Dr. Marwa Soliman: Senior Research Assistant at Burke Neurological Institute, United States
Marwa Soliman is a graduate student pursuing a Master of Computer Science with a focus on Big Data Systems at Arizona State University. With a background in both Computer Science and Biology, she is passionate about applying computational techniques to biological research, particularly in the field of neuroscience. Currently a Senior Research Assistant at the Burke Neurological Institute, she combines her expertise in data analysis, image processing, and deep learning to support cutting-edge research on spinal cord injury and circuit repair.
Online Profiles
Research Metrics
- Total Citations: 17
- Citations Since 2020: 17
- h-index: 1
- i10-index: 1
These metrics reflect a growing body of research with impactful contributions in the fields of neuroscience and motor learning, highlighting the relevance and influence of your work in advancing scientific understanding.
Education
Marwa is currently pursuing her Master of Computer Science in Big Data Systems at Arizona State University, expected to graduate in June 2025. She holds a B.A. in Computer Science and a B.A. in Biology, both earned summa cum laude from Manhattanville University, where she achieved a GPA of 3.91/4.00. Her academic journey has equipped her with a strong foundation in data science, machine learning, and computational biology.
Research Focus
Her primary research interests revolve around utilizing big data systems, machine learning, and image analysis to better understand neurological conditions, particularly spinal cord injury and neuroregeneration. Marwa is actively working on automating high-dimensional biological data analysis, integrating behavioral and neural activity data, and exploring gene networks related to axonal regeneration.
Experience
As a Senior Research Assistant at the Burke Neurological Institute, Marwa specializes in image and data analysis, with a focus on automating complex biological datasets, such as RNA sequencing and KDI analysis. She is proficient in using tools like DeepLabCut, OpenCV, and Python to analyze behavioral videos, and she leads efforts in 3D printing and laser cutting within the lab. Additionally, she has contributed to the development of synchronized systems that link motor behavior to neural recordings, advancing research on neurodegenerative diseases.
Research Timeline
Marwa’s research timeline spans from her undergraduate years, where she developed deep-learning algorithms for early skin cancer detection, to her current work in spinal cord injury research. At Manhattanville University, she worked on skin cancer detection algorithms during the summer of 2019. From 2020 onwards, she has been involved in more advanced projects at the Burke Neurological Institute, focusing on motion function assessment and neuroregeneration through data-driven tools and techniques.
Awards & Honors
Marwa has received multiple honors, including the Computer Science Department Honors Award, Biology Department Honors Award, and the prestigious Daughters for Life Scholarship in 2016. She was also a finalist at the Intel ISEF in 2014 and has been recognized for leadership and outstanding service, notably receiving the Leadership and Outstanding Service Award from the Mary T. Clark Center for Religion and Social Justice in 2019.
Top-Noted Publication
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Task-specific modulation of corticospinal neuron activity during motor learning in mice
N Serradj, F Marino, Y Moreno-López, A Bernstein, S Agger, M Soliman, …
Nature Communications, 14(1), 2708, 2023
This study explored how task-specific activities modulate corticospinal neuron function during motor learning, shedding light on how skilled motor behavior impacts the neural circuits responsible for voluntary movement. -
A Kinematic Deviation Index (KDI) for Evaluation of Forelimb Function in Rodents
A Torres-Espin, A Bernstein, M Soliman, JS Jara, Y Moreno-López, …
bioRxiv, 1, 2024
This paper introduced the Kinematic Deviation Index (KDI), a novel metric for assessing forelimb function in rodents, providing a more precise tool for evaluating motor deficits and recovery in animal models of neurological disorders. -
Acute Extrinsic Activation of the RANKL Pathway Decreases Wound Healing and Functional Recovery After Spinal Cord Injury in Mice
AL Vivinetto, A Bernstein, M Soliman, JW Cave, E Hollis
Glia, 2025
This publication explored how acute activation of the RANKL pathway impairs both wound healing and functional recovery following spinal cord injury, highlighting a potential target for therapeutic intervention. -
Conditioning electrical stimulation enhances functional rewiring in a mouse model of nerve transfer to treat chronic spinal cord injury
JS Jara, M Soliman, A Bernstein, P di Grazia, AR Ferguson, JM Brown, …
bioRxiv, 2025.01.17.633666
This study demonstrated that conditioning electrical stimulation enhances functional rewiring in a mouse model of nerve transfer for treating chronic spinal cord injury, providing promising insights into improving recovery outcomes. -
Task-specific modulation of corticospinal neuron activity during skilled motor learning
N Serradj, F Marino, Y Moreno-López, A Bernstein, S Agger, M Soliman, …
bioRxiv, 2021.03.22.436415
In this earlier work, the team investigated how skilled motor learning drives changes in corticospinal neuron activity, contributing to our understanding of the neural mechanisms underlying motor skill acquisition.