The Use of Implanted Intramuscular FES System for Ameliorating Foot Drop During Locomotion
Undergraduate Research Thesis, Georgia Institute of Technology
Curriculum Vitae
Education
M.S.E. in Biomedical Engineering, Johns Hopkins University, 2019
Focus: Diagnostic medical imaging, computational modeling, and systems bioengineering.B.S. in Biomedical Engineering, Highest Honor, Georgia Institute of Technology, 2016
Focus: Biomechanics, biotransport, and physiological systems modeling.
Certifications and Awards
- Project Management Professional (PMP) — Project Management Institute (2025)
- ISTQB Certified Test Automation Engineer (CTAL-TAE) — International Software Testing Qualifications Board (2025)
- ISTQB Certified Tester Foundation Level v4.0 (CTFL) — International Software Testing Qualifications Board (2024)
- Engineer-In-Training (EIT), Chemical Engineering Discipline — Maryland State Board for Professional Engineers (2021)
- Certified Six Sigma Yellow Belt (CSSYB) — American Society for Quality (ASQ, 2020)
- Mobile Atlanta Scholarship — Georgia Institute of Technology (2015)
Technical Competencies
Biomedical Engineering:
Medical imaging systems, diagnostic imaging pipelines, CT image reconstruction (FBP, PL), biophysical modeling, medical device design, process validation, and systems verification.Software and Automation:
Python (Pytest, Selenium, Pandas, NumPy, API integration), SQL, XML, MATLAB, LabVIEW, C++, Git, and CI/CD workflows for software validation and regression testing.Data Engineering and Computational Tools:
Data acquisition and transformation (ETL pipelines), statistical analysis, modeling and simulation of biological systems, and data visualization.Hardware and Laboratory Systems:
Automated manufacturing systems (cartoning, filling, labeling), instrumentation calibration, histological analysis, microscopy, flow cytometry, and 3D printing for anatomical modeling.
Work Experience
Software Test Engineer, Adaptix Imaging — Oxford, United Kingdom
October 2022 – Present
- Develop and maintain automated test frameworks for validating X-ray imaging software and hardware.
- Design Python-based UI testing tools to streamline verification workflows and ensure compliance with ISO 13485 and IEC 62304 standards.
- Collaborate with interdisciplinary teams to support software and hardware validation activities.
- Conduct system verification and validation testing across embedded hardware and software subsystems.
Software Applications Engineer, Informetric Systems Inc — New Providence, NJ
January 2020 – August 2022
- Gathered, analyzed, and mapped user and process requirements into configurable automation logic for InfoBatch manufacturing systems, driving digital transformation and process optimization for pharmaceutical clients.
- Developed, tested, and validated 5 software updates and hotfixes for InfoBatch and managed the software release and product launch of InfoLog, including setup of VM-based test environments, creation of installation packages using Advanced Installer, and design of new automated test procedures.
- Provided high-level technical support to resolve complex issues (e.g., HTML report formatting, delayed data uploads, printer integration) — ensuring system uptime, customer satisfaction, and operational continuity.
- Collaborated with software developers, QA, and client engineering teams to align requirements and deliver robust, production-ready solutions.
Pharmaceutical Engineer, Aphena Pharma Solutions — Easton, MD
January 2020 – February 2021
- Authored and executed 30+ validation protocols and reports (IQ/OQ/PQ), commissioning 8+ automated systems — including blending tanks, labeling machines, water purification units, and serialization equipment — under FDA cGMP and engineering validation standards.
- Designed and optimized 5+ manufacturing and lab-scale processes using engineering design principles and data-driven analysis, improving process efficiency and product consistency.
- Implemented CAPA and preventive maintenance programs, driving equipment reliability, reduced downtime, and cost efficiency.
- Collaborated with R&D, QA, and manufacturing teams to implement engineering process improvements, ensuring compliance with regulatory and technical standards.
Research Experience
Research Assistant, Advanced Imaging Algorithms & Instrumentation Lab — Johns Hopkins University
April 2018 – December 2019
- Designed and analyzed 3D-printed anthropomorphic phantoms to evaluate CT imaging system performance.
- Modeled image quality metrics for CT scanners and optimized imaging parameters for texture perception studies.
- Processed raw projection data using FBP and penalized-likelihood (PL) reconstruction algorithms.
- Modeled optical setups for Fourier ptychography microscopy and analyzed imaging performance via Fourier domain analysis.
- Supervisor: Prof. Joseph Webster Stayman, Ph.D.
Research Assistant, Myocarditis Lab — Johns Hopkins University
December 2017 – April 2018
- Assisted in rodent surgery and conducted molecular biology assays (PCR, ELISA, Western blot, flow cytometry).
- Evaluated cardiac histology samples and annotated tissue morphology for quantitative analysis.
- Applied ANCOVA to assess immune response variations in myocarditis models.
- Supervisor: Prof. Daniela Čiháková, M.D., Ph.D.
Research Assistant, Laboratory of Computational Motor Control — Johns Hopkins University
September 2017 – December 2017
- Designed robotic manipulandum experiments to model wrist motor adaptation and neural feedback control.
- Analyzed force adaptation and error-clamp trials to investigate separation of holding vs. movement neural circuits.
Research Assistant, Neurophysiology Laboratory — Georgia Institute of Technology
September 2013 – July 2017
- Developed an implantable intramuscular FES system to mitigate foot drop using closed-loop control algorithms.
- Simulated neuromechanical responses using NEUROMECHANIC software to predict muscular feedback.
- Collected and analyzed kinematic data from feline locomotion experiments with Vicon and MATLAB.
- Conducted survival surgeries (FHL reinnervation) under supervision of Prof. T. Richard Nichols, Ph.D.
Coursework
Mechanical Modeling and Design of Biological Systems
- EN.580.642 Tissue Engineering: design of biological tissue substitutes and applications of stem cells.
- BMED 3310 Biotransport: fundamentals of momentum, heat, and mass transfer in biological systems.
- BMED 3400 Introduction to Biomechanics: deformable bodies, kinetics, dynamics, and statics.
- BMED 4758 Biosolid Mechanics: mechanical modeling of biological tissues.
- BMED 2210 Conservation Principles in BME: systems thinking and model-based reasoning.
- PHYS 2211/2212 Intro to Physics I & II: mechanics, electromagnetism, and modern physics.
- Calculus I–III, Differential Equations, Linear Algebra.
- ECE 3710 + 3741 Circuit Design and Lab.
Chemistry
- CHEM 3511 A Survey of Biochemistry.
- CHEM 2380 Synthesis I Laboratory.
- CHEM 2311/2312 Organic Chemistry I & II.
- MSE 2001 Principles and Applications of Engineering Materials.
- CHEM 1211/1212 Inorganic Chemistry I & II.
Biomedical Engineering Design and Problem Solving
- BMED 2310 Introduction to Biomedical Engineering Design.
- BMED 4602 Capstone Design: Developed a wearable system to enhance surgeon comfort; led project planning, regulatory pathway analysis, and prototype validation.
- BMED 1300 Problems in Biomedical Engineering.
Physiology
- BMED 3600 Physiology of Cell and Molecular Systems.
- BMED 3100 System Physiology.
- EN.580.418 Principles of Pulmonary Physiology.
Statistics, Computational Modeling, and Applications
- BMED 2400 Introduction to Bioengineering Statistics.
- BMED 3520 Biomedical Systems and Modeling.
- EN.580.439 Models of the Neuron.
- EN.580.429 Systems Bioengineering III.
- EN.580.430 Systems Pharmacology and Personalized Medicine.
- EN.580.428 Systems Bioengineering I (Data Science & Computational Medicine).
Publications
Performance Assessment of Texture Reproduction in High-Resolution CT
Assessment of computed tomography (CT) images can be complex due to a number of dependencies that affect system performance. In particular, it is well-known that noise in CT is object-dependent. Such object-dependence can be more pronounced and extend to resolution and image textures with the increasing adoption of model-based reconstruction and processing with machine learning methods. Moreover, such processing is often inherently nonlinear complicating assessments with simple measures of spatial resolution, etc. Similarly, recent advances in CT system design have attempted to improve fine resolution details - e.g., with newer detectors, smaller focal spots, etc. Recognizing these trends, there is a greater need for imaging assessment that are considering specific features of interest that can be placed within an anthropomorphic phantom for realistic emulation and evaluation. In this work, we devise a methodology for 3D-printing phantom inserts using procedural texture generation for evaluation of performance of high-resolution CT systems. Accurate representations of texture have previously been a hindrance to adoption of processing methods like model-based reconstruction, and texture serves as an important diagnostic feature (e.g. heterogeneity of lesions is a marker for malignancy). We consider the ability of different systems to reproduce various textures (as a function of the intrinsic feature sizes of the texture), comparing microCT, cone-beam CT, and diagnostic CT using normal- and high-resolution modes. We expect that this general methodology will provide a pathway for repeatable and robust assessments of different imaging systems and processing methods.
The Use of 3D-Printed Phantoms for Evaluating CT Image Quality
Master’s Research Thesis, Johns Hopkins University
Talks
Conference Presentations
Conference Presentation
Verifying performance and safety is critical, but has been a bottleneck in the medical software release process. UI software testing, being the most complex and integrated component, has traditionally been tested manually. Because the UI software is constantly updated, building automated UI testing solutions (TAS) for continuous verification offers significant benefits — reducing manual labor and human errors, enabling early detection of software issues, and strengthening the robustness of the development lifecycle.
This presentation introduces a **readable and maintainable Python-based automation framework** for medical imaging applications that emulates user interactions, communicates with external web APIs, performs data validation, records test evidence, and generates comprehensive test reports.
Presentations & Posters
RSLondon Southeast, Imperial College London — Best Poster Award
Developed an automated UI software testing framework designed for medical imaging applications. Presented as a technical poster at RSLondon Southeast and recognized with the **Best Poster Award** for innovation in healthcare software testing and automation.
Teaching
Calculus 1 & 2 Teaching Assistant
Served as a Teaching Assistant for Calculus 1 and 2 from 2013 to 2016, leading recitation sessions to help students master derivatives, integration, and advanced calculus concepts. Provided guidance, answered questions, and facilitated problem-solving to enhance student understanding and performance.
Service and Leadership
- Presented award-winning poster on Automated UI Software Testing for Medical Imaging at RSLondon Southeast, Imperial College London.
- Active contributor to healthcare software QA and automation communities.