About Me

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I am an aspiring roboticist and current robotics PhD graduate student working with Dr. Egerstedt in the GRITS lab at Georgia Tech. I moved to Atlanta in July 2011 after working for almost 3 years at MIT Lincoln Laboratory where I worked on radar signal processing, tracking, and classification. Before that I received my BS and MS in electrical engineering (emphasis in control theory) from the ECE department at UCSB. My current research focuses on the overlap between Control Theory and Machine Learning and its applications to mobile robotic systems.


Georgia Institute of Technology. PhD in Robotics. Focus in Control Theory, Machine Learning, and Mechanics. Aug 2011 – Present.

University of California, Santa Barbara. Master of Science in Electrical Engineering. Major in Control Theory. Minor in Scientific Computation.
 GPA: 3.78. Jan 2007 – Jun 2008.

University of California, Santa Barbara. Bachelor of Science in Electrical Engineering. Emphasis in Communication, Control, and Signal Processing.
 Graduated with high honors. GPA: 3.76. Sep 2002 – Jun 2007.

Tohoku University. Sendai, Japan. Engineering study abroad program. Research focused on robotics. Coursework included Fourier analysis, numerical methods, and mechanical engineering in addition to Japanese language and culture. Jul 2005 – Aug 2006.


Rowland O’Flaherty and Magnus Egerstedt. Learnability for Dynamical Systems. 21st International Symposium on Mathematical Theory of Networks and Systems, July 2014.

Rowland O’Flaherty and Magnus Egerstedt. Learning to Locomote: Action Sequences and Switching Boundaries. 9th IEEE International Conference on Automation Science and Engineering, August 2013. Best paper finalist

Paul Backes, Rowland O’Flaherty, Daniel Helmick, Won Kim, Paulo Younse, Anthony Ganino. Tube Transfer Using the Sampling Arm for Mars Sample Caching. The International Conference for Aerospace, 2014 IEEE International Conference. March 2014

Rowland O’Flaherty, Peter Vieira, M.X. Grey, Paul Oh, Aaron Bobick, Magnus Egerstedt, and Mike Stilman. Humanoid Robot Teleoperation for Tasks with Power Tools. Proc. 5th IEEE International Conference on Technologies for Practical Robot Applications, 2013.

Rowland W. O’Flaherty, Ricardo G. Sanfelice, and Andrew R. Teel. Robust global swing-up of the pendubot via hybrid control. Proc. 27th American Control Conference, 1424–1429, 2008. PDF

Current & Previous Work:

Research Assistant in GRITS Lab at Georgia Tech. August 2011 – Present.

Work focuses on the overlap between Control Theory and Machine Learning and applications to mobile robotic systems. Past Work:

Intern at Jet Propulsion Laboratory. June 2013 – August 2013

Developed control algorithms for manipulation of a 5 degree-of-freedom robotic arm used for testing the capabilities of sample acquisition and caching for a proposed Mars mission.

MIT Lincoln Laboratory Staff Member. November 2008 – July 2011.

Work focuses on developing a classification algorithms and feature-aided tracker for radar detections from an airborne platform. Graduate student research. Department of Electrical and Computer Engineering, UCSB. Summer 2007 – Spring 2008.

Developed a graphical user interface that automatically defines and simulates a hybrid system upon analysis of specific system constraints. Designed a hybrid control algorithm, translated it into C and Matlab code, and compiled/developed the software interface that globally stabilizes a double link pendulum robot arm from any initial condition to the unstable upright position. Video. International student research. Department of Electrical Engineering, Tohoku University. Fall 2005 – Summer 2006.

Designed a control algorithm, translated it into C++ code, and compiled/developed the software interface to allow a robotic arm to catch a ball that is thrown toward it at an arbitrary speed/trajectory. Video. Online Editor for Design World magazine. September 2006 – June 2007.

Created SolidWorks models, posted and edited online articles, and managed team members.

Teaching Experience:

Georgia Tech ECE Teaching Assistant for Senior Design Course (Fall 2011 – Spring 2012). UCSB ECE Teaching Assistant for Signal Analysis (Summer 2007). UCSB ECE Teaching Assistant for Circuit, Devices, and Systems (Summer 2007).


Vice President of Georgia Tech Robotics Graduate Study Organization (RoboGrads) (Spring 2012 to Spring 2014)

Volunteer Outreach:

FIRST Tech Challenge Mentor Arlington High School (Fall 2009 – Spring 2011). MIT Product Engineering Processes Mentor (Fall 2010). Civil Air Patrol Member (Fall 2010 – Summer 2011). Awards and Honors:

Georgia Tech Presidential Fellowship, Fall 2011 – Spring 2015 Engineering Dean’s Honor List, every quarter. Tau Beta Pi (Engineering Honors Society) member, Spring 2005 – present. Bridging Scholarship Recipient, Fall 2005.


MATLAB, SIMULINK, C++, C, Python, HTML, Visual Basic, AppleScript, and Bash script.


SolidWorks, Apple Xcode, Microsoft Office.


Flying single engine airplanes, FIRST Tech Challenge mentoring, Arduino, Robotics, RC planes, cycling, scuba diving, traveling, backpacking, ultimate frisbee, Japanese.

Relevant Robotics Graduate Courses:

Georgia Tech Courses:

  • Optimal Control (Spring 2013) – Discuss the underlying principles in the theory and applications of optimization and optimal control of systems
  • Nonlinear Control (Spring 2013) – Nonlinear control deals with the analysis and control of systems that are nonlinear, time-varying, or both
  • Robot Planning (Fall 2012) – Discuss algorithms for robots and other complex systems that make intelligent decisions in high dimensional or continuous spaces of options.
  • Mechatronics (Fall 2012) – Mechatronics is the synergistic combination of precision mechanical engineering, electronic control, and systems thinking in the design of products and manufacturing processes.
  • Theoretical Statistics (Fall 2012) – Rigorous introduction to theory of statistical inference. Construction and assessment of estimators and tests. Fundamentals of decision theory, minimax, and Bayes Paradigms.
  • Robot Mechanics (Spring 2012) – Presents an introduction to the kinematics, dynamics, and control of serial robotic manipulators.
  • Artificial Intelligence (Spring 2012) – Presents concepts, representations, and techniques used in building practical computational systems (agents) that appear to display artificial intelligence (AI), through the use of adaptive information processing algorithms.
  • Network Control (Fall 2011) – Provide an overview of the tools and techniques that have proven instrumental for studying networked control systems, which consists of a set of dynamical units that interact over a signal exchange network for its coordinated operation and behavior.
  • Intro To Robotics Research (Fall 2011) – Familiarizes students with the core areas of robotics; mechanics, control, perception, AI, autonomy, and human-robot interaction. Provides an introduction to the mathematical tools required in robotics research.

MIT Courses

  • Underactuated Robotics (Spring 2011) – Introduces nonlinear dynamics and control of underactuated mechanical systems, with an emphasis on computational methods. Topics include the nonlinear dynamics of robotic manipulators, applied optimal and robust control, motion planning, and reinforcement learning.
  • Machine Learning (Fall 2010) – Introductory course on machine learning which gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks.

UCSB Courses

  • System Identification For Control (Winter 2008) – On-line identification of continuous- and discrete-time systems. Linear parameterizations. Continuous gradient and least squares algorithms. Stability, persistent excitation and parameter convergence. Robust algorithms for imperfect models. Averaging. Discrete-time equation-error identifiers.
  • Linear Systems I & II (Fall 2007 and Winter 2008) – Introduction into modern linear systems theory: stability, controllability, observability, realization theory, state feedback, state estimation, separation theorem, LQR/LQG, feedback stabilization, etc.
  • Noncooperative Game Theory (Fall 2007) – Teaches how to formulate problems as mathematical games and provide the basic tools to solve them. The course covers: Static games, starting with two-player zero-sum games and eventually building up to n-player non-zero sum games. Saddle-points, Nash equilibria, and Stackelberg solutions will be covered; Dynamic optimization (dynamic programming) for discrete and continuous time; Dynamic games, both open and closed-loop policies. Saddle-points and Nash equilibria will be covered.
  • Matrix Analysis (Fall 2007) – Graduate level-matrix theory with introduction to matrix computations. SVD’s, pseudo-inverses, variational characterization of eigenvalues, perturbation theory, direct and iterative methods for matrix computations.
  • Hybrid and Switched Systems (Spring 2007) – provides an introduction to hybrid control. We start by presenting a modeling framework for hybrid systems that combines elements from automata theory and differential equations. The students are then guided through a set of techniques that can be used to analyze and design hybrid control systems. The course also includes an overview of simulation tools for hybrid systems with emphasis on Simulink/Stateflow, SHIFT, and Modelica.
  • Numerical Simulation And Analysis (Winter 2007) – Development of modern numerical methods for ordinary differential equations including Runge-Kutta and multistep. Convergence, order and stability analysis. Concepts and capabilities of mathematical software
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