Erica Waters

University of Pennsylvania, PhD in Mechanical Engineering and Applied Mechanics

Aug. 2021 - Dec. 2026

• Dissertation: Leveraging Robot-Based Haptic Dyads to Improve Community-Based Stroke Rehabilitation

• Advisor: Michelle Johnson, PhD

• Fellowships: NIH F31 Predoctoral Fellowship, NSF Graduate Research Fellowship

• Special Programs: Center for Neuroscience and Society Graduate Fellows Program , Center for Excellence in Teaching and Learning Graduate Teaching Certificate Program, Applying Your Thesis to the Real World graduate course

University of Tennessee, BS in Mechanical Engineering

Aug. 2017 - Dec. 2020

• Capstone Project: Myoelectric 3D-Printed Hand/Wrist Prosthesis; sponsored by Choice Orthotics & Prosthetics (Presentation)

• Extracurriculars: VP and co-founder of Life Without Limits student group to design 3D-printed assistive devices; First-year student mentor in the Society of Women Engineers; Peer mentor to students with intellectual and developmental disabilities in the FUTURE Program; Member of the Chancellor’s Honors Program, Member of the Grand Challenge Scholars Program

Rehabilitation Robotics Lab, GRASP Lab, University of Pennsylvania

Aug. 2021 - Present

Graduate Research Assistant

• Led development, integration, and clinical evaluation of human–robot interaction systems for neurorehabilitation, focusing on adaptive haptic feedback and multi-user interaction.

• Developed and deployed adaptive assistive and resistive feedback controllers for reconfigurable therapy robots.

• Designed and implemented IRB-approved clinical studies with older adults and adults with stroke (n = 50+).

• Led 150+ hours of clinical research, including clinical assessments, robot evaluations, and qualitative interviews.

• Built analysis pipelines (R, Python) for multimodal human data (sEMG, kinematics) using machine learning.

• Collaborated with clinicians (OT, PT, CRNP) to design protocols, interpret results, and ensure clinical relevance.

• Awarded NSF GRFP and NIH F31 on first submission; independently developed proposals and led reporting.

• Published 9 peer-reviewed papers (6 first-author) and presented work at engineering and clinical conferences.

Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania

Aug. 2022 - Dec. 2023

Graduate Teaching Assistant

• Led recitations and labs for graduate- and undergraduate-level students as TA for “Design of Mechatronic Systems” and “Introduction to Robotics.”

• Instructed graduate students in robotics through hands-on labs with the 7-DOF Franka Emika Panda Robot.

• Taught rapid prototyping, coding in C, feedback control, etc. through weekly recitations with 50+ students.

• Directed teams of 5-8 TAs, managed office hours, and facilitated robot competitions for 80+ students.

Behavior, Robotics, and Sensing Group, University of Tennessee

Feb. 2018 - Jan. 2020

Undergraduate Research Assistant

• Designed, implemented, and published a study relating human reaching behavior and self-reported confidence.

• Utilized the MotionMonitor Tracking System to obtain 3D motion capture data of goal-directed reaching.

• Trained a k-NN algorithm to classify reaches by participant confidence using kinematic features.

• Investigated physical communication during robot-mediated collaborative motor tasks to support post-stroke neurorehabilitation. Developed a novel dyadic training protocol using force-sharing with a human partner.

• Demonstrated feasibility and efficacy of bi-directional haptic feedback for motor learning in people with stroke; published the first implementation of robot-based haptic dyad for individuals with neurological impairments.

• Collaborated with a diverse team including clinicians (OT, PT, CRNP), game developers (enAble Games LLC), and startup stakeholders (Recupero Robotics LLC) on a longitudinal feasibility study.

• Designed and implemented adaptive controllers that enabled 12+ months of continuous deployment in a clinic; developed a pipeline for processing kinematic data; analyzed usability and acceptability of the robot gym.

• Designed an optimal control model of behavior in a robot-based tracking task.

• Utilized optimization techniques including least-squares and gradient descent to fit parameters, achieving high accuracy (R = 0.89) with potential to inform clinical motor and cognitive assessment tools.

• Used supervised machine learning techniques to predict post-stroke kinematic performance from clinical assessments and features derived from CT scans.

• Developed an elastic net regression model to predict post-stroke reaching kinematics from brain lesion metrics (R² = 0.41), demonstrating feasibility of CT-based functional prediction.

• E. L. Waters, N. Y. Meng, N. Stroutinky-Sobotka, F. S. Shofer, P. Z. Cacchione, R. J. Mendonca, and M. J. Johnson, “Haptic Connection to a Partner Enhances Motor Learning in Older Adults: Implications for Multiplayer Robotic Exercise and Rehabilitation”, [IEEE Transactions on Neural Systems and Rehabilitation Engineering , Under Review].

• R. M. Azar*, E. L. Waters*, J. Opong-Duah, P. Z. Cacchione, and M. J. Johnson, “Towards Neuro-Informed Robotic Rehabilitation: Structural Imaging Predicts Post-Stroke Performance on Robot-Based Assessments”, [In Preparation]. (*Indicates equal contribution)

• E. L. Waters and M. J. Johnson, “Motor Learning in Robot-Based Haptic Dyads: A Review,” in IEEE Transactions on Haptics, vol. 17, no. 4, pp. 510-527, Oct.-Dec. 2024, doi: 10.1109/TOH.2024.3379035.

• R. M. Azar*, E. L. Waters*, J. Opong-Duah, P. Z. Cacchione, and M. J. Johnson, “Modeling Post-Stroke Motor Behavior from Structural Lesion Networks: A Preliminary Study With Robot-Based Assessments,” 2025 12th International IEEE/EMBS Conference on Neural Engineering (NER), San Diego, CA, USA, 2025, pp. 71-76, doi: 10.1109/NER61569.2025.11589029. (*Indicates equal contribution)

• E. L. Waters and M. J. Johnson, “Can an Optimal Control Model Capture Tracking Kinematics? Insights from Healthy and Post-Stroke Robot Interactions,” 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Copenhagen, Denmark, 2025, pp. 1-7, doi: 10.1109/EMBC58623.2025.11252623.

• J. Opong-Duah, A. Mittal, E. L. Waters, F. Sayani, S. Sall, F. S. Shofer, and M J. Johnson, “Robotic Assessment of Cognitive and Motor Impairment in Adults with Sickle Cell Disease,” 2025 International Conference On Rehabilitation Robotics (ICORR), Chicago, IL, USA, 2025, pp. 1793-1798, doi: 10.1109/ICORR66766.2025.11063212.

• E. L. Waters, R. M. Azar, J. Opong-Duah, S. Gaardsmoe, A. Johnson; R. J. Mendonca, P. Z. Cacchione, and M. J. Johnson, “Towards an Optimal Model of Post-Stroke Sensorimotor Control,” 2025 International Conference On Rehabilitation Robotics (ICORR), Chicago, IL, USA, 2025, pp. 1313-1319, doi: 10.1109/ICORR66766.2025.11063066.

• N. Y. Meng*, E. L. Waters*, G. Lin, S. Gaardsmoe, A. Johnson; L. A. Hallock, R. J. Mendonca, P. Z. Cacchione, and M. J. Johnson, “Analysis of Induced Muscle Activations by an Affordable, Reconfigurable Robot for Comprehensive Post-Stroke Rehabilitation,” 2025 International Conference On Rehabilitation Robotics (ICORR), Chicago, IL, USA, 2025, pp. 1361-1367, doi: 10.1109/ICORR66766.2025.11063060. (*Indicates equal contribution)

• E. L. Waters, R. J. Mendonca, P. Z. Cacchione and M. J. Johnson, “TheraDyad: Feasibility of an Affordable Robot for Multi-User Stroke Rehabilitation,” 2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), Heidelberg, Germany, 2024, pp. 1498-1503, doi: 10.1109/BioRob60516.2024.10719912.

• E. Waters and E. Wade, “Classification of Task-Specific Confidence from Kinematic Features,” 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER), Italy, 2021, pp. 757-762, doi: 10.1109/NER49283.2021.9441448.

• E. Waters and E. Wade, “Self-Efficacy and Kinematics: Establishing a Relationship between Kinematics and Task Challenge of a Goal Directed Reaching Task in Unimpaired Adults,” 2019 IEEE Symposium Series on Computational Intelligence (SSCI), Xiamen, China, 2019, pp. 1146-1153, doi: 10.1109/SSCI44817.2019.9003072.

• Biomechanics: Human Modeling, Kinematic Analysis

• Robotics: Machine Learning, Robotics, Haptics, Control Systems, Microcontrollers (Arduino, Teensy)

• Programming: Python (NumPy, SciPy, Pandas, Scikit-learn, etc.), R (R Studio), MATLAB, C/C++, C# (Unity)

• Mechanical Design: CAD (SolidWorks, OnShape), Rapid Prototyping (3D printing, laser cutting)

• Scientific Thinking: Experimental Design (protocol writing, hypothesis generation, group assignment), Analysis (statistical analysis, figure design)

• Study Administration: Research Ethics (IRB compliance, informed consent), Data Collection (REDCap, clinical assessment, user-experience surveys, interviews)

• Dissemination: Writing (grant proposals, research publications), Presentation (oral presentation, poster presentation)

• Teamwork: Communication, Collaboration, Mentorship, Leadership

• Administrative: Time Management, Organization

• Rehabilitation Robotics Lab (2021-2026): Supervised research projects for 15+ students, ranging from high school to graduate school, with a focus on research pipeline programs. Mentees have presented at program closing ceremonies, Penn Medicine PM&R Research Week, and Penn Global Health Day.

• Free Library of Philadelphia (2026): Designed and led a two-part afterschool robotics outreach workshop for ~40 K-12 students at the Roxborough Library Branch. (Read More)

• Franklin Institute (2025): Designed and led an afterschool robotics and biosensing outreach workshop for ~15 high school students at a science museum in Philadelphia. (Read More)

• Penn GEMS Engineering Camp (2022-2023): Designed and led an engineering design workshop for middle school students as part of a summer STEM outreach camp. (Read More)

• Panelist: Penn Graduate Women In Science and Engineering Research Panel (2025), GRASP External Review PhD Panel (2024), GRASP on Robotics Seminar (2023, 2024)

• Poster Judge: Penn Engineering Research Experiences for Undergraduates Symposium (2024)

• Tour Guide: GRASP Lab Tours (2021-2026), Penn Medicine PM&R Research Week Lab Tour (2024), IEEE International Conference on Robotics & Automation Rehabilitation Robotics Lab Tour (2023)

• Journal: IEEE Robotics and Automation Letters (2026)

• Conference: International IEEE/EMBS Conference on Neural Engineering (2025), International Conference On Rehabilitation Robotics (2025), International Conference for Biomedical Robotics and Biomechatronics (2024)

• American Congress of Rehabilitation Medicine (ACRM), Early Career Member, 2026-Present

• International Consortium for Rehabilitation Robotics (ICORR), Graduate Student Member, 2024-Present

• IEEE Robotics and Automation Society, Graduate Student Member, 2024-Present

• IEEE Engineering in Medicine and Biology Society, Graduate Student Member, 2024-Present

F31 Predoctoral Fellowship, Eunice Kennedy Shriver National Institute of Child Health and Human Development (Read More)

Aug. 2024 - Dec. 2026

Awarded $144,000 to support dissertation research; competitive fellowship funding fewer than 30% of applicants; designated principal investigator

Next Gen Presenter Program, American Congress of Rehabilitation Medicine (Read More)

Oct. 2026

Selected for the 2026 ACRM Annual Conference & Expo Next Gen Presenter Program, a professional development initiative for early-career rehabilitation researchers designed to support conference presenters

President Gutman Leadership Award, University of Pennsylvania (Read More)

Aug. 2025

Awarded $1,000 to support international conference presentation; competitive travel award for eligible graduate and professional students

Graduate Research Fellowship, National Science Foundation (Read More)

Aug. 2021 - May 2024

Awarded $138,000 to support graduate research and education; competitive fellowship awarded to ≈ 15% of over 12,000 applicants annually