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COLLOQUIUM Department of Computer Science and Engineering University of South Carolina Subrahmanyam Bulusu Marine Science Program & Department of Earth and Ocean Sciences University of South Carolina Date: April 25, 2013 Time: 1400-1500 (2:00pm-3:00pm) Place: Swearingen 1A03 (Faculty Lounge) Abstract Salt plays an important role in our daily lives. True, salt makes our food tastier, but perhaps its most significant role is as an ingredient in Earth's climate. A measurement of sea surface salinity, or the concentration of salt at the ocean’s surface, gives us vital information on global ocean circulation and how fresh water moves between the ocean and other reservoirs through the water cycle, the process by which water circulates from the ocean, to the atmosphere, to the land, and then back to the ocean. In the past, researchers assumed that salinity did not play a significant role in the dynamics and thermodynamics of the oceans because it has little variation ind the global oceans. Salinity and temperature together affect the density of seawater, and its circulation. Though temperature has been measured extensively, both in-situ and remotely sensed, salinity observations have been lacking. Regular in-situ salinity measurements have been restricted to just a small fraction of the oceans. Most of these measurements have been by ships-of-opportunity along major shipping lines. Due to these limited measurements, basin-scale processes and variability studies that require the incorporation of salinity data have been a challenge. The launch of the European Space Agency’s (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite in November 2009, and the United State’s NASA and Space Agency of Argentina’s (CONAE; Comisión Nacional de Actividades Espaciales) Aquarius/ Satellite de Aplicaciones Cientificas (SAC)-D satellite mission in June 2011, opened a new era for providing global oceans salinity observations, which will improve our understanding of salinity variability and dynamics. SMOS has been designed to observe soil moisture over the Earth's landmasses and salinity over the oceans. Aquarius/SAC-D science objectives seek to provide high quality salinity data that will help enhance the study of ocean circulation, the global hydrological cycle, climate variability, land processes, land use, soil moisture, natural hazards, health applications, cryosphere, etc. Dr. Subrahmanyam (Subra) Bulusu is an Associate Professor, with appointments in the Marine Science Program and the Department of Earth and Ocean Sciences at the University of South Carolina. He obtained his Ph.D. from the University of Southampton, UK in 1998, did two-year postdoctoral work at the Florida State University, and then became Research faculty at FSU until 2005. He joined USC in August, 2005 as an Assistant Professor and became an Associate Professor with tenure in 2009. Since his arrival at USC, he has established a state-of-the art Satellite Oceanography Laboratory in the Department of Earth and Ocean Sciences. Last year he was appointed as the USC campus Director for the NASA/SC Space Grant Consortium. He was awarded the prestigious Breakthrough Rising Star designation at USC in 2013.

Our speaker will be Jeff McElroy. Many of you know Jeff as a member of our IAB. Jeff has also started a number of highly successful high tech companies. Presently he is a principal of Bang! Technologies which specializes in helping entrepreneurs start high tech companies. Jeff is a good speaker and has had a number of interesting experiences that he will talk about. Jeff was a student here in the 1980s. At that time he persuaded Prof Hillborn in the Electrical and Computer Engineering department to let himself and another student do an Individual Study class to build a “car” to compete in the IEEE SoutheastCON hardware contest. This was our first entry into that contest which later became the basis for the capstone project in both the Electrical and the Computer Engineering programs. Following graduation one of his first companies was formed to develop a cell phone assistant using voice recognition. The basic idea was that you could use your phone as a personal secretary. For example you could ask your phone to “call Joe Smith” and it would look up the number and make the connection (this was 25 years ago, long before the iphone) or you could ask it to make a note of something said during the conversation so you wouldn’t forget it.

COLLOQUIUM Department of Computer Science and Engineering University of South Carolina Lantao Liu Department of Computer Science and Engineering Texas A&M University Date: April 11, 2013 Time: 1400-1500 (2:00pm-3:00pm) Place: Swearingen 1A03 (Faculty Lounge) Abstract Like humans, multiple robots need to collaborate with each other to accomplish certain missions efficiently. Task allocation (or assignment) is an important component for building multi-robot systems that behave as a coordinated whole. This talk will cover two settings in which coordination methods using task allocation techniques are effective; the two settings bring together ideas from different fields: distributed AI, operations research, graph theory, high performance computation, and economics. Specifically, I will introduce two decentralized task assignment methods: (1) a multi-level assignment decentralization framework based on matrix partitioning in order to cluster the strongly related robot-tasks pairs, and (2) a task-swap based assignment algorithm with many unique features that are particularly suitable for distributed multi-robot task allocation. Furthermore, I am also going to discuss how the classic assignment algorithms can still be extended to solve new problems in the multi-robot domain, e.g., how the combinatorial assignment algorithm itself can be extended to tackle the task allocation involving uncertainty; and how the matching bigraph data structure of the assignment algorithm can be manipulated to solve the robotics routing and formation control problems. Lantao Liu is a Ph.D. candidate (with dissertation successfully defended) in the Department of Computer Science and Engineering at Texas A&M University. Liu works on developing coordination methods for multiple robots. His dissertation was on task allocation problems. Liu also works on estimating and analyzing the properties of swarm systems, motion planning for robotics, and protein folding in computational biology. Recently, Liu has been awarded the prestigious Texas A&M University Dissertation Fellowship and the Chinese Government Scholarship for outstanding students abroad, which is based on nominations by Chinese embassies worldwide. Liu graduated with highest honors (academic silver medalist) from the Department of Automatic Control at Beijing Institute of Technology in 2007.

COLLOQUIUM Department of Computer Science and Engineering University of South Carolina Jingjin Yu Department of Electrical and Computer Engineering University of Illinois at Urbana Champaign Date: April 4, 2013 Time: 1330-1430 (1:30pm-2:30pm) Place: Swearingen 2D05 (Former Staff Lounge) Abstract As we know, Kalman filters, given their effectiveness in handling probabilistic events, play an important role in the processing of probabilistic sensor information, such as point clouds gathered from laser scanners. However, not all data is amenable to probabilistic analysis - some problems induce inherently combinatorial data structures. For these problems, a combinatorial filtering approach is necessary. In this talk, I discuss two such robotics (sensor fusion) problems. The first problem generalizes visibility-based pursuit-evasion games and seeks to maintain the distribution of hidden targets that move outside the field-of-view of the pursuers while a sensor sweep is being performed. Observing that key events happen only when the shadow region (all points invisible to the sensors) changes combinatorially or when targets pass in and out of the field-of-view, we can significantly reduce the amount of sensor information that we store, without discarding any useful information for computing the distribution of the hidden targets. This allows us to "live" inside a erived information space, which gives rises to efficient algorithms. These filtering algorithms provide critical information for tasks such as counting, herding, pursuit-evasion, and situational awareness in general. Next, we study the problem of using sparse, heterogeneous sensors to verify the stories (i.e., path samples) of agents (robots or people). Since there are two sets of data, the combinatorial filter for this problem can be built in two ways: Using a filter (an automaton) built from sensor data to process the story or using a filter built from the story to process the sensor data. Both approaches lead to dynamic programming based (optimally) efficient algorithms. In addition to exact path inference, our method also applies to approximate path inference that allows errors in the story. Besides immediate applicability toward security and forensics problems, the idea of external verification is promising in complementing design time model verification. Jingjin Yu received a B.S. in materials science and engineering from USTC, Hefei, China (1998). He holds M.S. degrees in chemistry (University of Chicago, 2000), mathematics (University of Illinois at Chicago, 2001), and computer science (University of Illinois at Urbana Champain, 2010). He is currently a Ph.D. candidate with the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. His research interests include robotics and control theory.

Sidney Valentine ABSTRACT Supervisory Control and Data Acquisition (SCADA) systems are widely used in automated manufacturing and in all areas of our nation's infrastructure. Applications range from chemical processes and water treatment facilities to oil and gas production and electric power generation and distribution. Current research on SCADA system security focuses on the primary SCADA components and targets network centric attacks. Security risks via attacks against the peripheral devices such as the Programmable Logic Controllers (PLCs) have not been sufficiently addressed. Our research results address the need to develop PLC applications that are correct, safe and secure. This research provides an analysis of software safety and security threats. We develop countermeasures that are compatible with the existing PLC technologies. We study both intentional and unintentional software errors and propose methods to prevent them. The main contributions of this dissertation are: Develop a taxonomy of software errors and attacks in ladder logic Model ladder logic vulnerabilities Develop security design patterns to avoid software vulnerabilities and incorrect practices Implement a proof of concept static analysis tool which detects the vulnerabilities in the PLC code and recommend corresponding design patterns.

COLLOQUIUM Ioannis Rekleitis School of Computer Science McGill University Date: March 28, 2013 Time: 2:00pm-3:30pm Place: Faculty Lounge, Swearingen 1A03 Abstract The last few years, robots have moved from the pages of science fiction books into our everyday reality. Currently, robots are used in scientific exploration, manufacturing, entertainment, and household maintenance. While the above advances were made possible by recent improvements in sensors, actuators, and computing elements, the research of today is focused on the computational aspects of robotics. In particular, methodologies for utilizing the vast volumes of data that can be generated by a robotic mission, together with techniques that would allow a robot to respond adequately in unforeseeable circumstances are the challenges of tomorrow. This talk presents an overview of algorithmic problems related to robotics, with the particular focus on increasing the autonomy of robotic systems in challenging environments. Cooperative Localization Mapping and Exploration employs teams of robots in order to construct accurate representations of the environment and of the robot's pose. The problem of coverage has found applications ranging from vacuum cleaning to humanitarian mine removal. A family of algorithms will be presented that solve the coverage problem efficiently in terms of distance travelled. Interestingly, the planetary and underwater exploration share many challenges when viewed from an algorithmic point of view. An a priori unknown environment and limited communications are among the most obvious. I would present recent results from a multi-robot experiment employing a UAV, a USV, and a AUV operating in sync with a remote marine biologist located thousands of kilometers away. Ioannis Rekleitis is an Adjunct Professor at the School of Computer Science, McGill University, Montreal, Canada. Between 2004 and 2007 he was a visiting fellow at the Canadian Space Agency. During 2004 he was at McGill University as a Research Associate in the Centre for Intelligent Machines with Professor Gregory Dudek in the Mobile Robotics Lab (MRL). Between 2002 and 2003, he was a Postdoctoral Fellow at the Carnegie Mellon University in the Sensor Based Planning Lab with Professor Howie Choset. He was granted his Ph.D. from the School of Computer Science, McGill University in 2002 under the supervision of Professors Gregory Dudek and Evangelos Milios. Thesis title: "Cooperative Localization and Multi-Robot Exploration." His Research has focused on mobile robotics and in particular in the area of cooperating intelligent agents with application to multi-robot cooperative localization, mapping, exploration and coverage. His interests extend to computer vision and sensor networks. He has worked with underwater, terrestrial, aerial, and space robots. Ioannis Rekleitis has published more than sixty journal and conference papers. His work can be found online at: http://www.cim.mcgill.ca/~yiannis/.

by Dr. Duncan Buell Scholars in the humanities who are moving into the digital world are confronting a complex issue: how to balance work on and use of digital tools with “research” in their respective disciplines. Are some scholarly activities real research, while others are “just work”? This is an issue that has been faced in the sciences, where it has been resolved at least in part and relates to the serious issue of “credit” for the creation of digital artifacts. While you eat your lunch, Buell will give his view on how to distinguish work and research, as well as the role of making tools in support of and as part of scholarly disciplinary work. Coffee will be provided. More information here.
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COLLOQUIUM Department of Computer Science and Engineering University of South Carolina Jenay M. Beer School of Psychology Georgia Institute of Technology Date: March 20, 2013 Time: 1430-1530 (2:30pm-3:30pm) Place: Swearingen 2A31 Abstract Many older adults wish to remain in their own homes as they age. However, challenges threaten an older adult’s ability to age in place, and even healthy independently living older adults experience challenges in maintaining their home. Challenges with aging in place can be compensated through technology, such as home assistive robots. However, for home robots to be adopted by older adult users they must be designed to meet older adults’ needs for assistance and the older users must be amenable to robot assistance for those needs. In this talk, I will discuss a range of projects (both quantitative and qualitative in nature) assessing older adults’ social interpretation, attitudes, and acceptance of assistive robotics. Study findings suggest that older adults’ assistance preferences discriminated between tasks, and the data suggest insights as to why older adults hold such preferences. The talk will detail a multidisciplinary approach to studying human-robot interaction (HRI) and how findings from user studies can apply to preliminary design recommendations for future assistive robots to support aging in place. Jenay M. Beer is a 6th-year Ph.D. student in Engineering Psychology at Georgia Tech. She is a member of the Human Factors and Aging Laboratory, co-directed by Wendy A. Rogers and Arthur D. Fisk. Her research intersects the fields of Human Robot Interaction (HRI) and Psychology. Specifically, she studies home-based robots designed to assist older adults to maintain their independence and age in place. She has studied a variety of robotic systems and topics such as emotion expression of agents, user acceptance of robots, healthcare robotics, and the role of robot autonomy in HRI. Jenay received a B.A. degree in Psychology from the University of Dayton, Ohio and an M.S. in Engineering Psychology from Georgia Tech.