School of Engineering
Showing 101-150 of 433 Results
-
David Kelley
Donald W. Whittier Professor of Mechanical Engineering
BioDavid Kelley's work is dedicated to helping people gain confidence in their creative abilities. He employs a project based methodology called Design Thinking within both the Product Design Program and the Hasso Plattner Institute of Design.
Design Thinking is based on building empathy for user needs, developing solutions with iterative prototyping, and inspiring ideas for the future through storytelling.
The Product Design program emphasizes the blending of engineering innovation, human values, and manufacturing concerns into a single curriculum. Kelley teaches engineering design methodology, the techniques of quick prototyping to prove feasibility, and design through understanding of user needs. -
Monroe Kennedy III
Assistant Professor of Mechanical Engineering
Current Research and Scholarly InterestsMy research focus is to develop technology that improves everyday life by anticipating and acting on the needs of human counterparts. My research can be divided into the following sub-categories: robotic assistants, connected devices and intelligent wearables. My Assistive Robotics and Manipulation lab focuses heavily on both the analytical and experimental components of assistive technology design.
-
Thomas Kenny
Senior Associate Dean for Education and Student Affairs and Richard W. Weiland Professor in the School of Engineering
BioKenny's group is researching fundamental issues and applications of micromechanical structures. These devices are usually fabricated from silicon wafers using integrated circuit fabrication tools. Using these techniques, the group builds sensitive accelerometers, infrared detectors, and force-sensing cantilevers. This research has many applications, including integrated packaging, inertial navigation, fundamental force measurements, experiments on bio-molecules, device cooling, bio-analytical instruments, and small robots. Because this research field is multidisciplinary in nature, work in this group is characterized by strong collaborations with other departments, as well as with local industry.
-
Ali Keshavarzi
Adjunct Professor, Electrical Engineering
BioAli Keshavarzi, Ph.D. is an Adjunct Professor in Electrical Engineering at Stanford University. Ali is involved in scholarly research and is an advisor to Stanford SystemX IoE Research (IoE = Internet of Everything). Currently Ali is a DARPA program manager in Microsystems Technology Office (MTO) defining impactful research frontiers in microelectronics. Ali is working on Software Defined Hardware (SDH) Program and on Foundation Required for Novel Compute (FRANC) Program while defining new concepts to push research forward on the technology, computing architecture, and data-centric application domains. Before his current role at DARPA, Ali was working with DARPA as an advisor and subject matter expert on the Electronic Resurgence Initiative (ERI). Ali is a member of DARPA MTO Investor Working Board (IWB) and the Embedded Entrepreneurship Initiative (EEI). Ali is a principal and the founder of Leading Edge Research LLC, Los Altos, CA.
Ali is a technology visionary and a leader who has been at the forefront of technology innovation with a track record of delivering critical process technologies, devices, circuits, SoCs, and modules to the semiconductor industry. Ali was the Vice President of R&D and a Fellow at Cypress Semiconductor and held various positions at Intel, TSMC, and GLOBALFOUNDRIES in a variety of technical and leadership roles over 25 years. Ali was a visiting research professor at UC Berkeley from 2017 to 2018.
Ali is an IEEE Fellow. He has over 60 U.S. patents, over 70 peer reviewed papers, has received best-paper awards and the best-panel award at ISSCC, most paper citation awards from DAC and IEDM. He has served in TPC of IEDM and ISSCC and has been the general chair of ISLPED. He received the prestigious Intel Achievement Award (IAA). Ali was awarded a distinguished Outstanding Electrical and Computer Engineer (OECE) of Purdue University.
https://engineering.purdue.edu/ECE/InfoFor/Alums/OECE/2015/keshavarzi.html -
Asir Intisar Khan
Visiting Postdoctoral Scholar, Electrical Engineering
Casual - Non-Exempt, Hoover Institution
Staff, Program-Pop, E.BioAsir Intisar Khan is a Postdoctoral Scholar in the Electrical Engineering and Computer Science department at the University of California, Berkeley, working with Prof. Sayeef Salahuddin. He is also a visiting postdoctoral scholar at Electrical Engineering, Stanford with Prof. Eric Pop. Asir received his Ph.D. and M.S. from the Electrical Engineering department at Stanford University, supervised by Prof. Eric Pop, and collaborated very closely with Profs. H.-S. Philip Wong, Kenneth Goodson, and Krishna Saraswat.
His research effort and vision encompass exploring novel materials and their functionalities to enable energy-efficient memory, computing devices, and interconnects for 3D heterogeneous integration. His research has enabled the lowest-to-date switching current density in phase-change memory technology and has been featured in Forbes Magazine and IEEE Spectrum. He received the Best Student Paper award at the 2022 IEEE VLSI Technology Symposium and several Best Student Presentation Awards: 2022 MRS Fall Meeting, 2023 AVS Symposium Electronic Materials and Photonics Division, and 2023 SRC TECHCON. He has held Research Intern positions at TSMC and IBM TJ Watson Research Center. Asir is a recipient of the 2023 AVS Russell & Sigurd Varian Award, the 2022 IEEE EDS Ph.D. Student Fellowship and 2022 Materials Research Society (MRS) Gold Graduate Student Award, and Stanford Graduate Fellowship.
https://sites.google.com/view/asirintisarkhan16 -
Irtiza Khan
Graduate, Stanford Center for Professional Development
BioIrtiza Khan is a software engineer and computer scientist. After completing his undergraduate studies in computer science at California State University, East Bay, he pursued graduate coursework at Stanford's School of Engineering to further explore the intersection between computer systems, big data, and machine learning.
