Supporting the verification of the Ottava Apollo system-level design input requirements.

• Tuned two feedback controllers using MATLAB’s root locus tool for sensing contact and modulating grasping forces between two soft robotic manipulators and a cylindrical object modeled in the PyBullet simulation environment by using a state machine to transition between a target action feedback controller to an error-based feedback controller once touch is detected. • Leveraging the Kalman filter to predict the future system state based on past estimations of two models, one for robust grasping and another for failed grasping due to slippage.

• Applying the Cognitive Load Theory (CLT) to analyze human mental workload during human-robot (HR) teaming in high-stress scenarios by capturing passive biosignals such as electrocardiogram, electrodermal activity, photoplethysmography, respiration, skin temperature, and pupillometry; Robot Operating System (ROS) time synchronizes all data. • Recruiting human subjects to use a VR environment simulating an extraterrestrial exploratory experience to establish a prioritized biosignal list for developing a live cognitive estimation model using a novel machine learning model to classify the physiological data output from collected data. The classifier will be embedded in an adaptive information system, the predicated cognitive state will modulate alert severity, and the efficacy of the HR team will be evaluated.

• Designed a manufacturing process for the Air Force Office of Scientific Research (AFOSR) that focuses on iterative physical properties to collect real-world data that will eliminate the need for simulations.• Used physical design optimization to prototype a quad-rotor drone, which will validate its fabrication and quantify both its performance and its failure risk by conducting physical tests of the prototypes.• Applied a weighted design guide to maximize data collection. For example, with software iterations requiring minor physical modification, the PDO process allows iterations through a spectrum of software parameters at a few minutes per cycle, while a separate set of physical frames is 3D printed and laser cut.

• Spearheading the R40 thermistor resistance test to better understand variability and improve repeatability to meet the critical patient safety specification for high-volume production. • Automated dry well, digital multimeter, and calibrator thermometer instruments to collect data in real-time by writing a Python script that exports to a .csv file for overlaying resistance and temperature graphs to determine stabilization time.

Research & Development Leadership Development Program (RDLDP)Biosense Webster, Inc. | NuVera Medical, Inc.Part of the Johnson & Johnson Family of Companies• Evaluated signal lines on multiple intra-cardiac echocardiography catheters for characterization of signal strength when migrating the low voltage differential signaling (LVDS) buffer circuit from the handle to the connector cable. • Interpreted oscilloscope data to determine that LVDS is functional with one or two cable buffers at the reusable connector cable; removing them from the disposable catheter provides a savings cost of $40 per catheter.

• Prototyped, manufactured, and tested tooling and fixtures such as tissue protectors, sewing templates, and calibration blocks to improve the efficiency of manufacturing procedures for pulmonary and aortic transcatheter heart valves. • Collected heart valve measurement data to develop an inspectional gauge to quickly determine whether valve assemblies met specification requirements. • Presented concepts to multiple engineering teams and technicians to receive feedback on areas of improvement such as biocompatibility, manufacturability, and feasibility.• Constructed engineering drawings, risk assessment forms, and biocompatibility evaluation results to ensure traceability and compliance of all tooling and fixtures.

• Assisted in advancing a consistent training testbed with the reliable classification of open surgery dexterity to facilitate the assessment, training, and maintenance of surgical competency by sensorizing surgical tools. • Determined the real-time tracking of surgical instrument pose by mounting a wireless inertial measurement unit (IMU) on needle driver and forceps to gather kinematic data utilizing Arduino 1.8.9 and Processing 3.5.3 software for mapping in neural networks. • Collaborated with the Cardiac Outcomes Research (CORE) Laboratory at the UCLA Medical Center to build upon a previous study that aimed to characterize Novice, Trainee, and Expert levels of surgical skill by having subjects perform sutures on synthetic material with sensorized tools.

• Designed “soft” actuators utilizing SolidWorks and 3D printing to implement in human-robotic devices such as a hand exoskeleton for assisting impaired stroke survivors with everyday hand functions, specifically a two-finger pinch grip. • Manufactured liquid elastomer actuators with carbon fiber and Kevlar thread reinforcements to aid flexion and extension trajectory during pneumatically powered actuation.• Adapted an innovative zero-volume method to increase efficiency and portability of a 16-gram CO2 cartridge pneumatic power source, resulting in 100 pinch grip motions per cartridge.

• Operated on a team of 20 members to design a senior project where we built and tested an internal combustion race car for the Society of Automotive Engineers (SAE) collegiate design competition series on an annual basis in Lincoln, Nebraska. • Spearheaded the research and assembling of vehicle sensors, controls, lights, batteries, and firewall to keep the vehicle functioning while extracting performance data and maintaining driver safety. • Utilized the Rapid Harness software to create organized wiring diagrams through color coded modules which facilitated team collaboration and expedited repairs. • Designed, manufactured, and tested the driver seat, steering column, clutch mount, and pedal box to improve the vehicle’s ergonomics which helped us place within the top 11 school in the Design Event during the 2018 FSAE competition. • Performed finite element analysis on SolidWorks to predict how our components would behave under stresses and vibrations before we began the manufacturing process. • Operated machining tools such as an angle grinder, drill, lathe, band saw, and computer numerical control (CNC) machines.