Talks:

• Jan. 13 2017
  • Speaker: Gabriel Terejanu
  • Affiliation: CSE, USC
  • Location: SWGN 2A31
  • Time: 2:20 - 3:10 PM
  • Title: Introduction to the course
• Jan. 20 2017
  • Speaker: Alberto Quattrini Li
  • Affiliation: CSE, USC
  • Location: SWGN 2A31
  • Time: 2:20 - 3:10 PM
  • Title: Multirobot systems for exploration: indoor and marine environments
  • Abstract: The use of multirobot systems is an effective way to efficiently accomplish tasks in many real-life applications, such as cleaning, surveillance, and environmental monitoring. To fully exploit their potential, one of the challenging aspect is effectively coordinating them and ensuring some form of communication between the robots. In this talk, a short taxonomy on multirobot coordination and communication-constrained planning is first presented. Then, some recent results from the multirobot exploration will be presented to highlight some aspects that need to be considered for the design of multirobot systems, including semantic information and the type of communication constraints. Further, ongoing work will be shown in marine environments with multiple robots, possibly heterogeneous, highlighting some of the additional challenges that are faced in such environments. The talk will conclude by showing some open problems and future directions for the coordination of multirobot systems.
  • Bio: After being a postdoctoral fellow in the Autonomous Field Robotics Laboratory (AFRL) at the Computer Science and Engineering Department of the University of South Carolina, Alberto is currently working as Research Assistant Professor in the same department. He received a M.Sc. in Computer Science Engineering (2011) and a Ph.D. in Information Technology (2015) from Politecnico di Milano. From February to July 2014, he was a visiting PhD student at Research on Sensor Networks Lab at the Computer Science Department of the University of Minnesota. His main research interests include autonomous mobile robotics and underwater robotics, dealing with problems that span from multirobot exploration to visual-based state estimation.
• Jan. 27 2017
  • Speaker: Ioannis Rekleitis
  • Affiliation: CSE, USC
  • Location: SWGN 2A31
  • Time: 2:20 - 3:10 PM
  • Title: Field Work in Robotics Research
  • Abstract: TBD
  • Bio: Ioannis Rekleitis is an Assistant Professor at the Computer Science and Engineering Department, University of South Carolina, and an Adjunct Professor at the School of Computer Science, McGill University. 2004-2007 he was a visiting fellow at the Canadian Space Agency working on Planetary exploration and On-Orbit-Servicing of Satellites. 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, Montreal, Quebec, Canada in 2002 under the supervision of Professors Gregory Dudek and Evangelos Milios. Thesis title: "Cooperative Localization and Multi-Robot Exploration". He finished his M.Sc. in McGill University in the field of Computer Vision in 1995. He was granted his B.Sc. in 1991 from the Department of Informatics, University of Athens, Greece. 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.
• Feb. 03 2017
  • Speaker: Dr. Ron Addie
  • Affiliation: University of Southern Queensland
  • Location: SWGN 2A31
  • Time: 2:20 - 3:10 PM
  • Title: Protecting Services from Security Mis-configuration
  • Abstract: It is understood that ICT security can be defined and enforced through rules. In this paper, the concept of rules which define and ensure users' access to services is introduced. Examples of how service is hindered by otherwise sensible security rules are presented. The concept of service protection policies is introduced. We use ns3 and Click in simulations to check the consistency of aggregate security policy by checking that service protection rules are valid. We show that these can improve the performance of the network experienced by users and increase network security.
  • Bio: Ron Addie received his BSc degree from Monash University in 1972 and completed his PhD at Monash University in the area of semi-Markov queues in 1986. From 1972 to 1992, he worked in Telstra Research Laboratories where he was involved in the development of ATM, teletraffic, and network analysis and design. In 1992 he moved to the University of Southern Queensland, where he holds the position of Associate Professor. His current research interests include queueing theory for long-range dependent traffic, rare event simulation, layered network design, network analysis, design and simulation software and security of web information systems. He is the author or co-author of many journal and conference papers, primarily in the area of communications, with more 1000 citations (according to Google Scholar).
• Feb. 10 2017
  • Speaker: Jason O'Kane
  • Affiliation: CSE, USC
  • Location: SWGN 2A31
  • Time: 2:20 - 3:10 PM
  • Title: TBD
  • Abstract: TBD
  • Bio: TBD
• Feb. 17 2017
  • Speaker: Aziz Mohaisen
  • Affiliation: State University New York at Buffalo
  • (New) Location: 300 Main B101
  • (New) Time: 10:30 - 11:45
  • Title:Security Analytics for Defeating Automated Internet-scale Threats
  • Abstract: Billions of devices are connected to the Internet today, significantly changing the threat landscape by lending adversaries unprecedented resources to launch automated attacks, and requiring new threat analysis and defenses. In this talk, I will argue that big data analytics can play an important role in securing the Internet, and exemplify my argument with applications to distributed denial of service (DDoS), malware analysis, and massively multiplayer online role-playing game (MMORPG) bot detection. First, I will present an analytical view of 50,000 unique and verified DDoS attacks on services on the Internet. I will show how adversaries’ spatiotemporal traits follow predictable patterns, consecutive attacks follow certain patterns allowing prediction of future threat, and attackers are highly collaborative. Second, I will show how big data analytics are applied to malware analysis and software behavior profiling, and demonstrate optimizations to scale such analytics. Third, I will discuss an analytics framework for game bot detection in MMORPG using self-similarity of user behavior. By applying this framework to three large online games, I demonstrate how this analytics approach can be used to extract general features of behavior and effectively detect game bots in practice. I will conclude by highlighting my vision of how this analytics approach can be applied to realize effective and proactive defenses, and extended for other applications.
  • Bio: Aziz Mohaisen is an Assistant Professor of Computer Science at the University at Buffalo. The current focus of his research is building security analytics for understanding and defending threat in software and networks, with applications to Malware, DDoS, DNS, MMORPG, IoT, Blockchain, etc. His work has been supported by various awards from NSF, NRF, AFRL and AFOSR. He was the recipient of the US Air Force Summer Faculty Fellowship (2016). Before joining UB in 2015, he was a senior research scientist at Verisign Labs in the Washington D.C. area (2012-2015) and a Research Engineer at ETRI in South Korea (2007-2009). He earned his M.Sc. and Ph.D. in Computer Science from the University of Minnesota in 2012, and was a recipient of the Doctoral Dissertation Fellowship (2011). Aziz is an avid (ultra)marathoner, and when not doing research or running, he likes to explore the world with his three growing kids.
• Feb. 20 2017 Bonus Seminar
  • Speaker: Zhichuan Huang
  • Affiliation: University of Maryland, Baltimore County
  • (New) Location: Swearingen 1A03 (Faculty Lounge)
  • (New) Time: 10:45 - 12:00
  • Title:Data-Driven Applications in Smart Cities - Data and Energy Management in Microgrids
  • Abstract: The White House announced Smart Cities Initiative with $160 million investment to address emerging challenges in this inevitable urbanization. Under the scope of this initiative, my work addresses emerging problems in the smart energy systems in connected communities with a data-driven approach, including sensing hardware design, streaming data collection to data analytics and privacy, system modeling and control, application design and deployments. In this talk, I will focus on an example of data driven solutions for data and energy management in smart grids. I will first show how to collect the energy data from large-scale deployed low cost smart meters and minimize the communication and storage overhead. Then I will show how we can conduct energy data analytics with the collected energy data and utilize data analytics results for real-time energy management in a microgrid to minimize the operational cost. Finally, I will present real-world impact of my research and some future work about CPS in smart cities.
  • Bio: Zhichuan Huang is a Ph.D. candidate in Department of Computer Science and Electrical Engineering at University of Maryland, Baltimore County. He is interested in incorporating big data analytics in Cyber-Physical Systems (also known as Internet of Things under some contexts) for data driven applications in Smart Connected Communities. His current focus is on data driven solutions for smart energy systems including from sensing hardware design, streaming data collection to data analytics and privacy, system modeling and control, application design and deployments. His technical contributions have led to more than 20 papers, featuring 14 first-author papers in premier venues, e.g., IEEE BigData, ICCPS, IPSN, RTSS and best paper runner-up in BuildSys 2014.
• Feb. 24 2017
  • Speaker: Dr. Shiyi Wei
  • Affiliation: University of Maryland, College Park
  • (NEW) Location: 300 Main B101
  • (NEW) Time: 10:30-11:45 AM
  • Title: Towards Practical Program Analysis: Introspection and Adaptation
  • Abstract: Software is ubiquitous. As its importance grows, the mistakes made by programmers have an increasingly negative effect, leading to critical failures and security exploits. As software complexity and diversity grows, such negative effects become even more likely. Automated program analysis has the potential to help. A program analysis tool approximates possible executions of a program, and thereby can discover otherwise hard-to-find errors. However, significant challenges must still be overcome to make program analysis tools practical for real-world software. I have gained substantial experience in building novel program analysis tools whose aim is to produce more secure and reliable software. Recently, I have focused on the challenge of building analysis tools that perform well (i.e., can analyze realistic code in a reasonable amount of time) and are precise (i.e., do not produce too many "false alarms"). To this end, I have developed an approach that systematically uncovers sources of imprecision and performance bottlenecks in program analysis. The goal is to significantly reduce the time-consuming manual effort otherwise required during analysis design process. In addition, I have designed an adaptive analysis, in which appropriate techniques are selected based on the coding styles of the target programs. Selection is based on heuristics derived from a machine learning algorithm. The idea is that precise techniques can be deployed only as where and when they are needed, leading to a better balance overall.
  • Bio: Shiyi Wei is a post-doctoral associate at University of Maryland, College Park. He obtained his Ph.D. in Computer Science from Virginia Tech in 2015, and B.E. in Software Engineering from Shanghai Jiao Tong University in 2009. His research interests span the areas of Programming Languages, Software Engineering and Security. The goal of his research is to make program analysis practical for improving the security and reliability of real-world software. He has published articles at top venues in his areas of interest, such as PLDI, FSE, ECOOP, and ISSTA. He has interned at IBM T. J. Watson Research Center.
• Feb. 27 2017
  • Speaker: Rong Su Bonus Seminar
  • Affiliation: Nanyang Technological University
  • Location: Swearingen 1A03 (Faculty Lounge)
  • Time: 9:30 - 10:45 AM
  • Title: Event-Driven Modeling and Distributed Task Routing and Scheduling in Cyber Physical Material Handling Systems
  • Abstract: We are at the dawn of the 4th industrial revolution - the era of the ICT backed Smart Manufacturing (or Industry 4.0). Among all challenges, the problem of how to model and manage efficiently the low volume high mixed (LVHM) manufacturing processes has been gaining more and more attentions from both academia and industry, owing to the rise of the maker/Do-It-Yourself (DIY) culture around the world. The major challenges in both modelling and operation planning are due to the complexity resulted from the scale and heterogeneity of the system, and the sophistication of relevant operations. In this talk I will first briefly mention one novel event-based modelling framework for cyber physical material handling, which, by separating operations and the corresponding materials, can significantly improve reusability of pre-developed models, making it potentially feasible to support a ?drag and play? strategy, when constructing or reconfiguring a material handling system without a need of starting from scratch. After that, I will focus on a novel task routing and scheduling approach within a distributed synthesis framework based on time weighted discrete-event models. By going through an example of operation planning for linear cluster tools, I will show the potential advantage of this supervisor synthesis approach. In addition, I will show that the same modelling and synthesis framework can be applied to robot motion planning problems, accompanied by large?scale case studies in a simulated environment.
  • Bio: Dr. Rong Su obtained his Bachelor of Engineering degree from University of Science and Technology of China in 1997, and Master of Applied Science and PhD degrees from University of Toronto in 2000 and 2004, respectively. After being affiliated with University of Waterloo and Technical University of Eindhoven, he joined Nanyang Technological University in 2010. Dr Su?s research interests include discrete event system theory, model-based fault diagnosis, operation planning and scheduling and control of multi-agent systems, with applications in smart manufacturing, intelligent transportation, human-robot interface, power management and smart buildings. He has more than 110 publications and 2 patents in the aforementioned areas. So far he has been involved in several projects funded by Singapore National Research Foundation (NRF), Singapore Agency of Science, Technology and Research (A*STAR), Singapore Ministry of Education (MoE), Singapore Civil Aviation Authority (CAAS) and Singapore Economic Development Board (EDB). Dr Su is a senior member of IEEE, and an associate editor for Journal of Discrete Event Dynamic Systems: Theory and Applications, Transactions of the Institute of Measurement and Control, and Journal of Control and Decision. He is also the Chair of the Technical Committee on Smart Cities in the IEEE Control Systems Society.
• Feb. 28 2017 Bonus Seminar
  • Speaker: Mahanth Gowda
  • Affiliation: University of Illinois, Urbana Champaign (UIUC)
  • Location:Swearingen 2A21
  • Time: 3:00 - 4:15 PM
  • Title: Motion Tracking Problems in IoT: Sports, Drones and Wireless Networks
  • Abstract: Motion tracking is a broad and classical problem that dates back many decades. While significant advances have come from the areas of robotics, control systems, and signal processing, the emergence of mobile and IoT devices is ushering a new age of embedded, human-centric applications. Fitbit is a simple example that has rapidly mobilized proactive healthcare; medical rehabilitation centers are utilizing wearable devices towards injury diagnosis and prediction. In this talk, I will discuss a variety of (new and old) IoT applications that present unique challenges at the intersection of mobility, multi-modal sensing, and indirect inference. For instance, I will discuss how inertial sensors embedded in balls, racquets, and shoes can be harnessed to deliver real-time sports analytics on your phone. In a separate application, I will show how GPS signals can be utilized to track the 3D orientation of an aggressively flying drone, ultimately delivering the much needed reliability against crashes. I will also show how injecting controlled mobility into conventional wireless infrastructure can open new opportunities in indoor WiFi and outdoor cellular networks. I will end with how arm motions of an individual can be inferred from smartwatch sensors alone, even when her arm and body are moving simultaneously (e.g., dancing). In general, I hope to show that information fusion across wireless signals, sensors, and physical models can together deliver motion-related insights, useful to a range of applications in IoT, healthcare, and cyber physical systems.
  • Bio: Mahanth Gowda is a PhD candidate in the Computer Science department at the University of Illinois, Urbana Champaign (UIUC). His research interests include wireless networking, mobile sensing, and wearable computing, with applications to IoT, cyber physical systems, and human gesture recognition. He has published across diverse research forums, including NSDI, Mobicom, WWW, Infocom, Hotnets, ASPLOS, etc. Prior to joining UIUC, Mahanth obtained his M.S. from Duke University, and a B.Tech from Indian Institute of Technology, Varanasi. He has interned at Microsoft Research, IBM Labs, and recently at the wearable computing group at Intel.
• Mar. 01 2017 Bonus Seminar
  • Speaker: Nikolaos Vitzilaios
  • Affiliation: Kingston University, London UK
  • Location: SWGN Faculty lounge (1A03)
  • Time: 1:00 - 2:00 PM
  • Title: TBD
  • Abstract: The area of Unmanned Systems & Robotics has seen a tremendous growth over the last decades with autonomous systems being rapidly developed in many domains resulting in a wide range of applications that we can see in our daily lives (drones, autonomous cars, industrial robots, medical and service robotics, space robotics, etc.). This presentation will show the research of Dr. Nikolaos Vitzilaios in this area over the last 10 years, presenting the developments in specific areas over time and focusing on latest research as long as future research plans.
    The presentation will include research in the following areas:
    - Aerial Robotics: applications of automatic control in unmanned fixed-wing aircraft and rotorcraft, including theoretical aspects as well as applied hardware and software developments. Several platforms have been developed over the last 10 years while the latest development will be presented based on a patented design of a dual-tilting quadcopter able to perform advanced navigation and control in narrow spaces as well as fault-tolerant control.
    - Mobile Robotics: several ground robotic platforms will be presented, including customized commercial mobile robots as well as in-house built robots (including a patented one). These platforms are built for different applications and projects and the presentation will focus on the collaboration with aerial robots in critical missions.
    - UAV Aerodynamics: novel research in the area of circulation control wings for fixed-wing aircraft will be presented.
    - Marine Robotics: a novel propulsion system will be presented for low speed propeller less robots that are required to be used in extreme environments (nuclear reactors).
    - Medical Robotics: the latest research on the modelling of the human thumb will be presented accompanied by a new kinematic model that shows the importance of the thumb in grasping and how this will affect our perception for the development of future robotic hands.
    - Mechatronic Systems: the development of an automatic bike gear shifter (patent pending).
    - Modeling and control of complex and highly nonlinear systems.
    - Future trends and planned research in perception and control.
    
  • Bio: Vitzilaios has more than 10 years of research and more than 5 years of teaching experience in the areas of Robotics and Controls, with notable presence in the Robotics & Automation society, more than 30 publications, one US patent and successful grant applications both in US and UK. His background is interdisciplinary from the areas of Mechanical Engineering, Electrical Engineering and Computer Science. His research interests span the broad area of Autonomous Unmanned Systems where he has significant hands-on experience in all kinds of robotic applications (aerial, ground, marine, industrial, biomedical). His research is mainly experimental and his interests include prototype development and commercialization of research outcomes. He is a Fellow of the Higher Education Academy in UK and a member of IEEE, AIAA, AUVSI and IFAC. He is a Chartered Mechanical Engineer in the Technical Chamber of Greece since March 2005.
• Mar. 02 2017 Bonus Seminar
  • Speaker: Yonghong Yan
  • Affiliation: Oakland University
  • Location: 300 Main B101
  • Time: 3:00-4:15 PM
  • Title: Portable Parallel Programming in an Age of Architecture Diversity for High Performance
  • Abstract: In this era of multicore, manycore and heterogeneous architectures with deep memory systems, portable parallel programming has become much more challenging than ever for both computation-intensive scientific and engineering applications, and applications that involve large-scale data processing such as computer vision or machine learning. It requires applications to expose significantly more concurrency at multiple levels including intra-node and inter-node, and to optimize local and shared data access with regard to the memory hierarchy of SRAM, DRAM, HBM, and storage. In this talk, the speaker will highlight the latest development of node-level parallel programming models for extreme scale performance, and discuss challenges and ongoing work in his research team for compiler and runtime systems to realize those models for many-/multi-core CPUs and GPUs. The talks will conclude with the discussion of memory-centric architecture and programming for future computer systems.
  • Bio: Dr. Yonghong Yan is an Assistant Professor from Oakland University, Rochester MI, and a member of OpenMP Architectural Review Board and OpenMP Language Committee. Dr. Yan is an expert in parallel computing, compiler technology and high performance computer architecture and systems. He is an NSF CAREER awardee. His research team develop intra-/inter-node programming models, compiler, runtime systems and performance tools based on OpenMP, MPI and LLVM compiler, explore conventional and advanced computer architectures including CPU, vector, GPU, MIC, FPGA, and dataflow system, and support applications ranging from classical HPC, to big data analysis and machine learning, and to computer imaging. The ongoing development can be found from https://github.com/passlab. Dr. Yan received his PhD degree in computer science from University of Houston, has a bachelor degree in mechanical engineering, and loves physics and electric engineering as well. Apart from all those, he enjoys playing sports, fishing, writing science fictions, and playing with kids.
• Mar. 03 2017
  • Speaker: Lannan (Lisa) Luo
  • Affiliation: The Pennsylvania State University
  • Location: 300 Main B101
  • Time: 10:30-11:45 AM
  • Title: Improving Software and Systems Security via Software Analysis
  • Abstract: As the digital brainpower of the IT revolution, software has become an important driving force of today?s economy as well as an indispensable element of personal life. Hence, the security of the software and systems becomes increasingly important. In this talk, I will present my work on analyzing and enhancing software and systems security, which applies rich and powerful software analysis methodologies. A particular emphasis is placed on two problems: automatically detecting software plagiarism and automatically discovering vulnerabilities in Android Framework. First, I will present CoP, a technique that can be applied to detect software plagiarism. Identifying similar code segments among programs is faced with a notorious challenge caused by code obfuscation and is even more difficult when the source code is unavailable. I will present how CoP addresses them. Then, I will present Centaur, a technique that applies symbolic execution to Android Framework aiming at discovering vulnerabilities and generating proof-of-concept exploits automatically. Android Framework is an integral and foundational part of the Android system, containing multiple million lines of code. Despite extensive work on Android, most of the existing tools are only capable of analyzing Android applications. There is a severe lack of techniques and tools for insecurity analysis of the underlying framework code in Android. Due to unique characteristics of Android Framework, many challenges are raised when conducting such program analysis as symbolic execution and taint analysis. I will show how we overcame these challenges and implemented the system for insecurity analysis of Android Framework. Finally, I will conclude the talk with a brief discussion on future research directions.
  • Bio: Lannan (Lisa) Luo is a Ph.D. candidate in the College of Information Sciences and Technology at The Pennsylvania State University, under the supervision of Prof. Peng Liu. She received her B.S. in Telecommunications Engineering from Xidian University, Xi?an, China in 2009, and M.S. in Communications and Information Systems from The University of Electronic Science and Technology of China in 2012. Her research interests are software and systems security. During her PhD study, she mainly works on the software piracy problem and mobile computing security. Her research work has been published in FSE (Best Paper Award nomination), ICSE, DSN, and TSE. She did an internship at Microsoft Research Asia in 2015. Find more about her here: http://www.personal.psu.edu/lzl144/.
• Mar. 06 2017 Bonus Seminar
  • Speaker: Yang Zhou
  • Affiliation: Georgia Institute of Technology
  • Location: SWGN 1A03 (Faculty Lounge)
  • Time: 10:30-11:45 AM
  • Title: Effective and Scalable Big Data Computing: Algorithms and Systems
  • Abstract: With continued advances in science and technology, digital data have grown at an astonishing rate in various domains and forms, such as business, geography, health, multimedia, network, text, and web data. Network data are also known as graph data, such as academic collaboration, biological, communication, electrical, social, and transportation networks. Such big graph data have huge potential to reveal hidden insights and promote innovation in many business, science, and engineering domains. The reality is that people are often overwhelmed with the flood of big graph data in terms of size, type, and complexity. In order to help people quickly discover interesting knowledge and make good decisions when faced with big graph data, my research is dedicated to developing a wide spectrum of comprehensive solutions that span algorithms, systems, and applications: (1) big graph data mining and learning algorithms; (2) big graph data processing systems; and (3) domain-specific graph analytics applications.
    In this talk, I will introduce problems, challenges, and solutions for collecting, processing, understanding, and learning big graph data with billions of vertices and edges. I will also discuss recent work for how to leverage algorithmic and systemic techniques to alleviate challenging bottlenecks in the development of advanced big graph data analytics tools in terms of both quality and scalability. I will conclude the talk by sketching interesting future directions for big data computing. More details can be found at: http://www.cc.gatech.edu/~yzhou86/
  • Bio: Dr. Yang Zhou received his Ph.D. degree in computer science at the Georgia Institute of Technology in December 2016. His primary research bridges several areas of big data algorithms and systems, including data mining, parallel and distributed computing, machine learning, database systems, and cloud computing, with a focus on the development of effective and scalable algorithms, systems, and applications that address the challenges of big data. He has also worked with researchers from diverse research fields, such as software engineering, storage systems, web services, and trust management, to build and deploy domain-driven knowledge discovery solutions that improve domain-specific system design, data management, and data analytics in real-world settings.
    His research efforts have led to 30 publications with 850 citations in top venues of data mining (SIGKDD, ICDM, TKDD, DMKD), database systems (VLDB), high performance computing (HPDC, SC), networking (JSAC), and software engineering (ISSTA). Some of his research results have been included in reading lists and taught in courses at universities worldwide. He has been selected among the 20 rising stars of the KDD community by Microsoft Academic Search and Microsoft Research Asia in 2016. He has been serving as the reviewer of DMKD, JPDC, Machine Learning, TDSC, TKDD, TOIT, TSC, TWEB, and WWWJ.
• Mar. 08 2017
  • Speaker: Chien-Ming Huang Bonus Seminar
  • Affiliation: Yale University
  • Location: SWGN 1A03 (Faculty Lounge)
  • Time: 9:30 - 10:45 AM
  • Title: Building Socially Cooperative Human-Robot Teams
  • Abstract: Robots hold promise in assisting people in a variety of domains including healthcare services, household chores, collaborative manufacturing, and educational learning. In supporting these activities, robots need to engage with humans in socially cooperative interactions in which they work together toward a common goal in a socially intuitive manner. Such interactions require robots to coordinate actions, predict task intent, direct attention, and convey relevant information to human partners. In this talk, I will present how techniques in human-computer interaction, artificial intelligence, and robotics can be applied in a principled manner to create and study socially cooperative interactions between humans and robots. I will demonstrate social, cognitive, and task benefits of effective human-robot teams in various application contexts. I will also describe my current research that focuses on building socially cooperative robots to facilitate behavioral intervention for children with autism spectrum disorders (ASD). I will discuss broader impacts of my research, as well as future directions of my research program to develop personalized social technologies.
  • Bio: Chien-Ming Huang is a Postdoctoral Associate in the Department of Computer Science at Yale University, leading the NSF Expedition project on Socially Assistive Robotics. Dr. Huang received his Ph.D. in Computer Science at the University of Wisconsin?Madison in 2015, his M.S. in Computer Science at the Georgia Institute of Technology in 2010, and his B.S. in Computer Science at National Chiao Tung University in Taiwan in 2006. Dr. Huang?s research has been published at selective conferences such as HRI (Human-Robot Interaction) and RSS (Robotics: Science and Systems). His research has also been awarded a Best Paper Runner-Up at RSS 2013 and has received media coverage from MIT Technology Review, Tech Insider, and Science Nation. In 2016, Dr. Huang was invited to give an RSS early career spotlight talk at AAAI.
• Mar. 10 2017 Bonus Semina
  • Speaker: Erkan Kayacan
  • Affiliation: University of Illinois at Urbana-Champaign
  • Location: SWGN SWGN 1A03 (Faculty Lounge)
  • Time: 1:00 - 2:00 PM
  • Title: Fast Optimization-Based Control & Estimation Methods for Complex Mechatronic Systems: Applications in Guidance and Navigation of Autonomous Vehicles
  • Abstract: Nowadays, the complexity in design of systems increases enormously due to the fact that human beings desire intelligence and autonomy in systems, such as complex mechatronic systems. These systems are described as fast, large-scale, distributed and interconnected, and the challenge is to have adaptability to maintain reliability even in highly uncertain environment. Traditional controllers have important limitations: 1) inability to tune optimally the coefficients of controllers due to the complex nature and the vaguely known dynamics 2) inability to be able to adapt the control parameters considering changing system parameters and varying environmental conditions 3) inability to deal with constraints on systems 4) not account interactions between subsystems. These drawbacks of traditional control algorithms result in suboptimal control performance of systems. Therefore, advanced techniques are required to deal with naturally constrained, nonlinear, and multi-input-multi-output systems. In this talk, nonlinear model predictive control (NMPC) and nonlinear moving horizon estimation (NMHE), which are computationally very intensive, and require the real-time solution, will be addressed to handle aforementioned problems and their applications in unmanned ground vehicles will be shown.
  • Bio: Erkan Kayacan received the B.Sc. and M.Sc. degrees in mechanical engineering from Istanbul Technical University, Turkey, in 2008 and 2010, respectively. In December 2014, he received the Ph.D. degree at University of Leuven (KU Leuven), Belgium. During his PhD, he held a visitor PhD scholar position at Boston University for 5 months under supervision of Prof. Calin Belta. After his Ph.D., he became a Postdoctoral Researcher with Delft Center for Systems and Control (DCSC), Delft University of Technology, The Netherlands. He is currently a Postdoctoral Researcher at University of Illinois at Urbana-Champaign under supervision of Assist. Prof. Girish Chowdhary. His research interests include control systems and applications in unmanned vehicles, robotics and mechatronics.
• Mar. 13 2017
  • Speaker: William Harrison Bonus Seminar
  • Affiliation: University of Missouri
  • Location: SWGN 1A03 (Faculty Lounge)
  • Time: 10:30 - 11:30 AM
  • Title: Why Functional Hardware Description Matters
  • Abstract: There is no such thing as high assurance without high assurance hardware. High assurance hardware is essential, because any and all high assurance systems ultimately depend on hardware that conforms to, and does not undermine, critical system properties and invariants. And yet, high assurance hardware development is stymied by the conceptual gap between formal methods and hardware description languages used by engineers.
    This talk presents ReWire, a functional programming language providing a suitable foundation for formal verification of hardware designs, and a compiler for that language that translates high-level designs directly into working hardware. ReWire is a subset of the Haskell language (i.e., every ReWire program is a Haskell program) that can be translated automatically to synthesizable VHDL. Furthermore, ReWire programs can be verified as one would any functional program ? e.g., with equational reasoning in Coq ? but they may also be rendered as efficient circuitry by the ReWire compiler. We describe the design and implementation of ReWire as well as its application to the construction and verification of secure hardware artifacts.
  • Bio: Dr. William Harrison received his BA in Mathematics from Berkeley in 1986 and his doctorate from the University of Illinois at Urbana-Champaign in 2001 in Computer Science. From 2000-2003, he was a post-doctoral research associate at the Oregon Graduate Institute in Portland, Oregon where he was a member of the Programatica project. Dr. Harrison is an associate professor in the Computer Science department at the University of Missouri, where he has been since 2003. In December 2007, he received the CAREER award from the National Science Foundation's CyberTrust program. In 2013, Dr Harrison spent a sabbatical year at the National Security Agency's research directorate. His interests include all aspects of programming languages research (e.g., language-based computer security, semantics, design and implementation), reconfigurable computing, formal methods and malware analysis.
• Mar. 13 2017 Bonus Seminar
  • Speaker: Kostas J. Kyriakopoulos
  • Affiliation: National Technical University of Athens
  • Location: SWGN 1A03 (Faculty Lounge)
  • Time: 1:00 - 2:00 PM
  • Title: Towards Persistent Autonomy of Underwater Robotic Vehicles: Robust Control Strategies for Efficient Positioning and Interaction
  • Abstract: An important prerequisite for Persistent Autonomy of Unmanned Underwater Vehicles (UUVs) is advanced, platform – level, motion planning control to efficiently handle most of the UUV platform-level motion issues in such a way as to allow motion be perceived from higher levels (Learning, Task Planning etc.) as a simple modality. At the same time the sought control scheme should handle complex task missions and be robust enough to parameter uncertainties and disturbances due to real sea conditions. In order to handle UUV specific needs such as limited energy and computational resources dictating low complexity motion control, model-free position and image based visual serving schemes are presented. They do not require vehicle parameters but guarantee transient and steady state, performance despite external disturbances. We proceed with a Vision-based Nonlinear Model Predictive Control scheme using a self-triggering mechanism to provide the next control update requiring a significantly smaller number of measurements from vision and less frequent computations of the control law, thus reducing processing time and energy consumption. Complex real-time tasks, such as inspection and surveillance, often require high pitch angle configurations that may cause divergence of the navigation filters due to acoustic sensor limitations (DVL). Thus we propose visual servo control for UUV navigation and stabilization relative to an unknown visual target while achieving high pitch and yaw. In the case of autonomous surveillance at low visibility, multi-beam imaging sonars replace vision and model-based sonar servo control is adopted. The proposed controller is robust to UUV external disturbances and parametric uncertainties. Inspection and surveillance can be enhanced when employing multiple cooperating UUVs. Results on energy efficient coordinated motion control of multi-agent UUVs is presented. In addition to free motion (e.g. inspection/surveillance), underwater missions often require a level of interaction (e.g. valve/lever manipulation, tool grasping/carrying etc.) that can be accomplished by Underwater Vehicle Manipulation Systems (UVMS). If a certain performance criterion is adopted (e.g. optimal configuration of the end-effector according to the required task) a motion control algorithm is developed for UVMS optimal pose configuration to efficiently interact with the environment. The first part of presentation is concluded with immediate future directions towards cooperative motion and (physical) interaction control of multi-agent UVMS. In the second part, a brief overview of our parallel research activities will be presented in areas such as:
    - Multi-agent Systems: "Distributed multi-agent provable cooperation in both continuous and discrete domains"
    - Aerial Robotics: Dynamic Flights in Dynamic Environments.
    - Neuro-Robotics: From Brain Machine Interfaces to Human Robot Interaction Applications
    We conclude our talk with a brief overview of our future research plans on:
    - Robotics on Advanced Manufacturing, and
    - Dependable Autonomous Systems (focus on Public Safety)
    
  • Bio: Kostas J. Kyriakopoulos received a Diploma in Mechanical Eng. (Honors) from NTUA (1985) and the MS (1987) and Ph.D (1991) in Electrical, Computer and Systems Eng. (ECSE) from Rensselaer Polytechnic Institute (RPI), Troy, NY. Between 1988-91 he did research at the NASA Center for Intelligent Robotic Systems for Space Exploration. Between 1991-93 he was an Assist. Prof. at ECSE - RPI and the NY State Center for Advanced Technology in Automation and Robotics. Since 1994 he has been with the Control Systems Laboratory (CSL) of the Mechanical Eng. Dept. at NTUA, where he served as Professor and Director of: (i) the Mechanical Design and Control Systems Division (ii) CSL (http://www.controlsystemslab.gr/index/), (iii) the Departmental Computation Lab while currently serves as Director of the Master’s Program on Automation Systems. His current interests are in the area of Embedded Control Systems applications in multi-Robot Autonomous Systems (Mobile, Underwater and Aerial Vehicles / Manipulators). He has been awarded a number of fellowships including the Alexander Von Humboldt Foundation Fellowship. He has published ~300 papers to journals and fully refereed international conferences. He has contributed to 34 projects funded by the EC and Greek Sources with a total budget of ~6M€. He served in the editorial committees of a number of IEEE publications and in the high-level administrative committees of a number of international conferences. He was recently elevated to the Fellow grade of IEEE. (http://users.ntua.gr/kkyria)
• Mar. 17 2017
  • Speaker: Shuai Li
  • Affiliation: Hong Kong Polytechnic University
  • Location: SWGN 1A03 Faculty Lounge
  • Time: 9:30 - 10:30 AM
  • Title: Model-based Neural Networks for Robot Control
  • Abstract: With the advances of mechanics, electronics, computer engineering, using autonomous robots, or a collection of them, to perform various tasks is becoming increasingly popular in both industry and our daily lives. Control plays an important role for stable and accurate task execution while learning is outstanding in dealing with unknowns or uncertainties. Recent advances in machine learning provide us with an opportunity to employ innovative learning structures for efficient adaptation. However, it remains challenging on how to efficiently integrate learning with control efficiently to reach provable and guaranteed stability even in the worst case. This talk will present our recent results along this research direction.
  • Bio: Shuai Li received the B.E. degree in electrical engineering from the Hefei University of Technology, Hefei, China, in 2005, the M.E. degree in control engineering from the University of Science and Technology of China, Hefei, in 2008, and the Ph.D. degree in electrical and computer engineering from the Stevens Institute of Technology, Hoboken, NJ, USA, in 2014. He joined Hong Kong Polytechnic University after graduation and directed his group to do research in robotics, cyber physical systems, intelligent control, etc. Dr. Li is an associate editor of the International Journal of Advanced Robotic Systems, Frontiers in Neurorobotics, and Neural Processing Letters.
• Mar. 20 2017 Bonus Seminar
  • Speaker:Dr. Truong Nghiem
  • Affiliation: Laboratoire d Automatique, Lausanne Switzerland
  • Location: SWGN 3D05
  • Time: 9:00 - 10:00 AM
  • Title:Control Meets Machine Learning: Balancing the Grid with Commercial Buildings
  • Abstract: Recent political and societal developments are leading to the deregulation of energy markets and the increasing shift from predictable and dispatchable power generation to variable and non-dispatchable generation such as renewables. Together with growing power demand, these radical changes are placing more stress on power networks and increasing significantly the uncertainty and volatility in electric grids and energy markets. In view of these developments, it has become crucial to make power grids resilient to uncertainty and volatility by introducing more controllable flexibility in both supply and demand. This is achieved through grid balancing services such as demand response and ancillary services.
    Commercial buildings consume about 37% of total electricity end use in the United States. They also possess a high level of controllable flexibility in electricity consumption and a strong incentive to save energy cost. In this talk, I will first argue for using commercial buildings to provide grid balancing services, followed by a discussion of current approaches and their drawbacks, particularly their high cost barrier to practical implementation. The second part of the talk will present a new approach that leverages Gaussian Processes (GP) – a machine learning technique – for significantly reducing the cost of deployment, and optimization-based control for effective provision of grid balancing services with commercial buildings. The proposed approach defines a simple protocol for safely altering the electricity consumption of a building, which can be implemented easily in existing Building Management Systems. I will show how the controller adapts to data online and maintains operational constraints with high probability by exploiting the non-parametric nature and the inherent ability to describe prediction uncertainty of GP. Simulations with the high-fidelity building simulator EnergyPlus and an experiment with data from a real building confirm the effectiveness of the approach. Finally, I will discuss my future research plan to develop design and analysis methodologies for closed-loop control systems with GP modeling, as well as algorithms, implementation, and experiments for their practical applications in Smart Grid and other domains.
  • Bio: Truong X. Nghiem is a postdoctoral scientist in the Automatic Control Laboratory at EPFL (Switzerland). Before this, he was a postdoctoral researcher at the University of Pennsylvania, where he received his Ph.D. degree in Electrical and Systems Engineering in 2012. During his graduate study at Penn, he was a member of the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory and the Energy-efficient Buildings (EEB) Hub of the U.S. Department of Energy. He is interested in integrating control, optimization, machine learning, and computation to address fundamental Cyber-Physical System challenges across various domains, with a focus on energy systems including smart buildings and smart grid.
• Mar. 20 2017 Bonus Seminar
  • Speaker: Sherif Abdelwahed
  • Affiliation: Mississippi State University
  • Location: SWGN faculty lounge
  • Time: 10:30 - 11:30 AM
  • Title:
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• Mar. 23 2017 Bonus Seminar
  • Speaker: Damindra Bandara
  • Affiliation: George Mason University
  • Location: 300 Main, B110
  • Time: 3:00 - 4:00 PM
  • Title:
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• Mar. 24 2017
  • Speaker: Xuequing Huang
  • Affiliation: New Jersey Institute of Technology
  • Location: SWGN 1A03 Faculty Lounge
  • Time: 9:30 - 10:30 AM
  • Title:
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• Mar. 27 2017 Bonus Seminar
  • Speaker: Selcuk Uluagac
  • Affiliation: Florida International University
  • Location: SWGN 1A03 Faculty Lounge
  • Time: 10:30 - 11:30 PM
  • Title:
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• Mar. 31 2017
  • Speaker: Yoris Au
  • Affiliation: The University of Texas at San Antonio
  • Location: SWGN 1A03 Faculty Lounge
  • Time: 1:30 - 2:30 PM
  • Title:Observational Learning in a Competitive Two-Sided Crowdsourcing Market: A Bayesian Inferential Approach
  • Abstract: This study investigates the effect of observational learning in the crowdsourcing market as an attempt to identify appropriate mechanism(s) for sustaining this increasingly popular business model. Observational learning occurs when crowdsourcing participating agents obtain knowledge from signals they observe in the marketplace and incorporate such knowledge into subsequent actions to improve their participation outcomes. This form of learning is examined in the context of the two-sided crowdsourcing platform in which participating customers’ and professionals’ decisions interact with and influence each other. Two structural models are constructed to capture customer and professional’s probability of success in the presence of various constantly changing market signals. A third model is developed to capture factors that influence market outcomes such as level of participation by professionals. These models will be estimated using the Bayesian approach on a longitudinal dataset that consists of seven years of transaction data in four product categories from a leading crowdsourcing site. We expect to observe learning effect in this crowdsourcing market and to identify various factors that influence the probability of a professional (agent) submitting a bid to a crowdsourcing project and the probability of a customer (principal) selecting a winner through observational learning.
  • Bio: Dr. Yoris Au joined the University of Texas at San Antonio (UTSA) in Fall 2003 from the PhD Program in Information and Decision Sciences from the University of Minnesota. Dr. Au has 12 peer reviewed journal publications. He was the Co-PI for a $300,000 grant from the UT System for the design and development of an online BBA in Cyber Security. Much of Dr. Au’s research is on the economics of information systems. He is also working on web application security and cloud computing security, and cyber security information sharing issues. He has served as chair of the department of Information Systems and Cyber Security since Fall 2013.
• Apr. 07 2017
  • Speaker: Roy Clark
  • Affiliation: (Non-USC)
  • Location: SWGN 2A31
  • Time: 2:20 - 3:10 PM
  • Title: The Role and Examples of an Advanced Technology Group
  • Abstract: When development organizations are heads-down developing the next product release, who looks towards the horizon for new product ideas and enabling technologies? An Advanced Technology group fills this role. Deciding which technologies are relevant, evaluating them for specific usage models, prototyping, tracking competing approaches, suggesting and engaging in merger and acquisition discussions and internal selling are a few dimensions of an Advanced Technology group. This talk will discuss these and more as it pertained to an Advanced Technology group within EMC. EMC, now part of Dell Technologies, is the industry-leading provider of storage and converged infrastructure solutions.
  • Bio: Roy Clark, is a retired Distinguish Engineer from DellEMC. He was a technical leader in an Advanced Technology Group for the Unified Storage Division. His responsibilities included leading a small team in conducting forward-looking research activities in support of defining and analyzing system-level architecture tradeoffs and technology tradeoffs across all of EMC’s storage platforms. He focused on overall caching, file systems, distributed systems, processor technology, flash technology and performance. He also drove storage platform requirements to the Intel processor architects and technologists so they could meet the performance requirements of EMC platform architectures including Celera, Centera, CLARiiON, and Symmetrix. Clark’s areas of expertise include the development of system architectures, control structures, and high-performance cache-coherent memory hierarchies. Specifically, he has designed and delivered several IBM-mainframe-compatible systems, RISC-based symmetric multiprocessing UNIX systems, high-end NUMA-based UNIX systems, and NAS-based storage systems. Clark joined Data General in 1994, which was later acquired by EMC. Prior to joining EMC, he held various positions at Amdahl Corporation, Magnuson Computers, NCR, Pyramid Technology, and Trilogy. Clark holds a B.S. in Electrical Engineering from Purdue University and has been recognized as a Fellow at Data General, and as a Chief Scientist at Pyramid Technology. He has received 64 patent awards and has several pending applications.
• Apr. 14 2017
  • Speaker: TBD
  • Affiliation: TBD
  • Location: SWGN 2A31
  • Time: 2:20 - 3:10 PM
  • Title: TBD
  • Abstract: TBD
  • Bio: TBD
• Apr. 21 2017
  • Speaker: TBD
  • Affiliation: TBD
  • Location: SWGN 2A31
  • Time: 2:20 - 3:10 PM
  • Title: TBD
  • Abstract: TBD
  • Bio: TBD