Events for November
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Professional Enhancement Seminar
Tue, Nov 03, 2020 @ 04:00 AM - 05:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: TBD, TBD
Talk Title: TBD
Abstract: This bi-monthly seminar brings industry professionals from fields within electrical and computer engineering to share advice and answer questions about what students can do to improve their professional experience.
Meeting ID: 974 2555 7004
Passcode: 494632
Host: Mihailo Jovanovic
Webcast: https://usc.zoom.us/j/97425557004?pwd=T29UWER0emdmRllVMVFiT3pRNlk5QT09WebCast Link: https://usc.zoom.us/j/97425557004?pwd=T29UWER0emdmRllVMVFiT3pRNlk5QT09
Audiences: Everyone Is Invited
Contact: Benjamin Paul
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar
Wed, Nov 04, 2020 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Nick Gravish, Mechanical & Aerospace Engineering University of California, San Diego
Talk Title: The Hard Parts of Soft Robots
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: The form and shape of modern robots are rapidly changing from rigid, stiff, but precise machines to more compliant, adaptable, but inherently underactuated systems; often called soft robotics. The emergence of soft robots is in part motivated by the need for safe robotic technologies when human interaction is frequent. However, another motivation for designing soft robotic systems is to exploit the compliant mechanics and high degree of freedom of these systems for adaptability, actuation, and sensing. The majority of efforts to build soft robots utilize a standard toolkit of silicone elastomer casting, pneumatic actuation, and stretchable conducting elements. In this talk I will present our efforts to design and build robots capable of compliance control, reconfiguration, and adaptability using laminate and 3D printing techniques, where "softness" is derived from the configuration of rigid constituent materials. This will focus on three research efforts: compliance control through sliding-layer laminates, insect-inspired 3D printing for "flexoskeleton" robots, and shape changing robot feet for improved mobility of legged robots. While these efforts focus primarily on the mechanical domain of soft robots I will highlight opportunities for sensor and electronics integration through these fabrication approaches.
Biography: Dr. Nick Gravish received his PhD from Georgia Tech where he worked on understanding the locomotion of ants within their nest. Gravish used robots as physical models to motivate and study aspects of biological locomotion. During his post-doc Gravish worked in the microrobotics lab of Rob Wood at Harvard, where he gained expertise in designing and studying insect-scale robots. Gravish is an assistant professor at UC San Diego in the Mechanical and Aerospace Engineering department. His lab focuses on developing new bio-inspired robotic technologies to improve the adaptability and resilience of mobile robots.
Host: Feifei Qian, feifeiqi@usc.edu
More Info:
Webcast: https://usc.zoom.us/webinar/register/WN_YSl0DRVOQJetWGNAACPOYQLocation: Online
WebCast Link: https://usc.zoom.us/webinar/register/WN_YSl0DRVOQJetWGNAACPOYQ
Audiences: Everyone Is Invited
Contact: Talyia White
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Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar
Wed, Nov 18, 2020 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Taylor T. Johnson, Electrical Engineering and Computer Science, Vanderbilt University
Talk Title: Verifying Deep Neural Networks in Autonomous Cyber-Physical Systems
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: The ongoing renaissance in artificial intelligence (AI) has led to the advent of machine learning (ML) methods deployed within components for sensing, actuation, and control in safety-critical cyber-physical systems (CPS). While such learning-enabled components (LECs) are enabling autonomy in systems like autonomous vehicles, swarm robots, and other CPS, as demonstrated in part through recent accidents in semi-autonomous/autonomous CPS and by adversarial ML attacks, ensuring such components operate reliably in all scenarios is extraordinarily challenging. We will discuss methods for assuring safety and security specifications in autonomous CPS using our NNV (Neural Network Verification) software tool (https://github.com/verivital/nnv), which has been applied to verify specifications for adaptive cruise control (ACC) and autonomous emergency braking (AEB) systems in motor vehicles. Next, we will present recent results on using NNV to prove robustness of neural networks used for perception tasks, such as image classification, applied to the VGG16/VGG19 networks that achieve high accuracy on ImageNet, as well as recent work on robustness of semantic segmentation. We will conclude with some architectural solutions to provide safety assurance in autonomous CPS at runtime, building on supervisory control with the Simplex architecture using real-time reachability, and will discuss future research directions for establishing trustworthy AI within CPS that we are exploring in a DARPA Assured Autonomy project.
Biography: Dr. Taylor T. Johnson, PE, is an Assistant Professor of Computer Engineering (CmpE), Computer Science (CS), and Electrical Engineering (EE) in the Department of Electrical Engineering and Computer Science (EECS) in the School of Engineering (VUSE) at Vanderbilt University (since August 2016), where he directs the Verification and Validation for Intelligent and Trustworthy Autonomy Laboratory (VeriVITAL) and is a Senior Research Scientist in the Institute for Software Integrated Systems (ISIS). Dr. Johnson was previously an Assistant Professor of Computer Science and Engineering (CSE) at the University of Texas at Arlington (September 2013 to August 2016). Dr. Johnson earned a PhD in Electrical and Computer Engineering (ECE) from the University of Illinois at Urbana-Champaign in 2013, where he worked in the Coordinated Science Laboratory with Prof. Sayan Mitra, and earlier earned an MSc in ECE at Illinois in 2010 and a BSEE from Rice University in 2008. Dr. Johnson has published over 90 papers on formal methods and their applications across cyber-physical systems (CPS) domains, such as power and energy, aerospace, automotive, transportation, biotechnology, and robotics, one of which was awarded an ACM Best Software Repeatability Award. Dr. Johnson is a 2018 and 2016 recipient of the AFOSR Young Investigator Program (YIP) award, a 2015 recipient of the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Research Initiation Initiative (CRII), and his research is / has been supported by AFOSR, ARO, AFRL, DARPA, NSA, NSF, the MathWorks, NVIDIA, ONR, Toyota, and USDOT. Dr. Johnson is a member of AAAI, AAAS, ACM, AIAA, IEEE, and SAE, and is a Professional Engineer (PE) in Tennessee.
Host: Pierluigi Nuzzo, nuzzo@usc.edu
Webcast: https://usc.zoom.us/webinar/register/WN_YSl0DRVOQJetWGNAACPOYQLocation: Online
WebCast Link: https://usc.zoom.us/webinar/register/WN_YSl0DRVOQJetWGNAACPOYQ
Audiences: Everyone Is Invited
Contact: Talyia White
