energy, Stanford University. He previously worked as a Staff Scientist at the National Center for Electron Microscopy (NCEM), part of the Molecular Foundry, at Lawrence Berkeley Lab. He was awarded a US Department of Energy (DOE) Early Career award in 2018, and the Burton medal from the Microscopy Society of America (MSA) in 2018. His research focuses on experimental methods, reconstruction algorithms, and software codes for simulation, analysis, and instrument design of transmission electron microscopy (TEM) and scanning TEM (STEM).

    Colin advocates for open science and his group has developed open-source scientific software including as the Prismatic STEM simulation code and py4DSTEM analysis toolkit. He has taught many workshops around the world on topics ranging from scientific visualization to large scale data analysis. He also is the founder and editor-in-chief for a new journal based on interactive science communication named Elemental Microscopy.