The Utah Teapot - Spring 2016 by Chris Coleman

SCHOOL OF COMPUTING the university of utah速

Utah The

Teapot SPRING 2016

In this Issue 2 New Robotics Center

6 Programming and Prejudice

3 Alumni Profile: Colette Mullenhoff

7 News

4 SoC Welcomes New Faculty

UTAH LAUNCHES NEW ROBOTICS CENTER From the hulking Terminator to the lovable R2-D2, people’s notion of what robots are has been shaped mostly by science fiction. But science fact is much different. Robotics can range from sophisticated tools on manufacturing lines to precise machines that perform delicate surgeries. At the tip of robotics research are faculty members from the University of Utah’s Department of Mechanical Engineering and the School of Computing who have been developing the next generation of autonomous machines. Now, their work will be receiving even more recognition in the future — the Utah State Board of Regents has approved the new University of Utah Robotics Center Robotics lab located in Rio Tinto Kennecott Mechanical Engineering Building (UURC), the latest addition to the list of research centers for the U’s College of Engineering. more people, more students, more faculty and visitors.” “The advantages of this are really about visibility — you The center is the consolidation of eight faculty-run labs might say a sense of identity. It identifies us as a center researching a wide array of fields in robotics including of excellence as a robotics center in the state of Utah medical robotics, machine learning, autonomous robots, and elsewhere,” said School of Computing professor John self-driving cars, human motor control, drones, climbing Hollerbach, co-director of the center and director of the robots, and robot vision. In addition to the individual school’s robotics track. “It’s our hope that our increased labs, the center also received two larger lab spaces in visibility with the center translates into higher goals in the newly-refurbished Rio Tinto Kennecott Mechanical terms of funding and grants. We also hope it will attract Engineering Building. Another focus for the lab will be its continued outreach effort, promoting science and math for younger students throughout the state. That includes sponsoring summer computing camps for K-through-12 students as well as helping organize the regional FIRST Robotics and FIRST LEGO League competitions. The UURC offers a master’s degree and Ph.D. in the Robotics Track, a joint program of study. It was the second robotics program ever offered in the U.S. and has five faculty members from the mechanical engineering department and four from the School of Computing. “The center will not only provide the foundation for the Robotics Track but also allows our research and curriculum to flourish even more,” said U mechanical engineering associate professor Mark Minor, co-director of the center. “The center also provides a focal point for youth considering STEM careers.”

John Hollerbach

SPRING 2016

ALUMNI PROFILE Colette Mullenhoff

UT: What is your job at Industrial Light & Magic? CM: I’m an R&D Engineer, developing and supporting software for the Digital Model Shop artists (modelers & texture painters). I work closely with the artists so they get the best tools for the job. UT: Last year at this time you were celebrating your winning an Oscars. Can you tell us about the technology that lead to the award? CM: The award was for Industrial Light & Magic’s (ILM) Shape Sculpting System, which is an artist-driven system allowing them to quickly enhance and modify character animation and simulation performances. The system gives artists the ability to easily make corrections to simulations on a frame-by-frame basis, for example, fixing unsightly creases on an animating character. The system also enables artistically directed transformations, for example between Bruce Banner and the Hulk. The digital sculpting tools are motivated by traditional hands-on sculpting techniques, making them very intuitive for artists. UT: What did you do before joining ILM? CM: I worked as a software engineer, first at Singletrac Studio, a video game company in Salt Lake City. Then I went to Evans & Sutherland, also in Salt Lake City. Next I went to ESC Entertainment in Alameda, Calif., where I worked on “The Matrix” sequels. And I’ve been working at Industrial Light and Magic in San Francisco for the past 12 years.

With an early interest in computer graphics and a desire to work in the movie industry, Colette Mullenhoff set her sights on a career in special effects. After completing her undergraduate degree at the University of California, Santa Barbara, Colette entered the University of Utah’s graduate program in computer science due to its strong reputation for pioneering computer graphics work. Nearly two decades later, the Teapot catches up with Colette, working as an R&D Engineer at Industrial Light & Magic where she worked on the effects for such blockbusters as Harry Potter and the Goblet of Fire and Pirates of the Carribean: At World’s End. Utah Teapot: What is it like working in the movie industry? Colette Mullenhoff: It’s an interesting, challenging and extremely rewarding place to work. Knowing our hard work is helping the artists with their job and thus contributes to the movie-making process is very motivating. I love seeing (and often pointing to) the results of our labor on the big screen. I feel privileged to work with such an amazingly smart and talented group of people.

UT: Was this the career path you expected? CM: While I achieved my ultimate goal of working in the movie industry, my path to get there was slightly indirect, but filled with valuable experiences and brilliant people. UT: When did you graduate from the University of Utah? CM: In 1998, with a master’s in computer science. UT: What was your experience like at the U? CM: I received an excellent foundation in computer graphics, including computer-aided geometric design, computer vision and scientific visualization. I gained more experience writing software, with team collaboration and developing software in a large system (Alpha-1). My experiences at the U were a confirmation that I was pursuing the right passion. When Colette is not busy working at ILM, she enjoys spending time with family and friends, pursing outdoor adventures and exploring new places. Downhill skiing continues to be one of her favorite winter activities.

SPRING 2016

SOC WELCOMES NEW FACULTY

Aditya Bhaskara Assistant Professor

Tucker Hermans Assistant Professor

Aditya Bhaskara is an assistant professor at the University of Utah’s School of Computing, University of Utah. He received his Ph.D. from Princeton University in 2012, and his undergraduate degree in computer science from the Indian Institute of Technology, Bombay. He was a post-doctoral researcher at EPFL, Switzerland, and Google Research NYC before joining Utah as a faculty member. Dr. Bhaskara’s recent research has been at the intersection of theoretical computer science and machine learning, with the goal of designing novel learning algorithms that also come with guarantees. More broadly, his interests lie in the design of approximation algorithms for graph problems and in theoretical computer science.

Tucker Hermans joins the School of Computing from the Technische Universität Darmstadt, where he was a post-doctoral fellow working in the Intelligent Autonomous Systems Laboratory. He received his Ph.D. in robotics in 2014 from the Georgia Institute of Technology. He holds an A.B. in Computer Science and German from Bowdoin College, as well as an M.Sc. in Computer Science from Georgia Tech. Dr. Hermans’ research focuses on autonomous robot learning for manipulation and perception. He is interested in endowing robots with capabilities to assist people in their everyday lives and to replace humans in dangerous industrial and disaster settings. Dr. Hermans’ research leverages visual and tactile sensing so that robots can learn from their own experiences in order to manipulate new objects and understand new environments when encountered for the first time.

SPRING 2016

Alexander Lex Assistant Professor Alexander Lex received his bachelor’s, master’s, and PhD degrees from the Graz University of Technology. For the past three years he was a post-doctoral fellow and Lecturer at the Harvard School of Engineering and Applied Sciences. In 2011, he completed a research internship at the Computational Genomics Lab at the Harvard Medical School. He develops interactive data analysis methods for experts and scientists. Dr. Lex’s primary research interest is interactive data visualization and analysis, especially applied to molecular biology and pharmacology. His research is driven by the observation that there are many data analysis challenges that require human reasoning and cannot be solved automatically. He is also interested in Human Computer Interaction and Bioinformatics. He is a co-founder and leader of Caleydo, which is both open source software that can be used by life science experts to visualize biomolecular data and pathways but also a platform for implementing prototypes of radical visualization ideas.

Ladislav Kavan Assistant Professor

Ryan Stutsman Assistant Professor

Jason Wiese Assistant Professor

Ladislav Kavan is an assistant professor at the University of Utah’s School of Computing, Prior to joining Utah, he was an assistant professor at the University of Pennsylvania and research scientist at Disney Interactive Studios, in Salt Lake City. Dr. Kavan’s research focuses on real-time computer graphics, physicsbased animation, and geometry processing. His dual quaternion skinning algorithm has become a popular method to display animated 3D characters. More recently, he is exploring numerical methods in physics-based animation, with applications related to simulating the human body. His goal is to combine computer graphics with biomechanics and medicine. Dr. Kavan serves as an associate editor for ACM Transactions on Graphics since 2013 and received the NSF CAREER award in 2014.

Ryan Stutsman joins the School of Computing from the Databases group at the Microsoft Research Redmond Lab. He received his Ph.D. from Stanford University. Dr. Stutsman’s interests are in large-scale storage and database systems; his work focuses on software that leverages scale to improve the performance, efficiency, and reliability of systems comprised of massive numbers of machines. A key contribution of his research is a system that cost-effectively aggregates the main memory of hundreds of commodity machines into terabytes of unified storage with access times thousands of times faster than today’s data center systems. Overall, his work on distributed inmemory storage seeks to fuel the next generation of data-intensive real-time applications.

Jason Wiese joins the School of Computing this fall. He received his Ph.D. from the Human-Computer Interaction Institute at Carnegie Mellon University in 2015 and has spent the last several months working as a research scientist at FX Palo Alto Laboratory. Dr. Wiese’s interests lie in understanding and redefining the ways that people interact with the technology around them through a combination of building systems and a variety of user study methods. In his recent work Dr. Wiese has engaged the domain of personal data from the perspective of end users, contrasted with the common company-centric “big data” perspective. This user-centric focus on personal data has important ramifications for users, developers, and data providers.

SPRING 2016

PROGRAMMING AND PREJUDICE Software may appear to operate without bias because it strictly uses computer code to reach conclusions. That’s why many companies use algorithms to help weed out job applicants when hiring for a new position. But a team of computer scientists from the University of Utah, University of Arizona and Haverford College in Pennsylvania have discovered a way to find out if an algorithm used for hiring decisions, loan approvals and comparably weighty tasks could be biased like a human being. The researchers, led by Suresh Venkatasubramanian, an associate professor in the University of Utah’s School of Computing, have discovered a technique to determine if such software programs discriminate unintentionally and violate the legal standards for fair access to employment, housing and other opportunities. The team also has determined a method to fix these potentially troubled algorithms. Venkatasubramanian presented his findings Aug. 12 at the 21st Association for Computing Machinery’s SIGKDD Conference on Knowledge Discovery and Data Mining in Sydney, Australia. “There’s a growing industry around doing résumé filtering and résumé scanning to look for job applicants, so there is definitely interest in this,” says Venkatasubramanian. Many companies have been using algorithms in software programs to help filter out job applicants in the hiring process, typically because it can be overwhelming to sort through the applications manually if many apply for the same job. A program can do that instead by scanning résumés and

SPRING 2016

by Vince Horiuchi

Suresh Venkatasubramanian

searching for keywords or numbers (such as school grade point averages) and then assigning an overall score to the applicant. These programs also can learn as they analyze more data. Known as machine-learning algorithms, they can change and adapt like humans so they can better predict outcomes. Amazon uses similar algorithms so they can learn the buying habits of customers or more accurately target ads, and Netflix uses them so they can learn the movie tastes of users when recommending new viewing choices. But there has been a growing debate on whether machinelearning algorithms can introduce unintentional bias much like humans do. “The irony is that the more we design artificial intelligence technology that successfully mimics humans, the more that A.I. is learning in a way that we do, with all of our biases and limitations,” Venkatasubramanian says. Venkatasubramanian’s research

determines if these software algorithms can be biased through the legal definition of disparate impact, a theory in U.S. law that says a policy may be considered discriminatory if it has an adverse impact on any group based on race, religion, gender, sexual orientation or other protected status. Venkatasubramanian’s research revealed that you can use a test to determine if the algorithm in question is possibly biased. If the test — which ironically uses another machine-learning algorithm — can accurately predict a person’s race or gender based on the data being analyzed, even though race or gender is hidden from the data, then there is a potential problem for bias based on the definition of disparate impact. If the test reveals a possible problem, Venkatasubramanian says it’s easy to fix. All you have to do is redistribute the data that is being analyzed — say the information of the job applicants — so it will prevent the algorithm from seeing the information that can be used to create the bias.

NEWS SoC Junior Wins Harvard Hackathon Award Calvin Chhour, a junior in the University of Utah’s School of Computing, took first place in the first annual Harvard Hackathon. Chhour along with three other team members won the International Development award for their project, Stegosaurus. The three-day HackHarvard event challenged students to create and design projects using new technology. Chhour, and his team competed against more than 100 other teams from universities in the U.S. and around the world. “It was overwhelming at first, but once we had our idea and got started things really came together. It was awesome collaborating and working with other students and having the mentors available for advice,” said Chhour. Chhour and his team developed a Google Chrome extension called Stegosaurus. The chat program can encrypt messages, files, and photographs into images that are deconstructed and revealed when sent to other Stegosaurus users. The purpose for the program is for use in countries where freedom of speech is oppressed and in domestic violence situations.

Calvin Chhour

Utah Students Win ACM Programming Contest The team, “Uncompilables,” which includes students William Li, Liam Machado, and Samuel Zachary, beat 52 other teams in the U.S. and Canada to win the ACM Programming Contest. Their first-place finish qualifies them for the World Finals in Thailand this May. “William, Liam, and Sam performed brilliantly — their years of practice prepared them well. Thanks to these three, the U has finally beaten the Canadians (and their training program) in grand style,” said Peter Jensen, associate professor in the U’s School of Computing and team coach. The ACM International Collegiate Programming Contest (ICPC) is the premiere global programming competition conducted by and for the world’s Liam Machado, Peter Jensen, Samuel Zachary, William Li universities. The competition is operated under the Association for Computer Machinery (ACM), is sponsored by IBM, and is headquartered at Baylor University in Waco, Texas. Teams of three students represent their universities in multiple levels of regional competition. Volunteer coaches prepare their teams with training and instruction in algorithms, programming and teamwork strategy. In the contest, teams attempt to solve as many programming problems as possible in five hours. Each year, the event has always been competitive with the Canadian teams usually winning due to their yearlong training programs. The Uncompilables team members solved the same number of problems (eight) as the second-place team but won the contest because they were slightly faster. The last time the University of Utah won the regional competition was in 1998.

SPRING 2016

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