Contact

• Email radke@drx.cc
• Twitter @radke
• Resume drx.cc/cv
• Github github.com/drxcc

Objective

Design and build next generation autonomous solutions and tooling.

Profile

Dr. Aaron J. Radke has strong industry and academic experience with +20yr in physics, engineering, software, and computer science and +10yr in autonomous systems, and +5yr in machine learning and data science. He has worked in small startups and high profile government research organizations including the Navy, Department of Defense, NASA, and Lockheed Martin.

This broad blend of backgrounds involves him in project phases from design to implementation, test and deployment. Extended industry experience includes autonomous algorithm design in the areas of guidance, navigation, control, planning, anomaly detection, and machine learning.

His cross cutting involvement coupled with a data visualization workflow provides innovative solutions with custom design tools. His passion for tooling keeps him active in the open source community of computer languages, data science and visualization.

Senior Software Engineer @ CiBO Technologies 2018 - 2019 (1yr)

• Developed data science analytics and visualization tooling in Scala with a goal of accelerating research to deployment;
• Designed data science pipelines utilizing rigor in software with type systems, explanations with Bayesian mathematics, and repeatability with system tests;
• Deployed full stack product applications with integrated data science backends to an AWS based Kubernetes infrastructure.

Senior Research Analyst @ Metron Scientific 2014 - 2018 (4yr)

• Researched and developed streaming based machine learning algorithms for anomaly detection, classification and prediction algorithms with a focus on real time implementation in software and hardware for autonomous applications;
• Led vehicle health monitoring architecture, analysis and implementation for autonomous vehicles;
• Developed custom Post Mission Analysis PMA data visualization and analytics software for real-time exploration of extremely large data sets aggregated from navigation, telemetry, and logs;
• Designed and analyzed autonomous obstacle avoidance and optimal threat minimization algorithms;
• Created 3DOF underwater simulation and visualization environments for real time obstacle avoidance algorithm exploration, monte carlo validation, adversarial obstacle research;
• Wrote Navy and DOD SBIR proposals for machine learning and artificial intelligence applications;
• Developed and implemented real time navigation, avoidance and planning algorithms;
• Awarded research initiatives related to system/vehicle health monitoring and machine learning;
• Reviewed control design architectures for underwater autonomous vehicles.

Senior Control Systems Engineer @ Lockheed Martin 2009 - 2014 (5yr)

• Constructed 6DOF environment physics and rocket flight dynamics from first principles in Matlab/Simulink and C++;
• Designed complex guidance, navigation and control (GNC) algorithms and procedures meeting flight constraints and schedule adjustments;
• Developed custom software visualization tools for flight profile analysis, system integration validation and telemetry;
• Missile launch support and firing range telemetry analysis;
• Validated and tested flight algorithm software by software-in-the-loop (SWIL) and hardware-in-the-loop (HWIL) including Carco rate tables;
• Modeled statistical error bounds for Monte Carlo simulations to explore mission profiles and control stability and robustness;
• Constructed a local cloud simulation farm and wrote software to run and visualize simultaneous Monte Carlo simulations and reduce computing time from a month to several days;
• Linearized system dynamics and control for stability analysis;
• Conducted missile payload variations studies with 6DOF and Monte Carlo;
• Communicated mission progress and success with clear interactive documentation;
• Integrated hardware, firmware and embedded systems development to upgraded an inertial guided digital auto-pilot;
• Created a predictive control algorithm for a high altitude airship utilizing weather forecasts and atmospheric wind modeling;
• Ported legacy Fortan based 6DOF aerodynamic flight simulations to Matlab/Simulink.

Skills

• Special interest in functional programming with a solid +10yrs in Scala and interests in Haskel
• Broad interest in programming language paradigms from OO to FP with rich type systems and emerging languages such as Rust
• Industry language development in Java, C, and C++
• Scripting languages for system glue with Ruby, Bash, and Python and jvm variants (JRuby and IPython)
• Familiarity with machine learning tools with a focus on deployment in both embedded and big data applications with Apache Mahout and Spark
• Data science tooling integration with Python and R and notebook styles with Jupyter and Mathematica
• Generic engineering and mathematics tools with +15yr of industry use of Matlab, Simulink, Mathematica, MathCAD
• Broad cross platform development targets Linux/Unix (x86, arm), OSX, Windows (32b, 64b), JVM (v6-v12), ARM (32b, 64b), pic, Raspberry Pi, and Integrity rtos
• Experience with historic numeric simulation languages such as Fortran
• Web design and front end including modern tooling such as Scalajs, Typescript) and popular libraries D3js, Vega
• Visualization tools +10yrs in Processing, +6yrs d3, Inkscape SVG, +5yrs Drx
• Version control with +10yrs years of Git and experience with Clearcase and SVN
• Development tools +15yrs in Vim as well as IDE tools such as a InteliJ and vscode
• Cloud deployment to AWS with Docker and Kubernetes
• Open source contributions to scala visualization, tooling, Sbt plugins, vim plugins,
• Research into computer language, markup and visualization tooling with Aao, Convey, and Drx.

Publications

The following is a list of relevant publications including a patent, dissertation, thesis, conference papers and presentations:

• “‘Small Data’ Anomaly Detection for Unmanned Systems”, IEEE AUTOTESTCON, September 2018.
• “Anomaly Detection and Prognostics for Unmanned Systems Using Non-invasive Sensors”, SNAME Maritime convention, October 2018.
• “Typeclasses for Data Visualization”, North East Scala Symposium, March 18, Boston 2018. http://drx.cc/tviz
• “Convey: literal function literals”, Pittsburg TechFest Room 317, June 1, 2013 [Online] http://pghtechfest.com/speakers
• “Modern Science and Awe”, Insight February 24 2010
• “Truth and the Rise of Modern Science”, Insight February 23 2008
• Patent WO/2007/035559 “Controllers, Observers, and Applications Thereof”, 2007.
• “High Performance Tracking Control for the Practitioner”, Proc. of the 2007 American Control Conference July 11-13 2007.
• “Feed Forward Filters for State and Disturbance Estimation”, Proc. of 46th IEEE Conference on Decision and Control December 12-14 2007.
• “MEMS Gyroscope Rate Sensing with Disturbance Rejection Control”, Submitted to the 46th IEEE Conference on Decision and Control December 12-14 2007.
• “On Disturbance Estimation and Its Applications in Health Monitoring”, Ph.D. Dissertation, Cleveland State University December 2006.
• “A Novel Disturbance Estimation Algorithm for Health Diagnosis of Dynamic Systems”, 52nd International Instrumentation Symposium May 7-11 2006.
• “A Survey of State and Disturbance Observers for Practitioners”, Proc. of the American Control Conference ACC/IEEE June 14-16, 2006.
• “Discrete Implementation and Generalization of the Extended State Observer”, Proc. of the 2006 American Control Conference June 14-16, 2006.
• Review contributions for Dan Simon’s Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches, Wiley-Interscience, June 23 2006.
• “Commercialization of Advanced Control Technologies”, November 2005.
• “Edwin Abbot’s Flatland as a framework for teaching linear system concepts”, Cleveland State University Lecture April 2004.
• “A Java Based Interactive Control Design and Tuning Platform”, Masters thesis, Cleveland State University July 2003.