Conferences, Lectures, & Seminars
Events for June
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Towards Smarter Hardware Prediction Mechanisms
Fri, Jun 01, 2018 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Akanksha Jain, University of Texas at Austin
Talk Title: Towards Smarter Hardware Prediction Mechanisms
Abstract: In today's data-driven world, memory system performance remains critical to the overall performance of many workloads. In this talk, we present recent work in two aspects of hardware caching: (1) The Hawkeye Cache (ISCA 2016), which introduces a novel method of solving the age-old problem of cache replacement, and (2) Harmony, which uncovers a new design space for cache replacement policies in the presence of prefetching (ISCA 2018). We will then briefly discuss ways that machine learning can help us improve upon these ideas, and we conclude by discussing the broader role machine learning can play in advancing memory system research.
Biography: Akanksha Jain received her PhD in Computer Science from The University of Texas in December 2016. In 2009, she received the B.Tech and M. Tech degrees in Computer Science and Engineering from the Indian Institute of Technology Madras. Her research interests are in computer architecture, with a particular focus on the memory system and on using machine learning techniques to improve the design of memory system optimizations.
Host: Xuehai Qian, x04459, xuehai.qian@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
High-dimensional Magnetic Resonance Imaging of Microstructure
Mon, Jun 04, 2018 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Daeun Kim, Electrical Engineering, University of Southern California
Talk Title: High-dimensional Magnetic Resonance Imaging of Microsctucture
Series: Medical Imaging Seminar Series
Abstract: Microstructure imaging in MRI represents imaging approaches to infer biological tissue properties at the cellular level (i.e., microscopic scale) from a macroscopic imaging voxel. Conventional approaches to microstructure imaging have focused on unmixng sub-voxel compartments that are present within each voxel of MR images acquired with a single MR contrast mechanism such as diffusion or relaxation. However, unambiguously distinguishing between these sub-voxel compartments continues to be challenging with conventional methods due to the ill-posedness of the inverse problem.
This work aims at developing a novel high-dimensional MRI method to provide substantially improved abilities of resolving microstructural compartments. A main idea of the method is to use high-dimensional contrast encoding with multiple MR contrast mechanisms (e.g., both diffusion and relaxation) combined with spatially-constrained reconstruction to improve the ill-posedness. In the context of the high-dimensional MRI method, we present 1) a novel experiment design scheme, 2) estimation and optimization strategies and 3) validation and application.
Biography: Daeun Kim is a PhD candidate in Electrical Engineering at University of Southern California, supervised by Professor Justin Haldar. She received her B.S. and M.S. degrees in Electronic and Electrical Engineering at Ewha Womans University, South Korea. Her research focuses on multidimensional signal processing for microstructure imaging in MRI. Her recent work was recognized as one of the most top ten popular abstract at the International Society for Magnetic Resonance in Medicine (ISMRM) in 2016, and won the 1st Place Award for Best Abstract Presentation at the Quantitative MR Study Group of the ISMRM in 2017. She is also a recipient of the USC Alfred E. Mann Innovation in Engineering Doctoral Fellowship and the USC WiSE Merit Award for Current Doctoral Students in 2017.
Host: Professor Justin Haldar
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Talyia White
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
EE Seminar: Addressing the privacy and energy efficiency challenges of largescale information systems
Thu, Jun 14, 2018 @ 10:30 AM - 11:30 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Peter Kairouz, Postdoctoral Research Fellow/Stanford University
Talk Title: Addressing the privacy and energy efficiency challenges of largescale information systems
Abstract: The explosive growth in connectivity and information sharing across a multitude of sensory devices has been accelerating the use of machine learning to guide consumers through a myriad of choices and decisions. While this vision is expected to generate many disruptive business and social opportunities, it presents a number of unprecedented challenges. My talk will address two of these challenges: sharing largescale datasets in a privacy-preserving fashion, and enabling a massive number of sporadically active low-energy wireless devices with small payloads to access the spectrum with minimal coordination and channel estimation overheads.
In the first part of my talk, I will present fundamental (and somewhat surprising) results on sparse group testing, a version of the classical group testing problem with a constraint on the number of tests an item is allowed to participate in. I will also show how these results aid in the design of low-energy random access protocols.
In the second part of my talk, I will introduce a novel privacy notion called generative adversarial privacy (GAP). GAP leverages recent advancements in adversarial learning to arrive to a unified framework for data-driven privacy that has deep game-theoretic and information-theoretic roots. I will also showcase the performance of GAP on real-life datasets.
I will conclude my talk by discussing exciting future research directions.
Biography: Peter Kairouz is a postdoctoral research fellow at Stanford University. He received his Ph.D. in ECE, M.S. in Maths, and M.S. in ECE from the University of Illinois at Urbana-Champaign (UIUC) and his B.E. in ECE from the American University of Beirut (AUB). He interned twice at Qualcomm and more recently at Google where he designed privacy-aware unsupervised learning algorithms. He is the recipient of the 2012 Roberto Padovani Scholarship from Qualcomm's Research Center, the 2015 ACM SIGMETRICS Best Paper Award, and the 2016 Harold L. Olesen Award for Excellence in Undergraduate Teaching from UIUC. His research interests are interdisciplinary and span the areas of data and network sciences, privacy-preserving data analysis, machine learning, and information theory.
Host: Dr. Keith Chugg, chugg@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor. -
Center for Systems and Control (CSC@USC) and Ming Hsieh Institute for Electrical Engineering
Mon, Jun 25, 2018 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ketan Savla, University of Southern California
Talk Title: Capacity of Societal Cyber-Physical Systems
Series: CSC@USC Seminar Series
Abstract: The term capacity has natural connotations about fundamental limits and robustness to disruptions. For engineered systems, a rigorous characterization of capacity also provides insight into algorithms with universal performance guarantees and informs optimal strategic resource allocation. We present analysis and optimization of capacity and related performance metrics for societal cyber-physical systems (including traffic, mobility, and power networks) in canonical settings. At the macroscopic scale, we extend static network flow formulations to several flow dynamics and control settings (including cascading failure). The tractability of the resulting nonlinear analysis and optimization is facilitated by the spatial sparsity of dynamics and invariance of key input-output properties, such as monotonicity, across multiple resolutions in the network. At the microscopic scale, we consider spatial queues with state-dependent service rate; for example, such problems arise in networks of dynamically coupled vehicles. While this dependence is complex in general, we provide tight characterization in limiting cases, for instance large queue length, which leads to tight throughput estimates.
Biography: Ketan Savla is an associate professor (with tenure) and John and Dorothy Shea Early Career Chair in Civil Engineering at the University of Southern California, with joint appointments in the Sonny Astani Department of Civil and Environmental Engineering, the Daniel J. Epstein Department of Industrial and Systems Engineering (courtesy), and the Ming Hsieh Department of Electrical Engineering-Systems (courtesy). Prior to that, he was a research scientist in the Laboratory for Information and Decision Systems at MIT. He obtained his Ph.D. in Electrical Engineering and M.A. in Applied Mathematics from the University of California at Santa Barbara (UCSB), M.S. in Mechanical Engineering from the University of Illinois at Urbana-Champaign, and B. Tech. in Mechanical Engineering from the Indian Institute of Technology Bombay. His current research interest is in distributed robust and optimal control, dynamical networks, state-dependent queueing systems, and incentive design, with applications in civil infrastructure and autonomous systems. His recognitions include CCDC Best Thesis Award from UCSB, NSF CAREER, an IEEE CSS George S. Axelby Outstanding Paper Award, and AACC Donald P. Eckman Award. He serves/has served as an Associate Editor for the Conference Editorial Board of the IEEE Control Systems Society, the IEEE Transactions on Intelligent Transportation Systems, and the IEEE Control Systems Letters.
Host: Mihailo Jovanovic, mihailo@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
