My name is Rico Picone, PhD. I’m an Associate Professor at Saint Martin’s University in the Department of Mechanical Engineering.
I research cybernetic systems and human-machine interaction. Other research interests include artificial intelligence (AI); human-computer/robot interaction (HC/RI); engineering education; enhancing magnetic resonance technologies, especially magnetic resonance force microscopy (MRFM); and Lacanian psychoanalysis.
I am teaching courses related to mechatronics, system dynamics, embedded computing, control theory, and artificial intelligence.
You can also find me elsewhere on the interwebs:
- ORCiD — identification badge things
- ResearchGate — academic network things
- GitHub — codey things
- Dialectica — startup things
- Linkedin — pro things
- Twitter — little things
- StackExchange — questionable things
Human-computer interaction (HCI) and human-robot interaction study the design of computer and robot systems and the interface of humans with these systems. It includes such fields as sensor and information fusion, artificial intelligence, and intelligence amplification, all of which are aspects of my work.
My work here explores augmented cognition, human intelligence amplification, haptics, and how attending to the Freudo-Lacanian unconscious may be crucial.
Augmented cognition, information architecture, and sensor fusion in robotics
An information architecture is a structural description of an information system. We have developed a new information architecture for intelligence amplification. A startup company, dialectica has sprung up around these ideas. Applications in robotics include sensor and information fusion via fuzzy logic. The “fuzzy” architecture allows quantitative data to be fused with qualitative information.
Rico A.R. Picone, Dane Webb, Finbarr Obierefu, Jotham Lentz. New methods for metastimuli: architecture, embeddings, and neural network optimization. To appear in the Springer Lecture Notes in Artificial Intelligence for the Human-Computer Interaction Conference 2021, Augmented Cognition thematic area. Preprint available at arXiv:2102.07090 [cs.AI].
Rico A.R. Picone, Dane Webb, Bryan Powell. Metastimuli: an introduction to PIMS filtering. In: Schmorrow D., Fidopiastis C. (eds) Augmented Cognition. Human Cognition and Behavior. HCII 2020. Lecture Notes in Artificial Intelligence, vol 12197. Springer, Cham. 10 July 2020. DOI 10.1007/978-3-030-50439-7_8.
Rico A.R. Picone, Jotham Lentz, and Bryan Powell. The fuzzification of an information architecture for information integration. In: Yamamoto S. (eds) Human Interface and the Management of Information: Information, Knowledge and Interaction Design. HIMI 2017. Lecture Notes in Computer Science, vol 10273. Springer, Cham. ISBN 978-3-319-58521-5. DOI 10.1007/978-3-319-58521-5_11.
Rico A.R. Picone and Bryan Powell. A New Information Architecture: a Synthesis of Structure, Flow, and Dialectic. Human Interface and the Management of Information: Information and Knowledge Design, Springer, Volume 9172, 2015, Pages 320-331. ISBN 978-3-319-20611-0. DOI 10.1007/978-3-319-20612-7_31.
Smart devices and haptics
Smart devices—devices with embedded computers—are becoming ubiquitous. My research group at Saint Martin’s University includes students working on smart devices that augment the user’s ability to make decisions. These devices can gather information about the user’s situation that the user may not be able to access, then interact with the user.
Research: magnetic resonance imaging technologies
Magnetic resonance imaging (MRI) technologies such as body-MRI, diffusion tensor imaging, and magnetic resonance force microscopy. All these technologies share a common limitation: low nuclear polarization (typically about one one-thousandth of full polarization). The margin for improvement is huge!
The two established methods for increasing polarization are (1) increasing the background magnetic field and (2) dynamic nuclear polarization. Unfortunately, both present practical difficulties.
The emerging field of separative magnetization transport (SMT) is attempting to use the concepts derived from statistical mechanics and separation science to increase polarization; that is, hyperpolarize an imaging sample.
I collaborate with the University of Washington and Cornell University on SMT research. We have two functioning MRFM microscopes, two of only a handful in the world. We are working to experimentally validate our SMT theoretical models. Theory, modeling, and simulation are the primary contributions from the SMU laboratory, which also contributes embedded computing, instrumentation, and control theory expertise.
Rico A.R. Picone, Solomon Davis, Cameron Devine, John A. Sidles, Joseph L. Garbini. Instrumentation and control of damped harmonic oscillators via a single-board microprocessor-FPGA device. Review of Scientific Instruments, Volume 88, April 2017, Pages 045108. DOI 10.1063/1.4979971.
Rico A.R. Picone, Joseph L. Garbini, John A. Sidles. Modeling spin magnetization transport in a spatially varying magnetic field. Journal of Magnetism and Magnetic Materials, Volume 374, 15 January 2015, Pages 440–450. DOI 10.1016/j.jmmm.2014.08.079.
Rico A.R. Picone. Separative magnetization transport: theory, model, and experiment. PhD Thesis, University of Washington, 2014.
Research: engineering education
Engineering education is a lively field because technology is rapidly advancing. As educators, we must respond to the changing landscape in order to prepare our students to thrive as engineers.
Cameron Devine, Joseph L. Garbini, Rico A.R. Picone. StateMint: A Set of Tools for Determining Symbolic Dynamic System Models Using Linear Graph Methods. The Journal of Open Source Education, 2(14), 44, April 2019. DOI 10.21105/jose.00044.
Paul E. Slaboch, Floraliza B. Bornasal, Rico A.R. Picone. A Pilot Study of a Novel Set of Three Courses for Teaching Electrical System Analysis to Mechanical Engineering Students. American Society for Engineering Education Annual Conference & Exposition, Proceedings. June 2016. DOI 10.18260/p.26394.
Rico A.R. Picone and Paul E. Slaboch. A Novel Set of Courses for Teaching Electrical System Analysis to Mechanical Engineering Students. Proceedings of the 2015 American Society for Engineering Education Rocky Mountain Section Conference, April 2015.