SUNMONTUEWEDTHUFRISAT
Conferences, Lectures, & Seminars
Events for September
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar
Wed, Sep 04, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Gaurav Gupta, Electrical & Computer Engineering, University of Southern California
Talk Title: Dealing with Unknown Unknowns: Compact Perception from Heterogeneous Data
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: Deciphering patterns from heterogeneous and noisy data to make robust inferences require knowledge of the complete system. Even with big data sizes, the presence of unknown unknowns (contributors) may not be neglected due to complex interactions of the observed system with the unobserved components and the environment (e.g., brain, social networks, gene-regulatory networks, physiological signals). In this talk, we will discuss the incorporation of unknown unknowns in the context of non-stationary non-Markovian processes. A multi-scale approach is used to model the non-Markovian time-dependence of the complex network nodes. The behavior is modeled using fractional differential equations. The benefits of this approach are demonstrated by modeling the real-world biological data of brain electroencephalogram (EEG), neuron spikes, and physiological signals like temperature and heartbeat intervals while considering the prediction of brain state or the prediction of viral infection. We will also describe how a compact model can be efficiently used to tackle some practical problems in brain machine interfaces and viral prediction in a different perspective than the traditional machine learning approaches.
Biography: Gaurav Gupta is a Ph.D. student working under the supervision of Prof. Paul Bogdan in the Ming Hsieh Department of Electrical and Computer Engineering at University of Southern California. He received his B.Tech degree from Indian Institute of Technology Kanpur in 2013 and M.S. from University of California Irvine in 2016, both in Electrical Engineering. His research interests include modeling of complex networks in the presence of unknown unknowns, discrete optimization, information theory for machine and representation learning, network inference for biological and social networks and the science biological computation.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Sep 06, 2019 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Borivoje NikoliÄ, Professor, University of California at Berkeley
Talk Title: Generating the Next Wave of Custom Silicon
Host: Profs. Hossein Hashemi, Mike Chen, Dina El-Damak, and Mahta Moghaddam
More Information: MHI Seminar Series IS - Borivoje Nikolic.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Jenny Lin
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Fall 2019 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Sep 09, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Kimon Drakopoulos, University of Southern California
Talk Title: Misinformation in platforms: Persuasion and inundation
Abstract: In the first part of the talk, we study information design in social networks. We consider a setting, where agents actions exhibit positive local network externalities. There is uncertainty about the underlying state of the world, which impacts agents payoffs. The platform can choose a signaling mechanism that sends informative signals to agents upon realization of this uncertainty, thereby influencing their actions. We investigate how the platform should design its signaling mechanism to achieve a desired outcome.. We find that in the case where the platform seeks only to minimize misinformation (regardless of the induced engagement), common threshold mechanisms with identical thresholds across agents are optimal. This is in contrast to the engagement maximization setting, where when agents are heterogeneous in terms of their network positions, common threshold mechanisms induce substantially lower engagement than the optimal mechanisms. We also study the frontier of the engagement/misinformation levels that can be achieved via different mechanisms and characterize when common threshold mechanisms achieve optimal tradeoffs.
In the second part of the talk, we study a model of information consumption where consumers sequentially interact with a platform that offers a menu of signals (posts) about an underlying state of the world (fact). At each time, incapable of consuming all posts, consumers screen the posts and only select (and consume) one from the offered menu. We show that in the presence of uncertainty about the accuracy of these posts, and as the number of posts increases, adverse effects such as slow learning and polarization arise. Specifically, we establish that, in this setting, bias emerges as a consequence of the consumer screening process. Namely, consumers, in their quest to choose the post that reduces their uncertainty about the state of the world, choose to consume the post that is closest to their own beliefs. We study the evolution of beliefs and we show that such a screening bias slows down the learning process, and the speed of learning decreases with the menu size. Further, we show that the society becomes polarized during the prolonged learning process even in situations where the society belief distribution was not a priori polarized.
Biography: Kimon Drakopoulos is an Assistant Professor of Operations Management at the Marshall School of Business, University of Southern California. His research focuses on the operations of complex networked systems, social networks, stochastic modeling, game theory and information economics. Kimon, prior to joining USC, completed his PhD at the Laboratory for Information and Decision systems at MIT focusing on the analysis and control of contagion processes on networks.
Host: Ketan Savla, ksavla@usc.edu
More Info: http://csc.usc.edu/seminars/2019Fall/drakopoulos.html
More Information: 190905 Kimon Drakopoulos CSCUSC Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2019Fall/drakopoulos.html
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Integrating Blockchain & Big Data
Mon, Sep 09, 2019 @ 07:00 PM - 10:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Wyatt Meldman-Floch, Constellation Labs
Talk Title: Integrating Blockchain & Big Data
Abstract: The main limitation to traditional linear blockchain technology is scalability. Most approaches to scalability improvements utilize L2 solutions such as sharding or partitioning. However, a limitation of these L2 approaches is a lack of resilience to node failures due to the stateful nature of blockchain protocols. Backend systems that can dynamically adapt to changes in throughput or outright resource failure are know as elastic infrastructure, which are a core feature of most tools for large scale data processing. In order to achieve native integration with traditional backend systems, stateful P2P networks need elastic infrastructure. MEME, an online machine learning model created at Constellation Labs was created to address elasticity in stateful peer to peer networks such as blockchain protocols and cryptocurrencies associated to them. MEME is an ensamble model comprised of three known approaches to quantify performance and influence of a participant in P2P networks that can be incorporated with any proof model such as proof of work (PoW), proof of stake (PoS) or proof of reputable observation (PRO). The focus of this presentation is on elastic infrastructure and MEME, an approach for maintaining elasticity in blockchain/DAG clusters created and used by Constellation Labs.
Biography: Wyatt is the CTO and cofounder of Constellation Labs, where he developed an asynchronous DAG protocol to powering a decentralized data marketplace. He is a software engineer based in San Francisco with over six years of professional experience specializing in distributed systems and machine learning. Wyatt's career began at NASAs SETI Institute where he contributed to the Kepler project and implemented an entropy-based algorithm to detect intelligent (alien) communication. Prior to cofounding Constellation Labs, he served as a software engineer for Rally Health, Radius Intelligence and Zignal Labs, where he built scalable data processing pipelines for data mining, distributed graph based NLP models, and stream processing platforms for data enrichment at the Twitter firehose at scale.
Host: Bhaskar Krishnamachari, CCI
More Info: https://www.meetup.com/Hyperledger-Los-Angeles/events/264393286/
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: https://www.meetup.com/Hyperledger-Los-Angeles/events/264393286/
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar
Wed, Sep 11, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Professor Arun Kumar, Department of Computer Science & Engineering & Halicioglu Data Science Institute, University of California, San Diego
Talk Title: Democratizing Machine Learning-based Data Analytics
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: As machine learning (ML) permeates data-driven applications in enterprise, Web, and scientific domains, data management and systems bottlenecks in ML are proving increasingly critical. The overarching goal of my research is to mitigate such bottlenecks and improve the efficiency of ML systems and productivity of ML users, which in turn can help reduce costs and democratize ML-based analytics. Toward this grand goal, we are building abstractions, algorithms, and systems to improve the processes of sourcing and preparing data for ML, performing iterative ML model selection, and integrating ML models with data-driven applications.
In this talk, I will give an overview of our recent work on all these fronts, focusing specifically on a new direction that could transform how ML systems are built: multi-query optimization for ML. Drawing on the lessons of decades of work on query optimization in relational systems, I will talk about some of our recent work on connecting linear algebra, learning theory, and optimization theory with scalable system design and implementation to accelerate the model selection process in ML systems. Our approach is a step towards bridging the large gap between current ML system abstractions and the level at which ML users think, has implications for both statistical models and deep learning, and could lay a principled systems foundation for new AutoML frameworks.
Biography: Arun Kumar is an Assistant Professor in the Department of Computer Science and Engineering and Halicioglu Data Science Institute at the University of California, San Diego. He is a member of the Database Lab and Center for Networked Systems and an affiliate member of the AI Group. His primary research interests are in data management and systems for machine learning/artificial intelligence-based data analytics. Systems and ideas based on his research have been released as part of the MADlib open-source library, shipped as part of products from EMC, Oracle, Cloudera, and IBM, and used internally by Facebook, LogicBlox, Microsoft, and other companies. He is a recipient of two SIGMOD research paper awards in 2019 and 2014, three distinguished reviewer awards from SIGMOD/VLDB in 2019 and 2017, the 2016 PhD dissertation award from UW-Madison CS, a 2016 Google Faculty Research Award, a 2018 Hellman Fellowship. Research webpage: https://adalabucsd.github.io/
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Sep 13, 2019 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Hai Li, Associate Professor, Duke University
Talk Title: Highly Efficient Neuromorphic Computing Systems with Emerging Nonvolatile Memories
Host: Profs. Hossein Hashemi, Mike Chen, Dina El-Damak, and Mahta Moghaddam
More Information: MHI Seminar Series IS - Hai Li.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Jenny Lin
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Trajectory planning for manipulators performing complex tasks
Mon, Sep 16, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ariyan Kabir, Postdoctoral Research Associate at the Viterbi School of Engineering
Talk Title: Trajectory planning for manipulators performing complex tasks
Abstract: Recent advances in hardware capabilities, computation power, and control algorithms have physically enabled manipulators to perform highly complex tasks. Representative examples can be laundry folding, composite sheet layup, liquid pouring, mobile manipulation, surgery, etc. Using manipulators for complex tasks can significantly improve human productivity and eliminate the need for human involvement in tasks that pose risks to human safety. However, it is not feasible to manually program manipulators for complex tasks in high-mix low-volume applications, as it will take a significant amount of time, effort, and cost. We could use manipulators in complex tasks in high-mix low-volume applications if manipulators could plan their own trajectories. Trajectory planning for manipulators performing complex tasks is a problem with several different challenges. It requires avoiding obstacles present in the robot's workspace, assigning appropriate tasks to the degrees of freedoms in robotic systems, respecting the kinematic and dynamic limitations of the manipulators, and identifying the appropriate trajectory and process parameters for achieving the desired task performance. This talk will present algorithmic foundations to address the problem of trajectory planning for robotic systems. First, I will present a context-dependent search strategy-switching algorithm to navigate the discrete state-space search towards promising directions for point-to-point trajectory planning. Second, I will present a successive refinement strategy for path-constrained trajectory generation using non-linear parametric optimization with conflicting constraints. Finally, I will present an approach to integrate trajectory planning with task-agent assignment for carrying out complex operations with multiple robots.
Biography: Ariyan Kabir is interested in building smart robotic assistants by contributing at the intersection of artificial intelligence and robotics. His research focus is on motion planning and self-directed learning for high degrees of freedom systems. He is developing algorithms to find near-optimal solutions to computationally hard planning problems. He is currently working as a Postdoctoral Research Associate at the Viterbi School of Engineering, University of Southern California (USC). He completed his Ph.D. in Mechanical Engineering from USC in July 2019. He completed his B.Sc. in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology (BUET), Dhaka. Ariyan has won one best paper award, and two best poster awards from his research contributions.
Host: Ashutosh Nayyar, ashutosn@usc.edu
More Info: http://csc.usc.edu/seminars/2019Fall/kabir.html
More Information: 190916_Ariyan Kabir_CSC Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2019Fall/kabir.html
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar
Wed, Sep 18, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Georgios Bouloukakis, University of California, Irvine
Talk Title: Towards End-to-end Data Exchange in the IoT
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: To enable direct Internet connectivity of Things, complete protocol stacks need to be deployed on resource-constrained devices. Such protocol stacks typically build on lightweight IPv6 adaptations and may even include a middleware layer supporting high-level application development. However, the profusion of IoT middleware-layer interaction protocols has introduced technology diversity and high fragmentation in the IoT systems landscape with siloed vertical solutions. To enable the interconnection of heterogeneous Things across these barriers, advanced interoperability solutions are required.
In this talk, I will introduce a solution for the automated synthesis of protocol mediators that support the interconnection of heterogeneous Things. Our systematic approach relies on software architecture abstractions and model-driven development. I will also present our ongoing work for the automated placement and deployment of protocol mediators at the Edge of IoT spaces.
Biography: Georgios Bouloukakis is a postdoctoral researcher at the University of California, Irvine in the Distributed Systems Middleware group. His research mainly focuses on the design of extensible and efficient IoT systems by leveraging fundamental mathematical models and state-of-the-art technologies. Before joining UC Irvine, Georgios received a postdoctoral scholarship from the Inria@SiliconValley research program. He obtained his Ph.D. from the Pierre and Marie Curie University, conducting his thesis at the research center of Inria Paris in the MiMove team in France.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Talyia White
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Medical Imaging Seminar
Thu, Sep 26, 2019 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ye Tian, University of Utah
Talk Title: Radial Simultaneous Multi-slice MRI for Cardiac Perfusion Assessment
Series: Medical Imaging Seminar Series
Abstract: First-pass myocardial perfusion MRI is a powerful tool to detect and evaluate coronary artery disease. In this work, we use undersampled radial simultaneous multi-slice (SMS) acquisitions to achieve greater slice coverage and reduced sensitivity to motion, compared to current standard techniques. I will present two acquisition frameworks for myocardial perfusion. One that uses radial SMS and a pixel-tracking method to produce multi-view perfusion images. The other framework uses continuous acquisition without gating or magnetization preparation. This work employed patch-based locally low-rank constraints and temporal total variation constraints.
Biography: Ye Tian recently completed his Ph.D. at the University of Utah (2014 -“ 2019). He has been working in the cardiovascular MRI group of Utah Center of Advanced Imaging Researches (UCAIR) since May 2016 under the guidance of Edward DiBella and Ganesh Adluru. His interests include myocardial perfusion DCE-MRI, radial SMS, image reconstruction, fast imaging, and myocardial T1 mapping.
Host: Professor Krishna Nayak
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia White
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Fall 2019 Joint CSC@USC/CommNetS-MHI Seminar Series
Mon, Sep 30, 2019 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Eva Kanso, University of Southern California
Talk Title: Sea Star Inspired Crawling and Bouncing
Abstract: The oral surface of sea stars is lined with arrays of tube feet that enable them to achieve highly controlled locomotion on various terrains. The activity of the tube feet is orchestrated by a nerve net that is distributed throughout the body; there is no central brain. How such a decentralized nervous system produces a coordinated locomotion is yet to be understood. We developed mathematical models of the biomechanics of the tube feet and the sea star body. In the model, the feet are coupled mechanically through their structural connection to the sea star body. We formulated hierarchical control laws that capture salient features of the sea star nervous system. Namely, at the tube foot level, the power and recovery strokes follow a state-dependent feedback controller. At the system level, a directionality command is communicated through the ring and radial nerves to all tube feet. We studied the locomotion gaits afforded by this hierarchical control system. We found that these minimally-coupled tube feet coordinate to generate robust forward locomotion, reminiscent of the crawling motion of sea stars, on various terrains and under various heterogeneity in the tube feet parameters and initial conditions. Our model also predicted a transition from crawling to bouncing consistent with our experiments performed on Protoreaster nodosus. We conclude by commenting on the implications of these findings for understanding the Echinoderms decentralized nervous system and their potential application to autonomous robotic systems.
Biography: Eva Kanso is a professor, and the Zohrab H. Kaprielian Fellow, in Aerospace and Mechanical Engineering at the University of Southern California (USC). Prior to joining USC, Kanso held a two-year postdoctoral position in Computing and Mathematical Sciences at Caltech. She received her Ph.D. and M.S. degrees in Mechanical Engineering as well as an M.A. degree in Mathematics from UC Berkeley. She got her Bachelor of Engineering from the American University of Beirut with distinction. At USC, Kanso studies the physics of how organisms interact with their environments. Kanso combines methods from fluid and solid mechanics with techniques from dynamical systems and control theory to analyze the interplay between the morphology of living systems and the environment to produce biological functions.
Host: Urbashi Mitra, ubli@usc.edu
More Info: http://csc.usc.edu/seminars/2019Fall/kanso.html
More Information: 190930_Eva Kanso_CSC Seminar.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Brienne Moore
Event Link: http://csc.usc.edu/seminars/2019Fall/kanso.html
