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Events for April 26, 2017
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MHI Emerging Trends Seminar Series
Wed, Apr 26, 2017 @ 10:00 AM - 11:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Kai Hwang, Professor, Ming Hsieh Department of Electrical Engineering
Talk Title: Big-Data Analytics for Cloud Computing in Cognitive Applications
Series: Emerging Trends
Abstract: In this talk, Dr. Hwang will address the effective use of big-data analytics on smart clouds, social networks, intelligent robots, and IoT platforms. He will assess machine/deep learning models and available software tools to advance the cognitive service industry represented by Google, Microsoft, Apple, Facebook, Baidu, IBM, Huawei, etc. The ultimate goal is to achieve enhanced agility, mobility, security, and scalability of public clouds, IoT platforms, and social-media networks.
His talk will assess current AI programs and brain projects pursued by high-tech companies, including Google X-Lab, TensorFlow, DeepMind AlphaGo, Nvidia Digits 5 for using GPU in deep learning, IBM neuromorphic computer, and CAS/ICT Camericon project, etc. Some hidden R/D opportunities are revealed for building smart machinesï¼delivery drones, self-driving cars, blockchains, AR/VR gears, etc. Extended cognitive applications will be discussed for 5G health-care, desease detection, emotion control, and social media community services.
Biography: Kai Hwang is a Professor of EE/CS at the Univ. of Southern California. He received the Ph.D. from UC Berkeley. He has published extensively in computer architecture, parallel processing, cloud computing, and network security. His latest two books are entitled: Cloud Computing for Machine Learning and Cognitive Applications (The MIT Press, April 2017) and Big Data Analytics for Cloud/IoT and Cognitive Computing (Wiley, U.K, May 2017).
An IEEE Life Fellow, he received the very-first CFC Outstanding Achievement Award in 2004 and the Lifetime Achievement Award from IEEE Cloud2012 for his pioneering work in parallel computing and distributed systems. Four of his graduated Ph.D. students were elected as IEEE Fellows and one an IBM Fellow. He has delivered four dozens of keynote or distinguished lectures in international Conferences or Research Centers. Dr. Hwang has performed consulting work with IBM, MIT Lincoln Lab, Chinese Academy of Sciences, and INRIA in France. He can be reached via his Email at USC: kaihwang@usc.edu.
Host: Shri Narayanan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
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MHI Emerging Trends Seminar Series
Wed, Apr 26, 2017 @ 10:00 AM - 11:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Kai Hwang, Professor, Ming Hsieh Department of Electrical Engineering
Talk Title: Big-Data Analytics for Cloud Computing in Cognitive Applications
Series: Emerging Trends
Abstract: In this talk, Dr. Hwang will address the effective use of big-data analytics on smart clouds, social networks, intelligent robots, and IoT platforms. He will assess machine/deep learning models and available software tools to advance the cognitive service industry represented by Google, Microsoft, Apple, Facebook, Baidu, IBM, Huawei, etc. The ultimate goal is to achieve enhanced agility, mobility, security, and scalability of public clouds, IoT platforms, and social-media networks.
His talk will assess current AI programs and brain projects pursued by high-tech companies, including Google X-Lab, TensorFlow, DeepMind AlphaGo, Nvidia Digits 5 for using GPU in deep learning, IBM neuromorphic computer, and CAS/ICT Camericon project, etc. Some hidden R/D opportunities are revealed for building smart machines, delivery drones, self-driving cars, blockchains, AR/VR gears, etc. Extended cognitive applications will be discussed for 5G health-care, disease detection, emotion control, and social media community services.
Biography: Kai Hwang is a Professor of EE/CS at the Univ. of Southern California. He received his Ph.D. from UC Berkeley. He has published extensively in computer architecture, parallel processing, cloud computing, and network security. His latest two books are entitled: Cloud Computing for Machine Learning and Cognitive Applications (The MIT Press, April 2017) and Big Data Analytics for Cloud/IoT and Cognitive Computing (Wiley, U.K, May 2017).
An IEEE Life Fellow, he received the very first CFC Outstanding Achievement Award in 2004 and the Lifetime Achievement Award from IEEE Cloud2012 for his pioneering work in parallel computing and distributed systems. Four of his graduated Ph.D. students were elected as IEEE Fellows and one an IBM Fellow. He has delivered dozens of keynote or distinguished lectures in international Conferences or Research Centers. Dr. Hwang has performed consulting work with IBM, MIT Lincoln Lab, the Chinese Academy of Sciences, and INRIA in France. He can be reached via his Email at USC: kaihwang@usc.edu
Host: Shri Narayanan
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Cathy Huang
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Computer Science General Faculty Meeting
Wed, Apr 26, 2017 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.
Location: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Invited Faculty Only
Contact: Assistant to CS chair
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Aerospace & Mechanical Engineering Laufer Lecture
Wed, Apr 26, 2017 @ 12:00 PM - 02:00 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Clarence W. Rowley, Professor, Department of Mechanical and Aerospace Engineering, Princeton University
Talk Title: Structure, Stability, and Simplicity in Complex Fluid Flows
Series: John Laufer Keynote Lecture Series
Abstract: Fluid flows can be extraordinarily complex, and even turbulent, yet often there is structure lying within the apparent complexity. Understanding this structure can help explain observed physical phenomena, and can help with the design of control strategies in situations where one would like to change the natural state of a flow. This talk addresses techniques for obtaining simple, approximate models for fluid flows, using data from simulations or experiments. We discuss a number of methods, including balanced truncation, linear stability theory, and dynamic mode decomposition, and apply them to several flows with complex behavior, including a transitional channel flow, a jet in crossflow, and a T-junction in a pipe.
Biography: Clancy Rowley is a Professor in the Mechanical and Aerospace Engineering department at Princeton University. He received his undergraduate degree from Princeton in 1995, and his doctoral degree from Caltech in 2001, both in Mechanical Engineering. He returned to Princeton in 2001 as an Assistant Professor and was appointed Associate Professor in 2007, and Full Professor in 2012. He has received several awards, including an NSF CAREER Award and an AFOSR Young Investigator Award. His research interests lie at the intersection of dynamical systems, control theory, and fluid mechanics, and focus on reduced-order models suitable for analysis and control design.
Host: Department of Aerospace and Mechanical Engineering
More Info: https://ame.usc.edu/about/seminars/
Location: Ronald Tutor Campus Center (TCC) - Trojan Ballroom A
Audiences: Everyone Is Invited
Contact: Ashleen Knutsen
Event Link: https://ame.usc.edu/about/seminars/
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MHI CommNetS seminar
Wed, Apr 26, 2017 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Adam Wierman, Caltech
Talk Title: Platforms & Networked Markets: Transparency & Market Power
Series: CommNetS
Abstract: Platforms have emerged as a powerful economic force, driving both traditional markets, like the electricity market, and emerging markets, like the sharing economy. The power of platforms comes from their ability to tame the complexities of networked marketplaces -- marketplaces where there is not a single centralized market, but instead a network of interconnected markets loosely defined by a graph of feasible exchanges. Despite the power and prominence of platforms, the workings of platforms are often guarded secrets, e.g., we know little about how amazon matches buyers and seller and how uber matches drivers and riders. Further, many competing platforms make very different design choices, but little is understood about the impact of these differing choices. In this talk, I will overview recent work that focuses on reverse engineering the design of platforms and understanding the consequences of design choices underlying modern platforms. I will use electricity markets and ridesharing services as motivating examples throughout the talk.
Biography: Adam Wierman is a Professor in the Department of Computing and Mathematical Sciences at the California Institute of Technology, where he currently serves as Executive Officer. He is also the director of the Information Science and Technology (IST) initiative at Caltech. He is the founding director of the Rigorous Systems Research Group (RSRG) and co-Director of the Social and Information Sciences Laboratory (SISL). His research interests center around resource allocation and scheduling decisions in computer systems and services. He received the 2011 ACM SIGMETRICS Rising Star award, the 2014 IEEE Communications Society William R. Bennett Prize, and has been coauthor on papers that received of best paper awards at ACM SIGMETRICS, IEEE INFOCOM, IFIP Performance (twice), IEEE Green Computing Conference, IEEE Power & Energy Society General Meeting, and ACM GREENMETRICS. Additionally, he maintains a popular blog called Rigor + Relevance.
Host: Prof. Insoon Yang
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
