Guest Speakers

 

Dr. DI GENNARO Stefano

Short Bio: Dr. DI GENNARO Stefano obtained the degree in Nuclear Engineering in 1987 (summa cum laude), and the Ph.D. degree in System Engineering in 1992, both from the University of Rome "La Sapienza", Rome, Italy. In October 1990 he joined the Department of Electrical Engineering, University of L'Aquila, as Assistant Professor of Automatic Control. Since 2001, he has been Associate Professor of Automatic Control at the University of L'Aquila. In 2012 he joined the Department of Information Engineering, Computer Science and Mathematics and he is also with the Center of Excellence DEWS. He holds courses on Automatic Control and Nonlinear Systems. He has been visiting various Research Centers, among which the Department of Electrical Engineering of the Princeton University, the Department of Electrical Engineering and Computer Science at Berkeley, and the Centro de Investigación y Estudios Avanzados del IPN, at Guadalajara. He is working in the area of hybrid systems, regulation theory, and applications of nonlinear control. Title of the presentation Event-Triggered Real-Time Techniques for Digital Implementation of Controllers for Spacecraft Structures Abstract The event-triggering is a technique that allows executing a control task whenever a certain event is produced, instead of on the basis of a constant sampling ratio. In the setting of implementation of continuous-time controllers on digital platforms, these events describe the loss of stability of the control system. Mathematically, this event is produced when the loss of stability occurs, which can be described in terms of the derivative of a certain Lyapunov function used to design the continuous-time control law. This technique is applied to a spacecraft structure showing that it can ensure stability with better performance, in terms of higher sampling periods, with respect a more classic discretization of the controller using a constant sampling ratio.

 

Dr. Sangho Shin

Short Bio: Ph,D. Sangho Shin is an Assistant Professor of Electrical Engineering at the Henry M. Rowan College of Engineering, Rowan University, Glassboro, New Jersey, USA. At Rowan, Dr. Shin is running a NASA sponsored CubeSat project, named MemSat, for its primary mission to evaluate performance of memristor technology in space environment. Dr. Shin received his Ph.D. degree from the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea, in 2007, in Electrical Engineering, and prior to joining Rowan he was a faculty member of University of California at Santa Cruz. Dr. Shin teaches undergraduate and graduate courses covering circuit and systems theory; analog/digital/RF integrated circuits; VLSI systems; nanoelectronic systems; and memristors and memristive electronics. His research interests and activities broadly include the emerging field of memristors enabled nanoelectronic circuit systems; low-power VLSI design and analog/RF integrated circuits; mixed-signal and mixed-technology integrated systems; and the small spacecraft technologies. He authored two book chapters, 50+ journal and conference papers, mostly on the memristive electronics, low-power CMOS integrated systems, and small satellite systems. He is a Senior Member of IEEE.

 

Dr. Gregory Ditzler

Short Bio: Dr. Gregory Ditzler received a BSc from the Pennsylvania College of Technology (2008), a MSc degree from Rowan University (2011), and a PhD from Drexel University (2015). He is currently an Assistant Professor at the University of Arizona in the Electrical & Computer Engineering Department where he is also affiliated with the Cognitive Sensing Research Center, and he directs the University of Arizona's Machine Learning and Data Analytics Lab. He received the Best Student Paper at the IEEE/INNS International Joint Conference on Neural Networks (2014), a Nihat Bilgutay Fellowship (2013), Koerner Family Engineering Fellowship (2014), Drexel University's Office of Graduate Studies Research Excellence Award (2015), and Rowan University's Research Achievement Award (2009). In 2016, he was selected as a summer faculty fellow at the Air Force Research Lab. He is a member of the IEEE, ACM and SIAM societies. His current research interests can broadly be characterized as machine learning with special interests in large-scale feature subset selection, incremental learning, multiple classifier concept drift, online and incremental learning, multiple classifier systems, and applications of machine learning in microbial ecology and cybersecurity.