About Me
I am a robotics enthusiast with 4 years of experience as a software engineer using C++ to develop consumer robotics products. I have a strong background in medical device design and robotics principles and am seeking opportunities to design mechatronic solutions to complex problems, particularly by using humanoid robots to advance the medical, industrial, and consumer fields.
I earned my BS in Biomedical Engineering from the Johns Hopkins University and my MS in Robotics from the University of Michigan in Ann Arbor. I am well versed in Mechanical, Electrical, and Software Engineering principles and have improved patient care by integrating novel technological advancements into conventional medical standards. For example, I developed needle holders compatible with a steady-hand robot to reduce innate tremors in a surgeon’s hand during vein anastomoses procedures. I also used SolidWorks to design a 3-DOF robotic catheter system allowing an operator to remotely perform cardiac ablations under MR imaging. I worked in two startup companies: one where I developed endotracheal tubes that provide a more secure hold on the trachea through an improved cuff design, and another where I built a prosthetic hand assessment method (PHAM) capable of training upper-limb amputees to better control their prosthetic hands and evaluating those movements by gathering IMU data.
At iRobot, I designed algorithms to improve the Roomba's cleaning efficiency by using robust cleaning strategies and localization behaviors. I launched and improved the Roomba i3 robot over two years. The Roomba i3 did not have a camera and thus could not localize using our existing visual SLAM algorithms and supporting behaviors. This posed a unique challenge: how can a blind robot localize in a room? As the lead software engineer on the Roomba i3's localization and cleaning strategy team, I designed, implemented, tested, and refined a wall-following-based cleaning behavior that created physical landmarks for an obstacle-based SLAM algorithm that used trajectory matching to observe landmarks. The product performed better than the company anticipated, outperforming the higher-end Roombas in low light settings and allowing us to bring desirable features such as Directed Room Clean to our customers at a fraction of the cost. I am proud of what I accomplished and learned at iRobot and am ready to bring my experience to a new robotics team.
If you would like to connect, please reach out to me on LinkedIn or send me an email at [email protected].
I earned my BS in Biomedical Engineering from the Johns Hopkins University and my MS in Robotics from the University of Michigan in Ann Arbor. I am well versed in Mechanical, Electrical, and Software Engineering principles and have improved patient care by integrating novel technological advancements into conventional medical standards. For example, I developed needle holders compatible with a steady-hand robot to reduce innate tremors in a surgeon’s hand during vein anastomoses procedures. I also used SolidWorks to design a 3-DOF robotic catheter system allowing an operator to remotely perform cardiac ablations under MR imaging. I worked in two startup companies: one where I developed endotracheal tubes that provide a more secure hold on the trachea through an improved cuff design, and another where I built a prosthetic hand assessment method (PHAM) capable of training upper-limb amputees to better control their prosthetic hands and evaluating those movements by gathering IMU data.
At iRobot, I designed algorithms to improve the Roomba's cleaning efficiency by using robust cleaning strategies and localization behaviors. I launched and improved the Roomba i3 robot over two years. The Roomba i3 did not have a camera and thus could not localize using our existing visual SLAM algorithms and supporting behaviors. This posed a unique challenge: how can a blind robot localize in a room? As the lead software engineer on the Roomba i3's localization and cleaning strategy team, I designed, implemented, tested, and refined a wall-following-based cleaning behavior that created physical landmarks for an obstacle-based SLAM algorithm that used trajectory matching to observe landmarks. The product performed better than the company anticipated, outperforming the higher-end Roombas in low light settings and allowing us to bring desirable features such as Directed Room Clean to our customers at a fraction of the cost. I am proud of what I accomplished and learned at iRobot and am ready to bring my experience to a new robotics team.
If you would like to connect, please reach out to me on LinkedIn or send me an email at [email protected].