CV
Contact Information
| Name | Shayan Khodabakhsh |
| Professional Title | M.S. Electrical Engineering · University of Rhode Island |
| skhodabakhsh@uri.edu | |
| Location | Department of Electrical, Computer, and Biomedical Engineering, Kingston, Rhode Island 02881 |
Professional Summary
M.S. Electrical Engineering student at the University of Rhode Island working on computer vision, multimodal sensor fusion (EEG, EMG, IMU, motion capture), and machine learning for clinical movement assessment. Two peer-reviewed journal publications in wearable sensor validation.
Experience
-
2026 - 2026 Kingston, RI
Graduate Researcher (Prof. Abiri) — A Vision-Language Coach for Ingestive Behaviors (NIH R01, DIBS)
Dept. of Electrical, Computer, and Biomedical Engineering, URI
- Fine-tuned a Qwen2.5-VL vision-language model with LoRA on profile-view meal video to jointly classify ingestive-behavior quality and generate clinician-style coaching feedback.
- Designed a multi-bite temporal windowing strategy capturing chewing rhythm and inter-bite pauses, improving classification accuracy over per-bite clips.
- Showed a single LoRA adapter on a VLM matches the classification accuracy of a prior multi-head architecture while adding language generation in one pass.
- First-author poster, ECBE Graduate Student Poster Competition.
-
2026 - Present Kingston, RI
Graduate Researcher (Prof. Besio) — Tripolar Concentric Ring Electrode (TCRE) EEG Comparison
Dept. of Electrical, Computer, and Biomedical Engineering, URI
- Built a unified Python preprocessing and analysis pipeline to compare Paste, Gel, and saline-soaked Felt TCRE configurations on resting-state and visual-evoked-potential recordings.
- Used scale-invariant cross-setup metrics (alpha SNR, alpha reactivity, spectrogram SSIM) to handle hardware scaling differences across acquisitions.
- Ran preprocessing sensitivity analyses and per-subject VEP diagnostics that informed cohort and exclusion decisions for the manuscript (in preparation, Sensors MDPI).
-
2026 - 2026 Kingston, RI
Graduate Researcher (Prof. Abiri) — PRIME Closed-Loop Cobot
Dept. of Electrical, Computer, and Biomedical Engineering, URI
- Fine-tuned YOLOv26 on task-specific image datasets for object detection and action recognition driving the closed-loop perception module of a human-robot teaming cobot.
- Integrated the perception module with the cobot stack and ran end-to-end task evaluation experiments.
- Manuscript under review.
-
2025 - Present Kingston, RI
Graduate Researcher — Automated Neuromuscular Assessment with Computer Vision and Robotics
Dept. of Electrical, Computer, and Biomedical Engineering, URI
- Developing a non-invasive assessment system using Socially Assistive Robots (SAR) to automate standardized neuromuscular tests.
- Implementing computer vision pipelines (Python/OpenCV) for 3D hand pose estimation to quantify fine motor deficits without markers.
- Designing closed-loop algorithms to provide real-time feedback to patients during unsupervised rehabilitation sessions.
-
2025 - Present Kingston, RI
Graduate Researcher — Multimodal EEG and Motion Capture for Movement Decoding
Dept. of Electrical, Computer, and Biomedical Engineering, URI
- Engineered a hardware synchronization solution to fuse high-density EEG (g.tec) data with optical motion capture systems.
- Optimizing data acquisition protocols to reduce latency between cortical activity and recorded kinematic events.
- Analyzing neural correlates of grasping and reaching movements for potential Brain-Computer Interface applications.
-
2024 - 2024 Kingston, RI
Research Assistant (Prof. D'Andrea) — Biomechanical and Myoelectric Pattern Recognition in ALS
Biomechanics and Motion Analysis Lab, URI (ALS Foundation No. 1159154)
- Synchronized EMG signals with gait kinematics to identify pathological movement patterns.
- Used Visual3D motion capture software to model joint mechanics and muscle activation timing.
-
2023 - 2023 Kingston, RI
Research Assistant (Prof. Chapman) — Wearable Inertial Sensor Validation
Biomechanics and Wearable Sensors Lab, URI
- Validated commercial IMU sensor accuracy against gold-standard optical motion capture.
- Analyzed sensor drift and calibration errors in measuring sagittal knee angles during dynamic tasks.
Education
-
2025 - Present Kingston, RI, USA
M.S.
University of Rhode Island
Electrical Engineering
- Department of Electrical, Computer, and Biomedical Engineering
-
2020 - 2022 Tehran, Iran
M.S.
Shahid Beheshti University
Applied Exercise Physiology
- Top 5 cumulative GPA in cohort
- Thesis: Acute Effects of Lunge Exercise with Blood-Flow Restriction on Amateur Male Basketball Players
-
2014 - 2020 Tehran, Iran
B.S.
Islamic Azad University, Science and Research Branch
Sports Engineering
Awards
-
2024 Dr. Thomas "Doc" Manfredi Student Research Fund Awardee
University of Rhode Island
-
2023 Finalist, Student Investigator Award and Presidential Cup Award
New England American College of Sports Medicine
-
2023 Dr. Thomas "Doc" Manfredi Student Research Fund Awardee
University of Rhode Island
-
2023 Dean's Scholarship
University of Rhode Island
-
2022 Top 5 Cumulative GPA, M.S. cohort
Shahid Beheshti University
Skills
Programming (Advanced): Python, MATLAB, R
Machine Learning & Computer Vision (Advanced): PyTorch, Keras, OpenCV, Hugging Face Transformers, LoRA / PEFT, YOLO, PyBullet
Biomedical Signal & Sensor Tools (Advanced): MNE-Python, g.tec EEG, Qualisys, Motive, Visual3D, StretchSense
Statistics (Intermediate): SPSS, Prism GraphPad, bootstrap methods
Certificates
- Fundamentals of Deep Learning - NVIDIA / University of Rhode Island (2024)
- A Deep Understanding of Deep Learning - Udemy (2024)
- Master the Fourier Transformation and Its Applications - Udemy (2024)
- MATLAB Fundamentals - MathWorks / University of Rhode Island (2023)
Languages
Persian : Native
English : Full professional proficiency
Interests
Research: Computer vision, Vision-language models, EEG / BCI, Multimodal sensor fusion, Socially assistive robotics