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Highlights

Triton 5K 2015

Over 140 CSE alumni, students, staff and faculty registered to run as part of Team Race Condition. As a result, the department took home the prize for the largest turnout and donation at the 2015 Chancellor’s 5K run in early June. Read more…  

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2015 Student Awards

CSE Chair Rajesh Gupta and Profs. Christine Alvarado and Sorin Lerner with graduate and undergraduate student recipients of the inaugural awards given by the department for graduating students.. Read more…

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Dissertation Medal

CSE alumna Sarah Meiklejohn (PhD '14) was singled out for her dissertation, "Flexible Models for Secure Systems", as the recipient of the 2015 Chancellor's Dissertation Medal. Meiklejohn is now a professor at University College London. Read more…

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Research Expo 2015

At the Jacobs School of Engineering’s Research Expo 2015, more than 25 CSE graduate students showcased their research during the poster session visited by hundreds of campus, industry and community members. Read more…

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Best Poster

Graduating M.S. student Narendran Thangarajan won the award for best Computer Science and Engineering poster at Research Expo 2015. He analyzed social media to characterize HIV at-risk populations in San Diego. Read more…  

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Computer Graphics on EdX

After announcing the launch of the Center for Visual Computing, the Center's director, CSE Prof. Ravi Ramamoorthi, announced that in August 2015 he will launch an online course on computer graphics over the edX online platform. Read more…

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$2 Million Alumni Gift

CSE alumnus Taner Halicioglu, an early employee at Facebook, is donating $2 million to the CSE department to recruit, retain and support the professors and lecturers whose primary mission is to teach and mentor students. Read more…

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Big Pixel Hackathon

Seventeen CSE students, most of them graduate students, participated in the first Bix Pixel Hackathon organized by the Qualcomm Institute to demonstrate how data science can be harnessed to tackle public policy issues. Read more...

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Paul Kube Tribute

CSE honored retiring lecturer Paul Kube with a tribute and the subsequent announcement that CSE is creating the Paul R. Kube Chair of Computer Science to be awarded to a teaching professor, the first chair of its kind in the department. Read more...

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Integrated Digital Infrastructure

CSE Prof. Larry Smarr leads a two-year initiative to deploy an Integrated Digital Infrastructure for the UC San Diego campus, including grants to apply advanced IT services to support disciplines that increasingly depend on digital data. Read more...

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Query Language for Big Data

CSE Prof. Yannis Papakonstantinou and Couchbase Inc., are collaborating on a next-generation query language for big data based on the UCSD-developed SQL++, which brings together the full power of SQL with the flexibility of JSON. Read more...

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Honoring Academic Integrity

At 5th annual Academic Integrity Awards, CSE lecturer Gary Gillespie (center, with Leo Porter and Rick Ord) accepted the faculty award in Apri. Then in May, he received the Outstanding Professor Award from the Panhellenic Association. Read more...

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Non-Volatile Memories

In March 2015, CSE Prof. Steven Swanson talks to 220 attendees at the 6th annual Non-Volatile Memories Workshop which he co-organized, and which he said was "moving onto deeper, more Interesting and more challenging problems." Read more...

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Frontiers of Innovation

At least five CSE graduate students and a similar number of undergraduates were selected to receive inaugural Frontiers of Innovation Scholarship Program (FISP) awards initiated for 2015-'16 by UC San Diego. Read more...

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Not-So-Safe Scanners

A team including CSE Prof. Hovav Shacham (right) and Ph.D. student Keaton Mowery released findings of a study pointing to serious flaws in the security of backscatter X-ray scanners used at many airports. Read more...

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Stereo Vision for Underwater Archaeology

As co-director of Engineers for Exploration, Prof. Ryan Kastner led expeditions to test an underwater stereo camera system for producing 3D reconstructions of underwater objects. Here Kastner is shown with the camera system in a UCSD pool. Read more…  

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Girls Day Out

The UCSD chapter of Women in Computing (WiC) held its second annual Girls Day Out in May, bringing roughly 100 girls from San Diego high schools to tour the campus and do hands-on experiments in electronics. Here, girls visit the Qualcomm Institute’s StarCAVE virtual reality room. Read more…  

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Coding for a Cause

Then-sophomore Sneha Jayaprakash's mobile app, Bystanders to Upstanders (B2U), matches students with opportunities to volunteer for social causes. Together with fellow CSE undergrads, she won a series of grants and awards, and is now doing a startup. Read more...

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Internet of Things

Computer scientists at UCSD developed a tool that allows hardware designers and system builders to test security. The tool tags then tracks critical pieces in a hardware’s security system. Pictured (l-r): Ph.D. student Jason Oberg, Prof. Ryan Kastner, postdoc Jonathan Valamehr. Read more…

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The Gift That Keeps on Giving

CSE capped the 2012-'13 academic year with the announcement of an anonymous $18.5 million gift from an alumnus – making it the largest-ever alumni gift to UC San Diego. Read more...

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  • KnuEdge, UC San Diego Host Conference, Competition to Drive Next-Gen Machine Learning Performance

    Former NASA Administrator Dan Goldin, now CEO of KnuEdge, and Calit2 Director Larry Smarr have announced the Heterogeneous Neural Networks (HNN) Conference, to be held in spring 2017 in San Diego, Calif. KnuEdge delivers LambdaFabric neural computing technology that accelerates machine learning and signal processing. The event will also include a KnuEdge-sponsored research paper competition, challenging participants to enable the next generation of machine learning performance and efficiency through developing heterogeneous neural network algorithms.

    "Machine learning has captured the tech industry's attention due to its potential to positively disrupt computing, accelerating cutting-edge technologies ranging from medical research to financial and insurance risk analysis, facial and voice recognition and augmented reality," said Dan Goldin (at right), CEO of KnuEdge. "But to get there, we must encourage and accelerate innovation and unlock what's next in the field. That is why we've decided to launch the Heterogeneous Neural Networking Conference with Calit2."

    KnuEdge and Calit2 have worked together since the early days of the KnuEdge LambdaFabric processor when key personnel and technology from UC San Diego provided the genesis for the first processor design. The HNN Conference brings the two organizations back together to focus on advancing machine learning capability and performance. 

    "KnuEdge built its LambdaFabric processor technology to help deliver on the promise of machine learning," said Calit2's Smarr, who is also a professor of Computer Science and Engineering in the Jacobs School of Engineering. "Heterogeneous neural network algorithms are tailored to emulate the efficiency of specific neurobiological pathways that have evolved through natural history. However, this requires the ability to perform sparse matrix multiplication, and hardware optimized for sparse matrix multiplication has been largely unavailable. KnuEdge provides this optimized hardware, enabling analysis of the data as it's delivered from the real world -- allowing much faster computation and time-to-solution."  

    Preceding the conference, KnuEdge will sponsor a research paper competition for the most innovative and effective heterogeneous algorithms built on today's advanced computing architectures. Currently, there is relatively little opportunity for researchers in the emerging field of heterogeneous neural networks to share their work and collaborate with other experts. This workshop will enable these specialists to learn and exchange ideas with their peers, showcase their work and gain recognition as pioneers of the discipline. 

    The vast majority of machine learning computing today is based on homogenous and convolutional neural network technology, an approach that took hold largely due to the availability of traditional computer architectures, but at the expense of extraordinary computational time and power. Industry thought leaders have long suspected that much greater efficiency and performance could be driven through the use of sparse matrix versus dense matrix multiplication.

    For instance, the GoogLeNet paper, "Going Deeper with Convolutions" by Christian Szegedy et al., proposes a solution to overfitting and wasted computation with required large computing infrastructure: "The fundamental way of solving both issues would be by ultimately moving from fully connected to sparsely connected architectures, even inside the convolutions. Besides mimicking biological systems, this would also have the advantage of firmer theoretical underpinnings due to the groundbreaking work of Arora et al... On the downside, today's computing infrastructures are very inefficient when it comes to numerical calculation on non-uniform sparse data structures."

    Another paper, "Sparse Convolutional Neural Networks" by Baoyuan Liu et al., states: "In this paper, we show how expressing the filtering steps in a convolutional neural network using sparse decomposition can dramatically cut down the cost of computation, while maintaining the accuracy of the system... In our Sparse Convolutional Neural Networks (SCNN) model, each sparse convolutional layer can be performed with a few convolution kernels followed by a sparse matrix multiplication."

    In October 2015, at Mark Anderson's Future in Review conference, Calit2 Director Smarr announced the formation of a Pattern Recognition Laboratory (PRL), housed in Calit2's Qualcomm Institute. The PRL is dedicated to exploring acceleration of a wide range of machine learning algorithms on novel, non-von Neumann computer architectures. KnuEdge will provide its LambdaFabric technology this year to Calit2's PRL.

    "The mission of our Pattern Recognition Lab is to find major increases in energy efficiency and speedups by optimizing machine learning algorithms on novel computing architectures," said PRL Director Ken Kreutz-Delgado, a professor of Electrical and Computer Engineering in the Jacobs School. "We believe this KnuEdge-sponsored contest and conference will accelerate this mission, and we look forward to participating."

    Details on the competition, conference agenda, speakers and venue will be released in September 2016. To sign up for email notifications, please contact info@knuedge.com, with the subject line "HNN Conference 2016."

  • Computer Scientists Find Way to Make All That Glitters More Realistic in Computer Graphics

    Iron Man’s suit. Captain America’s shield. The Batmobile. These all could look a lot more realistic thanks to a new algorithm developed by a team of U.S. computer graphics experts.

    The researchers, led by Professor Ravi Ramamoorthi at the University of California San Diego, have created a method to improve how computer graphics software reproduces the way light interacts with extremely small details, called glints, on the surface of a wide range of materials, including metallic car paints, metal finishes for electronics and injection-molded plastic finishes.

    The method developed by Ramamoorthi and colleagues is 100 times faster than the current state of the art. They are presenting their work this month at SIGGRAPH 2016 in Anaheim, California. The method requires minimal computational resources and can be used in animations. Current methods can only reproduce these so-called glints in stills.

    Accurate rendering of a material’s appearance has always been a critical feature of computer graphics, Ramamoorthi said. It has become even more important with the advent of today’s ever-higher display resolutions.

    The standard approach to modeling the way surfaces reflect light assumes that the surfaces are smooth at the pixel level. But that’s not the case in the real world for metallic materials as well as fabrics, wood finishes and wood grain, among others. As a result, with current methods, these surfaces will appear noisy, grainy or glittery.“There is currently no algorithm that can efficiently render the rough appearance of real specular surfaces,” Ramamoorthi said. “This is highly unusual in modern computer graphics, where almost any other scene can be rendered given enough computing power.”

    The researchers’ solution was to break down each pixel of an uneven, intricate surface into pieces covered by thousands of light-reflecting points smaller than a pixel, called microfacets. The team then computed the vector that is perpendicular to the surface of the materials for each microfacet, called the point’s normal. The normal is key to figuring out how light reflects off a surface.

    For any specific computer-generated scene, the microfacets on a surface reflect light back to the computer’s virtual camera only if its normal is located exactly halfway between the ray from the light source and the light ray that bounces back from the surface. Computer scientists calculated the normals’ distribution within each patch of microfacets. Then they used the distribution to determine which normals where in that halfway position.

    The key to the algorithm’s speed is its ability to approximate this normal distribution at each surface location, called a “position-normal distribution.” This enables the algorithm to easily computer the amount of net reflected light with a speed that is orders of magnitude faster than previous methods. Using a distribution rather than trying to calculate how light interacts with every single microfacet resulted in considerable time and computer power savings.

  • Alumna to Launch App to Help Growers Monitor Crop Conditions

    CSE alumna Chandra Krintz (at left)  says she loves designing systems and solving problems. As a professor of computer science at UC Santa Barbara since 2001, Krintz (M.S., Ph.D. '98, '01)  is doing both with a project called SmartFarm. She is developing a mobile app to "help growers identify real-time conditions in their fields and run their operations more efficiently," according to a feature article in Capital Press, the top agriculture-related publication in the western U.S. "It's Amazon.com for ag, [and] we want to do something analogous to that with SmartFarm."

    Before the end of 2016, the UC San Diego alumna hopes to begin offering the app to farmers free of charge, for use on any smartphone or tablet (the sensors aren't free, but Krintz says they are relatively cheap). The app taps into cheap sensors installed in the soil surrounding each plant (or on the plant itself) at a 20-acre experimental farm north of Santa Barbara. "We believe that by taking very precise measurements at the plant level, we'll collect individual information... that will help a farmer make better decisions than what is possible today." The plant and soil conditions are integrated into weather and other reports to help farmers improve soil health and plan irrigation schedules..

    Krintz comes by her interest in agriculture naturally: she grew up on a farm in her native Indiana. After undergraduate work at Cal State Northridge, she did graduate school at UC San Diego, including her doctoral dissertation on reducing load delay to improve performance of Internet-computing programs (under then-advisor Brad Calder). Today, Krintz's research interests include programming support and adaptive optimization for cloud computing applications and systems, and techniques for efficient interoperation and integration of web services (such as SmartFarm and Vigilance, a software program to help people manage their diabetes). The current plan is to offer SmartFarm at no costm even though she has had the experience of co-founding a successful startup called AppScale Systems (where she remains chief scientist). AppScale makes open-source software to back up applications built around the Google App Engine and for data located in "the cloud" using platforms including Amazon Web Services, Google Cloud Platform, Alibaba Cloud, and others.. .

  • 'Critical Mass' in CSE for Computer Science Education Research

    CSE represents one of the top programs worldwide in the area of computer science education research, according to the Computing Education Blog. Georgia Tech computer scientist Mark Guzdial, who writes the blog, noted that only two U.S. universities can boast of having established a 'critical mass' of researchers in computer educaton research. He defines critical mass as including at least three faculty members whose primary research is in the area. The two universities he points to? University of Nebraska at Omaha (UNO), and the University of California San Diego. UNO's group is only now becoming large enough to qualify, while UC San Diego began building its program more than a decade ago, and it currently includes (pictured below l-r) Christine Alvarado, Beth Simon, Leo Porter and Scott Klemmer.

    In 2004 CSE hired lecturer Beth Simon who received Ph.D. from CSE in 2002. Since then, the group has gradually expanded to include Alvarado (2012) and Porter (2014). Porter -- another CSE Ph.D. graduate -- arrived from Skidmore College to join teaching professors Alvarado and Simon in the department. The blogger noted that Porter has won many of the best-paper awards at the two most prestigious conferences in the field, SIGCSE and International Computing Education Research (ICER).. Alvarado joined after being "key to the growth of women in computing at Harvey Mudd," noted Guzdial.  Beth Simon, who "still probably has the most ICER publications of anyone, has just returned to UCSD," following a leave of absence to work at Coursera, the largest platform for online learning.  But the list doesn't end there. The blog notes that CSE Prof. Scott Klemmer (who has dual appointments in CSE and Cognitive Science) also touches on computer science educaton research; notably, he gave the keynote presentation at the ICER conference in 2013, where he talked about “Design at Large” and how his work on design can be applied to computer-science education. Klemmer is currrently a co-director of the Design Lab at UC San Diego.

    Since 2014 CSE has had four faculty members all or partly focused in this area, and there is at least one new arrival in Cognitive Science this year: Philip Guo (at left) intends to work with Porter, Simon and Alvarado, and is expected to receive a partial appointment in CSE. He is coming from the University of Rochester, where he was an assistant professor of computer science. The blog notes that Guo "built the Python Tutor that we use in our ebooks, blogs frequently on CS Ed issues, and has been publishing a ton recently (including four papers at VL/HCC last year) on issues related to learning programming." .After finishing his Ph.D. at Stanford in Computer Science in 2012, Guo built online learning tools as a software engineer at Google, and did a postdoc at the online learning platform, edX, while in MIT's artificial-intelligence lab. So why join CogSci? "My recent research has been heading more and more toward using computers as tools to augment human cognition," writes Guo in his own blog, "rather than trying to improve the underlying computing technologies." He expects to collaborate with faculty who specialize in human-computer interaction in both departments, as well as with CSE faculty including Ranjit Jhala, Sorin Lerner and Bill Griswold in the area of programming languages and software engineering