Ph.D., University of Miami, 1987
B.S., Technical University Munich, 1984
Peter Bauer was born in Bamberg, Germany and came to the US in 1981 on a Fulbright scholarship. Here he received his Diplom degree in EE from Technical University Munich, 1984. In 1987, he received his Ph.D in EE from the University of Miami, where he studied m-D system theory with Professor E.I. Jury. In the summer of 1988 Peter Bauer came to ND. Dr. Bauer's research focus before coming to Notre Dame was on multi-dimensional systems, in particular the stability of m-D nonlinear and time-variant systems. Robust stability of systems under parameter uncertainties was another area of prior work. Dr. Bauer has had a long standing research collaboration with Professor Kamal Premaratne at the University of Miami. He is also collaborating with Dr. Scheutz at IU Bloomington, Dr. Eric Rogers at University of Southampton, England, and Dr. Galkowski at the University of Zielona Gora, Poland. Dr. Bauer has also had a long standing research collaboration with the Technical University Munich, Germany and the Unversity of Hiroshima, Japan.
Summary of Activities/Interests
Research Interests: Distributed sensor/actuator networks, network congestion control, networked control systems, system theory, digital signal processing, stability theory, multidimensional systems. Most recent research addresses the following problems: - Swarm navigation and resource allocation using ultra-low complexity swarm agents. This work provides a scalable, low cost swarming solution that can be used in water, air,and on land. The MOSES laboratory at ND has built VEX based swarms to solve a number of problems, ranging from tracking and protection tasks to contaminant detection. - Sensor Fusion using a new paradim to effectively combine information from disparate heterogeneous sensors and other sources: Evidence Filtering. This methods is particularly effective in handling "uncertainties" and can be used to accomplish time or frequency selective fusion of large amounts of data in real time. Distributed fusion and in-sensor network processing are also a major focus. - Series Hybrid Vehicle Technology to achieve several times the gas mileage current vehicles can attain. The concept is based on a "batteryless" approach. - Networked sensing and control. - Multi-dimensional system characterization of grid-sensor networks. - Synchronization errors in networked systems. Current Projects: DTRA - Crane Naval supported project: Networked Sensing in Built and Natural Environments This is a multi-year multi-departmental project addressing distributed contaminant detection and propagation using a sparse stationary and mobile wireless sensor networks. Ultra-low Complexity Swarming Project: this project is performed in conjunction with IU and aims at the design and implementation of large swarms with ultra-low complexity agents. The Extreme Series Hybrid Project: performed in conjunction with SlipStream Projects, Mishawaka, IN. Most Cutting Edge: - The Ultra-Low Complexity Swarm paradigm developed in the MOSES lab at ND: This is the lowest complexity implementation of a mid to large size swarm to date. It is based very simple navigation rules that are derived from potential fields that are radio beacon induced. The concept can easily handle coordination of hundreds of swarm agents in a fully distributed manner, while not even requiring a digital processor in each agent. The arising self-organizing behavior (emergent behavior) is obtained from basic neural characteristic of a swarm agent. - design and construction of a mid-size Hybrid Electric Drive Train that allows for 100mpg+ gas mileage under city driving conditions. - Real time selective information fusion for detection: based on a concept called "evidence filtering", vast amounts of data can be sifted through and selectively fused using a Dempster Schafer based fusion mechanism. This allows to solve the "needle in the hay stack" problem, if signature information on the information sources is known.
Courses: Signals & Systems I, Signals & Systems Rec, Signals & Systems
December 14, 2012