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X-ORIGINAL-URL:https://isg.ics.uci.edu
X-WR-CALDESC:Events for Information Systems Group
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DTSTART;TZID=America/Los_Angeles:20200110T110000
DTEND;TZID=America/Los_Angeles:20200110T120000
DTSTAMP:20261108T022015
CREATED:20191122T030338Z
LAST-MODIFIED:20200108T194010Z
UID:1232-1578654000-1578657600@isg.ics.uci.edu
SUMMARY:Scalable Programming: Progress\, Prospects and Challenges (CS/NetSys Seminar)
DESCRIPTION:Speaker:  Prof. Gul Agha (University of Illinois at Urbana-Champaign) \nAbstract:\nMobile cloud computing\, social media\, cyberphysical systems\, and the internet of things\, are examples of increasingly important applications requiring scalable concurrency.  The Actor model facilitates programming large-scale concurrent applications.  Not surprisingly\, Actor languages and frameworks have been widely adopted in industry to address scalability.  Although this has significantly reduced programming errors\, developing complex concurrent systems and reasoning about their properties can nevertheless be challenging and error-prone.  A key source of complexity is the interactions between actors.  I will describe our work in programming languages defining new constructs to address this complexity.  Specifically\, we have developed ways of expressing multiparty session types and synchronization constraints which capture interactions.  I will then briefly discuss three promising techniques to formally reason about Actor systems.  First\, inferring the concurrency structure of an actor program can facilitate targeted test generation.  Second\, predictive runtime verification can flag safety violations in future potential executions.  Finally\, statistical methods can improve confidence that a system obeys certain probabilistic properties.  I will conclude by discussing open problems and promising research directions. \nBio:\nDr. Gul Agha is Professor Emeritus of Computer Science at the University of Illinois at Urbana-Champaign and Interim CEO of Embedor Technologies.  Dr. Agha is a Fellow of the ACM and of the IEEE\, and a recipient the 2019 ACM Sigsoft Impact Paper Award.  He has served as Editor-in-Chief of IEEE Concurrency: Parallel\, Distributed and Mobile Computing\, and of ACM Computing Surveys.  Dr. Agha is best known for his formalization of the Actor model\, used in languages and frameworks such as Erlang\, Scala/Akka\, and Orleans\, and to develop scalable applications such as Twitter\, LinkedIn\, and Facebook Chat.  Dr. Agha’s other contributions include development of Statistical Model Checking\, which has applications in biological systems and cyberphysical systems among others; Concolic Testing for programs with dynamic memory and concurrency\, a method incorporated in industrial software testing tools such as KLEE\, Microsoft SAGE\, and S2E; Euclidean model checking for reasoning about the evolution of probability distributions and for synthesizing controllers; the application of computational learning to program verification; logical methods for automated decentralized\, predictive runtime verification; and distributed algorithms for wireless sensor networks(WSNs).  Dr. Agha co-founded Embedor Technologies which is applying WSNs to continually monitor the structural health of bridges\, buildings and large machinery.  For example\, Embedor’s technology was used to monitor the world largest Ferris wheel during construction\, and will be used to continuously monitor it during operation.
URL:https://isg.ics.uci.edu/event/personalization-of-pervasive-autonomy-applications-and-system-support/
LOCATION:DBH 6011
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20200124T150000
DTEND;TZID=America/Los_Angeles:20200124T160000
DTSTAMP:20261108T022015
CREATED:20200121T095342Z
LAST-MODIFIED:20200124T182021Z
UID:1265-1579878000-1579881600@isg.ics.uci.edu
SUMMARY:LSM-based storage techniques: a tutorial
DESCRIPTION:Speaker: Chen Luo \nAbstract: Recently\, the log-structured merge-tree (LSM-tree) has been widely adopted for use in the storage layer of modern NoSQL systems. Because of this\, there have been a large number of research efforts\, from both the database community and the operating systems community\, that try to improve various aspects of LSM-trees. In this tutorial\, I will describe the basics of LSM-tree storage techniques as well as exploring their design space and performance trade-offs. If time permits\, I will also survey some representative work on optimizing LSM-trees.
URL:https://isg.ics.uci.edu/event/lsm-based-storage-techniques-a-tutorial/
LOCATION:CA
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20200130T140000
DTEND;TZID=America/Los_Angeles:20200130T180000
DTSTAMP:20261108T022015
CREATED:20200130T181101Z
LAST-MODIFIED:20200130T181101Z
UID:1270-1580392800-1580407200@isg.ics.uci.edu
SUMMARY:A Theoretical View of Distributed Systems (CS Distinguished Seminar Series)
DESCRIPTION:Speaker: Prof. Nancy Lynch (Massachusetts Institute of Technology) \nAbstract: For several decades\, my collaborators\, students\, and I have worked on theory for distributed systems\, in order to understand their capabilities and limitations in a rigorous\, mathematical way. This work has produced many different kinds of results\, including: \n    Abstract models for problems that are solved by distributed systems\, and for the algorithms used to\n    solve them\,\n    Rigorous proofs of algorithm correctness and performance properties (also some error discoveries)\,\n    Impossibility results and lower bounds\, expressing inherent limitations of distributed systems\,\n    Some new algorithms\, and\n    General mathematical foundations for modeling and analyzing distributed systems. \nThese various results have spanned many different kinds of systems\, ranging from distributed data-management systems\, to communication systems\, to biological systems such as insect colonies and brains. \nIn this talk\, I will overview some highlights of our work over many years on theory for distributed systems. I will break this down in terms of three intertwined “research threads”: algorithms for traditional distributed systems\, impossibility results\, and mathematical foundations. At the end\, I will say something about our recent work on algorithms for new kinds of distributed systems. \nBio: Nancy Lynch is the NEC Professor of Software Science and Engineering in MIT’s EECS department. She heads the Theory of Distributed Systems research group in the Computer Science and AI Laboratory. She received her PhD from MIT and her BS from Brooklyn College\, both in Mathematics. \nLynch has (co-)written many research articles about distributed algorithms and impossibility results\, and about formal modeling and verification of distributed systems. Her best-known contributions are the “FLP’’ impossibility result for reaching consensus in asynchronous distributed systems in the presence of failures\, with Fischer and Paterson\, and a paper with Dwork and Stockmeyer on algorithms for reaching consensus under restricted failure assumptions. Other contributions include the I/O automata system modeling frameworks\, with Tuttle\, Kaynar\, Segala\, and Vaandrager. \nLynch is the author of the textbook “Distributed Algorithms” and co-author of “The Theory of Timed I/O Automata” and “Atomic Transactions”. She is an ACM Fellow\, a member of the National Academy of Engineering and the National Academy of Sciences\, and a Fellow of the American Academy of Arts and Sciences. She has been awarded the Dijkstra Prize (twice)\, the van Wijngaarden Award\, the Knuth Prize\, the Piore Award\, the Athena Award\, and the IEEE Technical Committee on Distributed Processing Outstanding Achievement award. She has supervised approximately 100 PhD students\, Masters students\, and postdocs. \nLynch is interested in all aspects of distributed computing theory\, including modeling\, algorithm design and analysis\, lower bounds\, and applications. She is especially interested in algorithms for “difficult” platforms\, which are subject to noise\, failures\, and changes. Recently\, her work has focused on wireless network algorithms\, biological distributed algorithms\, and the connections between them.
URL:https://isg.ics.uci.edu/event/a-theoretical-view-of-distributed-systems-cs-distinguished-seminar-series/
LOCATION:DBH 6011
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20200131T150000
DTEND;TZID=America/Los_Angeles:20200131T160000
DTSTAMP:20261108T022015
CREATED:20200113T213640Z
LAST-MODIFIED:20200121T095512Z
UID:1260-1580482800-1580486400@isg.ics.uci.edu
SUMMARY:Building Personal Chronicle of Life Events (Final Defense)
DESCRIPTION:Speaker: Jordan Oh \nAbstract:\nHuman beings have always been interested in understanding themselves and their surroundings. Learning about the relationship between the two can reveal facts of the present and help predict the future\, a critical part to live a better life. With the proliferation of IoT sensor devices\, it is now possible to collect quality data for each individual and utilize this data for building personal models that can help to understand the self and environment. However\, since this sensor data have different granularities and semantics\, the semantic gap becomes even more formidable. Thus\, there are challenges in aggregating\, integrating\, and synchronizing this heterogeneous data to a form such that it effectively describes the life experiences of each individual. In this dissertation\, we design a personal chronicle\, which contributes a solution to the aforementioned challenges\, called Personicle\, in which all kinds of personal data streams can be correlated with one another to form a model of a person.  \nTo implement the Personicle\, we first attempt to bridge the semantic gap between the low-level multimedia logs and high-level semantics by developing a common daily event model through the data unobtrusively obtained from smart devices. To do this\, we define an atomic interval\, which brings together the scattered sources of heterogeneous data to partition the data into manageable pieces. This atomic interval lets us segment a day into sequences of similar patterns and use the segments for daily event recognition.  \nSecondly\, we design an event-triggered Ecological Momentary Assessment (EMA) to maximize the chance of aggregating the semantic data from the users. Unlike the traditional EMA process\, which mainly depends on user initiative and intervention\, we contribute to overcoming the problems endemic to persistent data collection\, such as missing a logging moment or early abandonment\, by initiating the EMA process from the system side at the right moment.  \nLastly\, we propose a fully-automated approach to obtain latent semantic information from all the integrated data aiming to maximize the opportunity of both qualitatively and quantitatively capturing one’s life experiences. To show a concrete example of this enrichment\, we perform an experiment with “Eating” and “Working”\, a complex event central to human experiences. These enhanced daily events can then be used to create a personal model that could capture how a person reacts to different stimuli under specific conditions.   \nBio:\nHyungik Oh is a Ph.D. Candidate at UC Irvine. His research interests are lifelogging\, activity/event recognition and applied machine learning. He is currently working on pioneering research called Personicle in which he builds a personal chronicle of life events by aggregating\, integrating\, and synchronizing heterogeneous sensor data streams.
URL:https://isg.ics.uci.edu/event/final-defense-jordan-oh/
LOCATION:CA
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