My name is Rico Picone, PhD. I’m an Assistant Professor at Saint Martin’s University in the Department of Mechanical Engineering.

I research ways to enhance magnetic resonance technologies, especially magnetic resonance force microscopy (MRFM). Other research interests include artificial intelligence (AI), human-computer/robot interaction (HC/RI), and engineering education.

I am teaching courses related to mechatronics, system dynamics, embedded computing, control theory, and artificial intelligence.

Curriculum Vitæ

Elsewhere

You can also find me elsewhere on the interwebs:

Office Hours
WF 12–1 and MWF 1–2

Research: magnetic resonance imaging technologies

Introduction

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.

My work

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.

Selected publications

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: AI and human-computer/robot interaction

Introduction

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

I have two current projects in HCI. Both projects are focused on different aspects of intelligence amplification, and one includes an embedded computing aspect.

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.

Selected publications

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

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.

For instance, a group of students has developed a smart thermostat with new capabilities to save energy through informing a user about the effects of her decisions. This project has been funded by Puget Sound Energy.

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.

Selected publications

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.