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Events for March 21, 2016
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CS Colloquium: Andrew Gordon Wilson (CMU) -Scalable Gaussian Processes for Scientific Discovery
Mon, Mar 21, 2016 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Andrew Gordon Wilson, CMU
Talk Title: Scalable Gaussian Processes for Scientific Discovery
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium
Every minute of the day, users share hundreds of thousands of pictures, videos, tweets, reviews, and blog posts. More than ever before, we have access to massive datasets in almost every area of science and engineering, including genomics, robotics, and astronomy. These datasets provide unprecedented opportunities to automatically discover rich statistical structure, from which we can derive new scientific discoveries. Gaussian processes are flexible distributions over functions, which can learn interpretable structure through covariance kernels. In this talk, I introduce a Gaussian process framework which is capable of learning expressive kernel functions on massive datasets. I will show how this framework generalizes a wide family of scalable machine learning approaches, leverages the inductive biases of deep learning architectures, and allows one to exploit existing model structure for significant further gains in scalability and accuracy, without requiring severe assumptions. I will then discuss how we can use this framework for reverse engineering human learning biases, crime prediction using point processes, image inpainting, video extrapolation, modelling change points and the impacts of vaccine introduction, and discovering the structure and evolution of stars.
Biography: Andrew Gordon Wilson is a Postdoctoral Research Fellow in the Machine Learning Department at Carnegie Mellon University working with Eric Xing and Alexander Smola. Andrew received his PhD in machine learning from the University of Cambridge in 2014, supervised by Zoubin Ghahramani. Andrew's research interests include probabilistic machine learning, scalable inference, Gaussian processes, kernel methods, Bayesian modelling, nonparametrics, and deep learning. Andrew's work has received several awards, including the G-Research Outstanding Dissertation Award in 2014 and the Best Student Paper Award at the Conference on Uncertainty in Artificial Intelligence in 2011.
Host: CS Department
Location: Olin Hall of Engineering (OHE) - 136
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Seminars in Biomedical Engineering
Mon, Mar 21, 2016 @ 12:30 PM - 01:49 PM
Conferences, Lectures, & Seminars
Speaker: Bryan Smith, Ph.D., Instructor, Department of Radiology Stanford University, Stanford, California
Talk Title: Nanoparticle imaging: Shifting paradigms to transform nanomedical diagnosis and therap
Biography: After receiving his Bachelors degree in Physics, Mathematics, and Biomedical Engineering at Tufts University, Bryan Smith completed his Ph.D. in Biomedical Engineering as an NSF Fellow at The Ohio State University working in cancer nanotechnology. He moved to Stanford University for his post-doctoral work, where he was awarded a Stanford Molecular Imaging Scholar NIH Fellowship as well as a Stanford Dean's Fellowship. He was granted a K99/R00 NIH Pathway to Independence award for his work in nanomedical imaging
Host: K. Kirk Shung, PhD
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Addressing Spectrum Scarcity through Optical Wireless Communications
Mon, Mar 21, 2016 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mohamed-Slim Alouini, King Abdullah University of Science and Technology
Talk Title: Addressing Spectrum Scarcity through Optical Wireless Communications
Abstract: Rapid increase in the use of wireless services over the last two decades has lead the problem of the radio-frequency (RF) spectrum exhaustion. More specifically, due to this RF spectrum scarcity, additional RF bandwidth allocation, as utilized in the recent past, is not anymore a viable solution to fulfill the demand for more wireless applications and higher data rates. The talk goes first over the potential offered by optical wireless communications to relieve spectrum scarcity. It then summarizes some of the challenges that need to be surpassed before such kind of systems can be massively deployed. Finally the talk offers an overview of some of the recent results for the determination of the capacity of optical wireless channels.
Biography: Mohamed-Slim Alouini (S'94, M'98, SM'03, F'09) was born in Tunis, Tunisia. He received the Ph.D. degree in Electrical Engineering from the California Institute of Technology (Caltech), Pasadena, CA, USA, in 1998. He served as a faculty member in the University of Minnesota, Minneapolis, MN, USA, then in the Texas A&M University at Qatar, Education City, Doha, Qatar before joining King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah Province, Saudi Arabia as a Professor of Electrical Engineering in 2009. His current research interests include the modeling, design, and performance analysis of wireless communication systems.
Host: Andreas Molisch, molisch@usc.edu EEB 530, x04670
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 539
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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EE 598 Cyber-Physical Systems Seminar Series
Mon, Mar 21, 2016 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Marilyn Wolf, Georgia Institute of Technology
Talk Title: Service-oriented Architectures for Cyber-physical Systems
Abstract: Service-oriented architectures are widely used in information processing and Web technologies to provide scalable access to resources in distributed systems and extensible applications. However, many traditional service-oriented architectures are designed for transaction processing. In contrast, cyber-physical systems used for real-time control require quality-of-service constraints and graceful handling of failures to provide requested services. Our group is developing extended service-oriented models for use in smart energy grids and other applications. We will describe our work in service-oriented architectures, including model-based design and simulation.
Biography: Marilyn Wolf is Rhesa S. "Ray" Farmer Distinguished Chair in Embedded Computing Systems and Georgia Research Alliance Eminent Scholar at the Georgia Institute of Technology. She received her BS, MS, and PhD in electrical engineering from Stanford University in 1980, 1981, and 1984, respectively. She was with AT&T Bell Laboratories from 1984 to 1989. She was on the faculty of Princeton University from 1989 to 2007. Her research interests include cyber-physical systems, embedded computing, embedded video and computer vision, and VLSI systems. She has received the ASEE Terman Award and IEEE Circuits and Systems Society Education Award. She is a Fellow of the IEEE and ACM and an IEEE Computer Society Golden Core member.
Host: Paul Bogdan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Estela Lopez
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EE-EP Seminar - Dion Khodagholy, Monday, March 21st at 2:00pm in EEB 132
Mon, Mar 21, 2016 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dion Khodagholy, New York University Langone Medical Center
Talk Title: Large-Scale Organic Neural Interface Devices
Abstract: Recording from neural networks at the temporal resolution of action potentials is critical for understanding how information is processed in the brain. We developed an organic, conformable, biocompatible and scalable neural interface electrode and transistor arrays that can record both Local Field Potential (LFP) and extracellular action potentials without penetrating the brain surface. We recorded spiking activity in both rodent experiments and intra-operatively in patients undergoing epilepsy surgery using a large-scale surface probe designed to enable localization of fine LFP activity and the underlying neuronal entrainment. Large-scale, chronically recorded data generated by these devices has broad applicability to the understanding of physiologic and pathologic network activity, control of brain-machine interfaces, and therapeutic closed-loop devices.
Biography: Dion Khodagholy is a fellow at the Simon's Society of Fellows and a postdoctoral research associate in Prof. GyoÌrgy BuzsaÌki's laboratory at New York University Langone Medical Center (NYULMC). He received his Masters degree from University of Birmingham (UK) in Electronic and Communication Engineering. This was followed by a second Masters degree in Microelectronics at Ecole des Mines (France) combined with industry experience at Microelectronic Center of Provence. He attained his Ph.D. degree in Microelectronics at the Department of Bioelectronics (BEL) of Ecole des Mines with Prof. George Malliaras. At BEL, he focused on understanding organic semiconductor device physics and developing organic-based devices to interface with biology. His postdoctoral research at NYULMC is focused on three main domains: (i) design and development of large-scale, organic material-based neural interface devices; (ii) analysis of neural data acquired by these devices to understand large-scale neural network function; (iii) translation of these advancements to neural data acquisition systems in patients with epilepsy. His research explores the interface of electronics and the brain in the context of both applied and discovery sciences, with the ultimate goal of innovating in device engineering and neuroscience methods to improve diagnosis and treatment of neuropsychiatric disease.
Host: EE-Electrophysics
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
