About Me
Innovative researcher and educator specializing in biomechanics, assistive technology, and rehabilitation engineering. Experienced in leveraging machine learning algorithms for control of myoelectric prosthetic hands and developing accessible technologies to enhance daily experiences for individuals with disabilities. Passionate about creating user-centered solutions through interdisciplinary collaboration, physical computing, and disability studies. Dedicated to mentoring the next generation of engineers and driving inclusive innovation at scale.
Education
PhD in Mechanical Engineering
2016-2022
Northwestern University
MSc in Mechanical Engineer
2016-2019
Northwestern University
BSc in Mechanical Engineering
2012-2016
University of Washington
Scholarships, Fellowships, Awards
Advanced Rehabilitation Research Training (ARRT) Fellowship
2022-2024
University of Washington
Walter P. Murphy Fellowship
2016-2017
Northwestern University
Precision Medicine Initiative Challenge
2017
3rd place
Student Research Award
2016
Dept of Mechanical Engineering, University of Washington
Levinson Emerging Scholar Award
2015-2016
University of Washington
Research Experiences for Undergraduates Fellow
2015
University of Washington
Best Poster Award
2015
Northwest Biomechanics Symposium
Mary Gates Research Scholarship
2015
University of Washington
C.E. Boucher Memorial Scholarship
2013-2015
University of Washington
Publications
Accuracy of video-based hand tracking for people with upper-body disabilities
AA Portnova-Fahreeva et al. IEEE TNSRE. 2024
How do people with limited movement personalize upper-body gestures? Considerations for design of personalized and accessible gesture interfaces
M Yamagami, AA Portnova-Fahreeva et al. ASSETS. 2023
AA Portnova-Fahreeva et al. Frontiers in Bioengineering and Biotechnologies. 2022
D Boe, AA Portnova-Fahreeva et al. Frontiers in Bioengineering and Biotechnologies. 2021
AA Portnova-Fahreeva et al. Frontiers in Bioengineering and Biotechnologies. 2020
M Han, AA Portnova et al. PloS One. 2020
AA Portnova et al. PloS One. 2018
Skills
Machine learning
Build and train neural network models using Tensorflow
Perform hyperparameter tuning
Rehabilitation measures
Both qualitative and quantitative
Human-centered design
Co-design assistive technologies with end-users
Co-create rehabilitation solutions with medical professionals
Data analysis
Signal processing
Statistical methods
Dimensionality reduction (PCA, SVA, Autoencoders)
Simulation modeling
Simulate various virtual environments using Unity
Myoelectric device control
Facilitate control of devices and virtual objects
via muscle signals
Biosignal data collection
IMU
EMG
motion capture (marker-based and markerless)
bend sensors
wearable technologies
Fabrication
CAD modeling in Solidworks
3D printing (fused deposition modeling, vat polymerization)
3D scanning
Computer programming
C#
MATLAB
Python