ECE Professor Art Gossard among 10 UCSB researchers named to Thomson Reuters’ 2015 list of Highly Cited Researchers

thomson reuters logo
The annual list recognizes researchers in the sciences and social sciences from around the world whose work has had major impact in their fields. The list includes scientists whose papers rank in the top 1 percent by citations for field and publication year in the Web of Science.

UCSB’s highly cited researchers for 2015 are:

• Guillermo C. Bazan, Materials
• Steven D. Gaines, Environment/Ecology
• Arthur C. Gossard, Physics
• Craig J. Hawker, Chemistry
• Alan J. Heeger, Chemistry, and also Materials
• Kevin D. Lafferty, Environment/Ecology
• Samir Mitragotri, Pharmacology & Toxicology
• Daniel Moses, Materials
• Thuc-Quyen Nguyen, Materials
• Joshua P. Schimel, Agricultural Sciences

According to Thomson Reuters, the 2015 list is generated through the compilation of data from 2003 to 2013, which included 120,793 highly cited papers.

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Celebrating a Year of Light with Nobel laureates Kroemer, Nakamura, Heeger and Chu

international year of light logo
Symposium at UCSB will feature talks by four Nobel laureates — UCSB’s Kroemer, Heeger and Nakamura and former Secretary of Energy Steven Chu

The United Nations declared 2015 the International Year of Light to recognize the importance of light and light-based technologies in revolutionizing everyday life around the world and providing new and innovative solutions to global issues.

To celebrate the International Year of Light, UC Santa Barbara’s College of Engineering and Institute for Energy Efficiency (IEE) are hosting a symposium Thursday, Oct. 8, from 1 to 7:30 p.m., in the campus’s Corwin Pavilion. The event is free and open to the public.

The daylong conference will feature presentations and discussions by experts in the field. Three UCSB faculty members — Herbert Kroemer (Physics 2000), Alan Heeger (Chemistry 2000) and Shuji Nakamura (Physics 2014) — received Nobel prizes for their light-based research and each will be discussing his work.

Steven Chu (Physics 1997), former U.S. Secretary of Energy and a recipient of the Nobel Prize for his own work with light-based research, will give the symposium’s keynote lecture. ECE Professor and Institute for Energy Efficiency Director, John Bowers, a leading authority on photonics and optoelectronics, will also deliver a lecture on the future of the emerging industry.

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UCSB Alumni Association honors NASA Astronaut and ECE alumnus José Hernández

photo of jose hernandez
Hernández to be honored as UC Santa Barbara’s 2015 Distinguished Alumnus on Saturday, Oct. 24, at an awards lunch in the campus’s Corwin Pavilion

The ceremony also will celebrate UCSB’s status as a Hispanic-Serving Institution (HSI). An HSI is defined as a college or university in which Hispanic enrollment comprises a minimum of 25 percent of the total enrollment of undergraduate and graduate students, both full- and part-time. UCSB was named a Hispanic-Serving Institution by the Hispanic Association of Colleges and Universities and is the only HSI that is also a member of the prestigious Association of American Universities.

“We are very excited to have José Hernández return to campus to help us kick off this campaign to raise money for Dreamers’ scholarships,” said George Thurlow, UCSB’s assistant vice chancellor for alumni affairs and executive director of the campus’s alumni association. “José’s story is an inspirational one for all alumni and for all Californians. His work today with Latino youth is even more inspirational.”

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Cinematic Virtual Reality: Creating Immersive Visual Experiences

Historically, virtual reality (VR) with head-mounted displays is associated with gaming applications and computer-generated content. However, the ability to show wide field of view content to a user can be used to provide immersive visual experiences involving real-world scenes as well. We refer to such applications as Cinematic VR. In this talk, we will present our recent research contributions in postproduction, compression, and display of omnidirectional stereoscopic videos for Cinematic VR. We will also show a method to evaluate the impact of various image processing stages on the end-to-end quality of the VR system. We are currently at the confluence of various tech trends in capture devices (e.g., Google Jump, Jaunt NEO, Nokia OZO) and displays (e.g., Oculus Rift, Gear VR) where such immersive experiences may become realizable in the near future.

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Ph.D. Defense: Design of III-N Hot Electron Transistors

The III-Nitride material system has shown excellent properties for various applications like LED and LASER lighting, high frequency and high power amplifiers, and power switching. As the technology and theoretical understanding of the III-N system matures, the limitations on further development are based on very basic electronic properties of the material, one of which is electron scattering. A good understanding of electron scattering (and ballistic electron effects) in the III-N system can potentially offer solutions to many problems encountered in these fields. In the field of high frequency transistors, III-N based high electron mobility transistors (HEMTs) have shown excellent performance, however, due to low saturation velocities and parasitic delays, the pathway to THz amplification is unclear. Vertical heterojunction bipolar transistors (HBTs) in the III-N system, unlike their counterparts in the III-As/III-P system, have not had much success in the high-frequency domain due to the high activation energy of the primary p-type dopant, Mg. Ballistic electron effects in transistors can be used to overcome drift/diffusion limits and reduce device delays for very high-frequency operation. Towards this goal, we explore III-N
based vertical unipolar hot-electron transistors (HETs).

The HET consists of three primary regions, a high-energy electron injector (emitter), a thin transit region (base), and a high-energy filter (collector). The injected high-energy electrons (hot-electrons) travel across the base in a quasi-ballistic manner. The collector allows only hot-electrons to pass through and quantum mechanically reflects scattered electrons. The HET designs explored here use AlGaN and InGaN based polarization-dipoles to form potential barriers in the conduction band. Using such a structure, transistor operation was demonstrated in III-N HETs for the first time. The current gain (β) in these first devices was, however, very low (β ~ 0.1 using a 25nm base). Upon further investigation, it was experimentally determined that the ballistic mean free path of hot-electrons is 6nm in the HET base. The III-N HET base was then scaled to 4nm and a β of 3.5 was achieved, which is the highest reported for III-N HETs. This order of magnitude improvement in β was enabled by the use of novel design, growth and process techniques which will be discussed in this talk. We believe that this work provides a clear pathway towards realizing the high-frequency potential of III-N HETs.

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Fundamentals of RF Sensing

Ubiquitous RF signals can potentially enable several applications like imaging, counting, tracking, gesture recognition e.t.c. RF signals interact with materials on their path and hence contain information about them. We use the information contained in the RF signals to image objects including occluded ones and count people. In this talk, completed work on imaging of several structures through walls using robots and counting number of people in a given area by just using WiFi RSSI measurements along with several experimental results will be presented and future directions in these areas will be discussed.

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Utilizing Machine Learning for Filtering General Monte Carlo Noise

Producing photorealistic images from a scene model requires computing a complex multidimensional integral of the scene function at every pixel of the image. Monte Carlo (MC) rendering systems approximate this integral by tracing light rays (samples) in the multidimensional space to evaluate the scene function. Although an approximation to this integral can be quickly evaluated with just a few samples, the inaccuracy of this estimate relative to the true value appears as unacceptable noise in the resulting image.

One way to mitigate this problem is to quickly render a noisy image with a few samples and then filter it as a post-process to generate an acceptable, noise-free result. This approach has been the subject of extensive research in recent years and many algorithms have been developed. However, the majority of these approaches use simple, heuristic rules to design the algorithm and, as a result, cannot handle complex scenes.

We begin by studying how standard image denoising techniques can be applied to the problem of Monte Carlo rendering. To do this, we propose a way to use any standard image denoising method (e.g., BM3D) to remove noise from MC rendered images. We do this by estimating the amount of noise at each pixel of the image, coupled with a multilevel algorithm that denoises the image in a spatially-varying manner. We then show that although this approach works better than the previous color-based schemes, i.e., the methods that only use color information, it cannot handle complex scenes with severe noise. This is due to the fact that this algorithm does not utilize additional scene features such as world positions, shading normals, and texture values, which are available in MC rendering.

To address the filtering problem systematically, we then present a new way of analyzing the MC filtering approaches. We observe that the major challenge in all filtering techniques is filter parameter estimation. Our key contribution is to address this challenging problem using machine learning. Specifically, we first propose to estimate the optimal filter parameters at each pixel directly from the output of the MC renderer using a neural network. We train the network on a set of scenes by minimizing the error between the filtered and ground truth images. Second, we propose to find the optimal filter parameter sets in an error-minimization filtering approach to produce filtered results as close as possible to the ground truth. We optimize these candidate filter parameter sets on a set of training scenes by minimizing the error between the filtered and ground truth images.

We show that the proposed approaches outperform state-of-the-art methods in removing general MC noise. In this thesis, we present the first attempt to use machine learning for removing noise from MC rendered images. We believe this opens a new avenue for future work and we hope other researchers can build upon the ideas presented here to further advance the MC filtering field.

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Spatio-Temporal Reconstruction Techniques for Optical Microscopy

Optical microscopy offers the unique possibility to study living samples under conditions akin to their native state. However, the technique is not void of inherent problems such as optical blur due to light diffraction, contamination with out-of-focus light from adjacent focal planes, and spherical aberrations. Furthermore, with a dearth of techniques that are capable of imaging multiple focal sections in quick succession, the multi-dimensional capture of dynamically changing samples remains a challenge of its own. Computational techniques that use auxiliary knowledge about the imaging system and the sample to mitigate these problems are hence of great interest in optical microscopy. The first part of this thesis deals with the design of a discrete model to characterize light propagation. Following the scalar diffraction theory in optics, we propose a multi-rate discrete algorithm, based on generalized sampling theory, to reverse the coherent diffraction process via back propagation. The second part of this thesis describes a spatial registration tool designed for multi-view microscopy, where the imaged sample is rotated about a lateral axis for the acquisition of multiple 3D datasets from different views in order to subsequently alleviate the severe axial blur found in each such dataset. Automatic algorithms that only rely on maximizing pixel-based similarity provide poor results in such applications owing to the anisotropic point-spread-function (PSF) of optical microscopes. We propose a pyramid-based spatial registration algorithm that re-blurs the multi-view datasets with geometrically transformed forms of the PSF in order to make them comparable, before maximizing their pixel based similarity for registration. The third part of this thesis describes a fast converging iterative multi-view deconvolution technique that can be applied to the spatially registered 3D datasets acquired using multi-view microscopy. The fourth part of this thesis addresses problems due to spherical aberrations encountered during the imaging of thick samples in optical microscopy. We propose a fast iterative shrinkage-thresholding depth-variant 3D deconvolution method that uses depth-dependent PSFs. The final part of this thesis describes a non-rigid temporal registration tool that aids in the multi-dimensional imaging of quasi-periodic processes such as cardiac cycles. We propose a variant of dynamic time warping that is capable of both temporally warping and wrapping an input sequence by allowing for jump discontinuities in the non-linear temporal alignment function akin to those found in wrapped phase functions.

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U.S. News & World Report ranks UCSB number 8 among the country’s top public universities

UCSB Campus aerial shot
In its 2016 listing of the “Top 30 Public National Universities” in the country, U.S. News & World Report has ranked UC Santa Barbara number 8. This marks the university’s highest ranking ever in the magazine’s annual listing.

UCSB — which this year experienced the most competitive admissions process in campus history — jumped two spots among the “Top 30 Public National Universities.” Among the “Best National Universities” ranking, which includes both public and private institutions, UCSB moved up three places to number 37.

Within the University of California system, only UC Berkeley and UCLA ranked above UCSB. Other UC campuses in the Top 30 include UC Irvine, UC San Diego and UC Davis.

In addition, UCSB placed number 6 among public universities in the magazine’s list of colleges and universities that offer students the best education value. UCSB’s College of Engineering is ranked number 18 among public universities on the U.S. News & World Report list of “Best Programs at Engineering Schools Whose Highest Degree is a Doctorate.”

The magazine has just released its annual college rankings online at The 2016 “America’s Best Colleges” guidebook goes on sale Tuesday, September 23.

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Professor Kaustav Banerjee invited to NAE’s Global Grand Challenges Summit

nae logo Banerjee is among a select group of engineers invited by the National Academy of Engineering to attend its 2015 Global Grand Challenges Summit (GGCS) in Beijing, China, Sept 15-16.

The Summit is being jointly organized by the Chinese Academy of Engineering (CAE), the U.S. National Academy of Engineering (NAE), and the Royal Academy of Engineering (RAE). The aim of the event is to prompt international cooperation to creatively address some of the most pressing issues of our time: the Grand Challenges for Engineering—including carbon sequestration, cybersecurity, health care, innovations in infrastructure, and education of the engineers who will take on such challenges.

The 2015 Beijing summit is an invitation-only event that includes a diverse mix of thought leaders, leading engineers and students. This event is the second in a series inspired by the NAE Grand Challenges for Engineering. The first summit was held in London in 2013.

Professor Banerjee who directs the Nanoelectronics Research Lab, is internationally recognized as a visionary and a leading innovator in the field of nanoelectronics.

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