TC-22 - Intelligent Measurement Systems | IEEE Instrumentation & Measurement Society

Chair(s):

Mel Siegel

Carnegie Mellon University

United States

Mel Siegel

Biography

Mel did his undergraduate work at Cornell University and his graduate work, leading to the PhD under Nobel Laureate John L. Hall at the University of Colorado - Boulder. He is currently a faculty member in the Robotics Institute, School of Computer Science, Carnegie Mellon University, where he is the founding director of the Sensors, Measurement, and Control Lab. His previous employment includes service in the US Peace Corps teaching physics and mathematics in Ghana, a post-doc at the University of Virginia, a professorship at the State University of New York - Buffalo, and an eight-year foray into industry with the specialty mass spectrometer system manufacturer Extrel, where he directed research, development, and applications. At the Robotics Institute he and his students and colleagues conduct research at all levels of sensor and measurement science, from devices to instruments to systems to advanced sensor fusion software. His interest in the human-machine interaction aspect of robotics led also to substantial contributions to the field of three dimensional display systems, including innovations for which several patents have been issued. At the robotics theory level, Mel has recently been studying energy and communication scaling issues, focusing especially on systems made up of very large numbers of very small sensor-carrying robots. In addition to teaching courses in Sensing and Sensors regularly and Electromechanical Systems occasionally, Mel runs a professional masters degree program – Master of Science in Information Technology / Robotics Technology – with a distance education component that is part of Carnegie Mellon’s internationalization effort. He is a Fellow of the IEEE.

Affiliation(s)

Carnegie Mellon University

United States

Pasquale Coscia

Università degli Studi di Milano

Italy

Scope:

Fostering the development and use of artificial intelligence, computational intelligence, and soft-computing in measurement systems and related applications.

Goals:

Develop, promote and support design methodologies, development tools, and applications of artificial intelligence, computational intelligence, and soft-computing in instrumentation and measurement systems, especially for automation, robotics, power and energy, bioengineering, medicine, signal processing, automotive, transportation, smart grids, smart home, smart cities, and ambient intelligence.
Develop, promote and support the integration of artificial intelligence, computational intelligence, and soft-computing technologies in advanced instrumentation and measurement procedures and systems, in particular by studying accuracy and classification of heterogeneous instrumentation and measurement.
Develop, promote and support standards in the field of artificial intelligence, computational intelligence, and soft-computing technologies (including, neural networks, fuzzy logic, genetic algorithms, expert systems) for intelligent instrumentation and measurement applications, as hardware and software components integrated in conventional analog and digital systems.
Disseminate information and knowledge about artificial intelligence, computational intelligence, and soft-computing technologies for instrumentation and measurement applications and attract a wider audience to their benefits, by means of workshops, special sessions in conferences, lectures, and publications.
Maintain liaisons with other committees, groups, societies, and organizations working on artificial intelligence, computational intelligence, and soft-computing technologies and in the applications fields.