CS4/591: High Performance Computing (Fall, 2024) (Instructor, Course Site)
CS151: Computer Programming Fundamentals for Non-Majors (Spring, 2020) (Instructor, Course Site)
CS151: Computer Programming Fundamentals with C++ (Summer, 2003) (Instructor, Course Site)
CS152: Computer Programming Fundamentals with Java (OOP Lecture)
CS201: Discrete Mathematics (Proofs Lecture)
CS251: Intermediate Programming with Java (Teaching Assistant, Lab Site)
CS261: Mathematical Foundations of Computer Science (Instructor, Course Site)
CS523: Complex Adaptive Systems (Spring 2013) (Teaching Assistant, Course Site)
CS523: Complex Adaptive Systems (Spring 2017) (Instructor, Course Site)
CS591: Programming Swarm Robots (Fall 2017) (Instructor, Course Site)
Q-bio (Summer 2018) (Models Lecture)
CARC CS/Math471: Introduction to Scientific Computing (Fall 2018) (HPC Lecture)
CS533: Experimental Methods in Computer Science (Part 2 of a two part course. Part 1 taught by Prof Mueen)
Intro to CARC Workshop (Spring 2019)
Coding for Beginners
CS4/591: High Performance Computing (Spring, 2024) (Instructor, Course Site)
Current Activities:
● Center for Advanced Research Computing: High performance computing research support for a wide array of projects, from COVID modelling to Quantum Algorithms and Neuroimaging.My work has several themes: Understanding biological processes through computer simulation and modelling, distributed high performance computing, and the design of distributed search algorithms for teams of robots (NASA ChiliHouse, NASA Swarmathon, and NSF NRI VolCAN). The computational biology research focuses on signalling and search processes in the immune system and search strategies in Pogonomyrmex sp . desert seed-harvester ants.
My work has been funded by the NASA Astrobiology Institute, as part of the Agnostic Biosignatures for Extant Life program, to develop algorithms for detection of complex molecules that qualify as having been produced by living processes. This work will help us understand the data we receive from space probes to other worlds.
I was technical lead for Swarmathon III and IV and was software lead for Swarmathons I and II. The Swarmathon is a robotics competition held at NASA Kennedy Space Center.
The robotics work is primarily funded by NASA Kennedy Space Center. It is intended to help us understand how autonomous robots on other planets could best search for resources in support of human missions, and also to provide a robotics educational platform for underrepresented students from MUREP institutions. The educational component is in the form of an annual robotics competition called Swarmathon.
Algorithms control an increasing portion of our daily lives. Ensuring that those algorithms are fair is a difficult but critical task. We recently challenged proposed changes to the U.S. Department of Housing and Urban Development's (HUD) proposal to dramatically revise rules around responsibility for algorithmic fairness in the Fair Housing Act (Comment on Regulations, Forbes article).
The current version of the quick robot install USB disk image is here: Swarmathon IV Swarmie Disk Image (16.03 GB). When you boot from this image it will WIPE your robot harddrive and install Ubuntu 16.04 with ROS Kinetic Kame and a git repository containing the competition base code.
"Using RuleBuilder to graphically define and visualize BioNetGen-language patterns and reaction rules." Suderman, Ryan, G. Matthew Fricke, and William S. Hlavacek, In: Hlavacek W. (eds) Modeling Biomolecular Site Dynamics. Methods in Molecular Biology, vol 1945. Humana Press, New York, NY, 2019. PDF
"Ant Colonies as a Model of Human Computation", Melanie Moses, Tatiana Flanagan, Kenneth Letendre and G. Matthew Fricke, In: Handbook of Human Computation, Springer, 2014. website
More is Faster: Why Population Size Matters in Biological Search. Janatul Ferdous, G. Matthew Fricke, and Melanie Moses., Journal of Computational Biology (2024), PDF
CO2 emissions during the 2023 Litli Hrtur eruption in Reykjanes, Iceland: 13C tracks magma degassing.Tobias Fischer et al. Bulletin of Volcanology (2024), Web, PDF
More is Faster: Why Population Size Matters in Biological Search. Janatul Ferdous, G. Matthew Fricke, and Melanie Moses., Journal of Computational Biology (2024), PDF
Sensor Equipped UAS for Non-Contact Bridge Inspections: Field Application. Roya Nasimi, Fernando Moreu, and G. Matthew Fricke., Sensors (2023), PDF
Aerial Survey Robotics in Extreme Environments: Mapping Volcanic CO2 Emissions With Flocking UAVs. John Erickesen et al., Frontiers in Control Engineering, https://doi.org/10.3389/fcteg.2022.836720 (2022). Web, PDF
The Grayness of the Origin of Life. Hillary H. Smith et al., Life, 11, 498. https://doi.org/10.3390/life11060498 (2021). Web, PDF
Machine learning feature analysis illuminates disparity between E3SM climate models and observed climate change. Nichol, J. Jake, Matthew G. Peterson, Kara J. Peterson, G. Matthew Fricke, and Melanie E. Moses. Journal of Computational and Applied Mathematics (2021): 113451. Web, PDFAerial strategies advance volcanic gas measurements at inaccessible, strongly degassing volcanoes. Emily. J. Liu et al. Science Advances, (2020) Vol. 6, no. 44, eabb9103, DOI: 10.1126/sciadv.abb9103. PDF
Swarm Foraging Review: Closing the Gap Between Proof and Practice. Qi Lu, G. Matthew Fricke, John C. Ericksen, and Melanie E. Moses Current Robotics Reports (2020): 1-11. PDF
Variability in the Analysis of a Single Neuroimaging Dataset by Many Teams. Rotem Botvinik-Nezer et al. Nature (2020). Paper
Modeling T Cell Motion in Tissues During Immune Responses. Cannon, Judy, Melanie E. Moses, Janie R. Byrum, Paulus Mrass, G Matthew Fricke, and Humayra Tasnim. In: Biophysical Journal 116 (Feb. 2019), 322a. doi: 10.1016/j.bpj.2018.11.1749.
Quantitative Measurement of Naïve T cell Association with Dendritic Cells, FRCs, and Blood Vessels in Lymph Nodes., Tasnim, Humayra, G. Matthew Fricke, Janie R. Byrum, Justyna O. Sotiris, Judy L. Cannon, and Melanie E. Moses. Frontiers in immunology 9 (2018). PDF
ROCK regulates the intermittent mode of interstitial T cell migration in inflamed lungs. Paulus Mrass, Sreenivasa Oruganti, G. Matthew Fricke, Justyna Tafoya, Janie Byrum , Lihua Yang, Samantha Hamilton, Mark Miller, Melanie Moses and Judy Cannon. Nature Communications (2017)
Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search. Fricke, G. Matthew, Kenneth A. Letendre, Melanie E. Moses, and Judy L. Cannon. PLoS Computational Biology 12.3 (2016): e1004818. PDF
Immune-inspired search strategies for robot swarms. G. Matthew Fricke, Joshua Hecker, Judy Cannon, and Melanie Moses. Robotica 34, no. 08 (2016): 1791-1810. Cambridge Press. PDF
Quantifying the Effect of Colony Size and Food Distribution on Harvester Ant Foraging, Tatiana P. Flanagan, Kenneth Letendre, William R. Burnside, G. Matthew Fricke, and Melanie E. Moses, PLoS ONE, 2012. PDF
GetBonNie for building, analyzing, and sharing rule-based models, Bin Hu; G. Matthew Fricke; James R. Faeder; Richard G. Posner; William S. Hlavacek Bioinformatics 2009, Oxford Journals
Receptor aggregation by intermembrane interactions: A Monte Carlo study G. Matthew Fricke; James L. Thomas Biophysical Chemistry Volume 119, Issue 2, 20 Jan 2006; Pages 205-211. PDF
Navigating the Edge: UAS Boundary Tracing for Efficient Volcanic Plume Monitoring John Ericksen et al. IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR) (2024), PDF
A Bio-Inspired Transportation Network for Scalable Swarm Foraging, Qi Lu, G. Matthew Fricke, Takaya Tsuno, and Melanie E. Moses, In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE Press, 2020.
LoCUS: A loss-tolerant volcano survey algorithm, Ericksen John, Abhinav Aggarwal, G. Matthew Fricke, and Melanie E. Moses, IEEE Robotics and Computing Conference (IRC) (2020)
Ignorance is Not Bliss: An Analysis of Central-Place Foraging Algorithms, Abhinav Aggarwal, Diksha Gupta, William F. Vining, G. Matthew Fricke, and Melanie E. Moses, In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE Press, 2019. Paper PDF, Presentation PDF
Comparing physical and simulated performance of a deterministic and a bio-inspired stochastic foraging strategy for robot swarms, Lu, Qi, Antonio D. Griego, G. Matthew Fricke, and Melanie E. Moses., In 2019 IEEE/RSJ International Conference on Robotics and Automation, IEEE Press, 2019.
Brief Announcement: On Site Fidelity and the Price of Ignorance in Swarm Robotic Central Place Foraging Algorithms, Abhinav Aggarwal, G. Matthew Fricke, Diksha Gupta, and Melanie Moses. In Symposium on Principles of Distributed Computing (PODC), ACM Press, 2019, https://doi.org/10.1145/3293611.3331572. PDF
A Distributed Deterministic Spiral Search Algorithm for Swarms. G. Matthew Fricke, Joshua P. Hecker, Antonio D. Griego, Linh T. Tran, and Melanie Moses. In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE Press, 2016. . PDF
Distinguishing Adaptive Search From Random Search in Robots and T cells, G. M. Fricke, J. P. Hecker, S. R. Black, J. L. Cannon, M. E. Moses, in Proceedings of the Conference on Genetic and Evolutionary Computation, Association for Computing Machinery, 2015.
From Microbiology to Microcontrollers: Robot search patterns inspired by T cell movement, G. Matthew Fricke, Francois Asperti-Boursin, Joshua P. Hecker, Cannon Judy L., and Melanie E. Moses. Proceedings of the 12th European Conference on Artificial Life, The MIT Press, 2013. Paper
How Ants Turn Information into Food, T. Paz Flanagan, K. Letendre, W. Burnside, G. M. Fricke, M. Moses, in IEEE SSCI 2011 - Symposium Series on Computational Intelligence - IEEE Symposium on Artificial Life (2011), pp. 178–185. PDF
Emergent Representation in a Robot Control Architecture, Claiborne, Andy., Fricke, G. Matthew., Lopes, L., Lewis, Joseph., and Luger, George, UNM-NASA PURSUE Conference, (2000).
John Ericksen, PhD Dissertation, Drone Strategies for Volcano Surveys., Current.
J. Jake Nichol, PhD Dissertation, Climate Model Reconciliation with Machine Learning., Current.
Jannatul Ferdous, PhD Dissertation, Scalable Immune Systems., Current.
Humayra Tasnim, PhD Dissertation, Insight Into Complexity: Novel Information Theoretic Analysis of Spatiotemporal Interactions, 2024. PDF
Quincy Wofford, MS Thesis, Performance Predictable Application Platforms for Distributed Computing, 2020.
Swarmathon Rovers with Mounted Grippers
Swarmathon Tutorial Release 0.2.1 (MP4)
PowerSearch3D Videos (MP4)
Pneumatic Gripper Trials
Gripper Mockup Video (MP4)
Pogonomyrmex Rugosus
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Ant Colony Algorithms (ACOs) are used in shortest-path problem domains such as chip design and network routing. We investigated how three species of the desert harvester ant (Pogonomyrmex Rugosus, Maricopa, and Desertorum) share information about their surroundings, especially with regard to the scaling of information sharing with colony size. This information was compared to computational models of various foraging strategies. |
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The iAnt uses search patterns inspired by Pogonomymex sp.
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BioNetGen: Biochemical reaction networks are central to understanding and influencing the operation of biological cells. GetBonNie (http://getbonnie.org) and BioNetGen (http://www.bionetgen.org) automate the development of reaction networks so that biologists can create and study detailed models of cellular biochemistry. Poster. Video.
Getting started with RuleBuilder
The streamlined latest version of RuleBuilder 2 is on GitHub. The original version of RuleBuilder 1 is also on GitHub.
T-Cell Targeting Infected Cell
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CemPro: Macrophages and T-cells communicate with one another at the cell surface through ligands and receptors. The proteins that form the ligands and receptors cluster during signaling. The mechanism for this clustering is unknown. |
We model proteins on the cell surface with a Metropolis Monte Carlo lattice and measure the conditions under which clustering occurs. We then bring two virtual cell membranes into contact and measure the cross membrane binding forces needed to cause protein phase separation. Paper in Biophysical Chemistry . PowerPoint Web Slideshow. PDF Slideshow.
KomPhy: Algorithms for reconstructing phylogenies from character sequences encounter enormous search spaces even for small numbers of taxa. Techniques are needed to speed up the exploration of these spaces so that larger problems can be approached. In the past neural networks have provided a framework for tackling complex problems very quickly. My thesis describes and tests a new neural network approach to phylogenetic reconstruction called KomPhy. Thesis. Slideshow . Software.
CultureAL: Semester project for David Ackley's Artificial Life course at UNM. CulturAL uses a very simple framework to explore the interaction of learned traits (directly and through peer emulation) and biological traits. Processes such as 'shielding' and the Baldwin Effect are explored. Learning in this model benefits the population as a whole through emulation but is counterproductive for the learner who is much better off copying others and procreating. The population as a whole evolved to minimize direct learning and maximize emulation of peers relying on the background mutation rate to produce enough 'learners' to feed the emulation strategy.. The most prevalent impact shared knowledge has on genetic evolution is shielding, which allows populations to survive that would otherwise die out and allows genetic mutation to explore the fitness landscape with more freedom. Presentation .
Madcat: Extension of the Copycat AI framework to a robotic path finding problem which formed the basis of Joseph Lewis' PhD. Starcat is Joseph's current research. Madcat NASA Student Conference Paper .
NASA Autonomous Control Engineering .
Facebook: https://facebook.com/gmfricke
YouTube channel: https://www.youtube.com/user/MatthewFricke
Google scholar profile: https://scholar.google.com/citations?user=hdPxTWwAAAAJ&hl=en
Pretty Good Privacy Email Key: http://fricke.co.uk/pgppublickey.txt
I am a research faculty member at the University of New Mexico Computer Science Department. I am also the Software Lead for the UNM-NASA Swarm Robotics Challenge: nasaswarmathon.com.
BA in Anthropology from Appalachian State University.
BS in Math from the University of New Mexico.
MS in Computer Science from the University of New Mexico.
PhD in Computer Science from the University of New Mexico.
My wife, Suzanne, and I have four boys: Henry, Leo, Owen, and Tristan. We live in Albuquerque, New Mexico, USA. I was born and raised in Shrewsbury, UK, but have lived in Mount Airy, North Carolina and Albuquerque, New Mexico for most of my life. I have been interested in computers since playing with a Commodore 64 when I was ten years old.
Go Figure Software is my contracting company. Through Go Figure Software I have provided programming services to scientists at the UNM Physics Department and Los Alamos National Labs.
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Charles Darwin's Childhood Home
