All EECS News

EECS Graduate Student Named 2012 Keithley Graduate Fellow for Advancing Research in Nanoscale Devices and Electronic Measurements

Tina He AwardKeithley Instruments, Inc., a world leader in advanced electrical test instruments and systems, has named Tina He as the recipient of the first annual Keithley Graduate Fellowship Award.  Ms. He, a Case Western Reserve University (Case) Ph.D. student, was chosen for this award for her graduate research work with Professor Philip Feng in the Department of Electrical Engineering and Computer Science at Case, on developing novel nanoscale devices and circuits with potential applications to advanced test and measurement.

The research and experiments Ms. He and Dr. Feng are pursuing involves developing very high speed nanoelectromechanical systems (NEMS) devices and arrays, NEMS logic building blocks, and circuits. Their experimental research includes nanodevice fabrication and low-noise electronic measurement, and will be reinforced by novel designs and modeling. 

Informatics symposium to focus on application, impact of IT on health research

The Clinical and Translational Science Collaborative (CTSC) and the Institute for Health Informatics and Comparative Effectiveness Research will cohost “Informatics: Driving Discovery, Improving Health (IDD 2012)” April 6.

The aim of this symposium is to enlighten and update the clinical research community and other interested regional informaticians about the current research and health informatics tools being used for clinical and translational research data management.

Gmail creator, CWRU Computer Engineering alum Paul Buchheit to deliver his own message at commencement

Paul BucheitGmail creator and Case Western Reserve University alumnus Paul Buchheit (CWR ’98; GRS ’98, computer engineering) will speak to 1,750 students who grew up using the technology he created when he delivers the 2012 commencement address May 20 in Veale Convocation Center.

Buchheit, a partner at the venture capital firm Y Combinator, was one of the first engineers at Google, where he suggested the company’s famous “Don’t be evil” motto and created the first AdSense prototype.

After graduating from Case Western Reserve, Buchheit spent a year at Intel Corp. before becoming Google’s 23rd employee in 1999. His free email service Gmail launched in 2004 and now boasts more than 350 million registered users.

He retired from Google in 2006 and founded FriendFeed the following year. The service allows users to share information such as links, photos and messages online and was acquired by Facebook in 2009.

Buchheit joined Y Combinator in 2010. Founded in 2005, the firm provides funding, advice and networking opportunities to promising startups.



Mike Lewicki receives $1.8M 4-year NSF grant for studying motion in natural scenes

Mike LewickiMike Lewicki (Associate Professor of EECS) has received a $1.8M ($815K for CWRU) 4-year NSF grant (together with colleagues at UC Berkeley and UT Austin) for studying motion in natural scenes.

This project seeks to advance our understanding of a fundamental problem in both biological and machine vision: how does a visual system recover 3D scene structure -- such as the layout of the environment, surface shape, or object motion -- from dynamic, 2D images?  Computer vision has approached this problem by developing algorithms for recovering specific aspects of a scene, but obtaining general solutions that perform robustly for complex natural scenes and viewing conditions remains a challenge.  Biological vision systems have evolved impressive information processing strategies for extracting 3D structure from natural scenes, but the neural representations for doing this are poorly understood and provide little insight into the computational process.  This project will pursue an interdisciplinary approach by attempting the understand the universal principles that lie at the heart of this problem in both biological and machine vision systems.  Specifically, the project will  1) develop a novel class of computational models that recover and represent 3D scene information by factoring apart the underlying causal structure of images, 2) collect high quality video and range data of dynamic natural scenes under a variety of controlled motion conditions, and 3) test the perceptual implications of these models in psychophysical experiments.