ACADEMIC INTEREST
Human Embedded AI systems for Neuro-rehab and surgery
EDUCATION
University of Southern California Expected: May 2026
PhD. Biomedical Engineering- recommendation tool for Neuro-rehab and surgery
Virginia Tech August 2019-MAY 2022 (Transferred)
PhD. Biomedical Engineering- Machine Learning research in interactive Neurorehabilitation
Bangladesh University of Engineering and Technology February 2013-September 2017
B.S. Electrical and Electronics Engineering
Thesis: Beat Tracking with Empirical Mode Decomposition-based Tempo Estimation and Dynamic Programming
EXPERIENCE (Current)
Jimmy Iovine and Young Academy, USC | Human Technology Interaction Faculty
Los Angeles: January 2025 – May 2026
• Collaborated with design faculty to design the HTI degree for the program
• principle investigator (PI) for a collaborative project with Johnson & Johnson MedTech. In this project we will be developing digital assistants that will predict surgical site outcomes for post operative team in the hospitals.
• Developed SARA system that is currently used by the clinicians of Shirley Ryan Ability Lab which is number one rehab center in the United States. The system uses vision and language, vision and time series data fusion to predict scores and impaired movement quality elements by observing stroke survivors performing different tasks.
EXPERIENCE (Past)
Shirley Ryan Ability Lab | Residency Training
Chicago: May 2024 – July 2024
• Collaborated with clinicians from Shirley Ryan ability lab to design a dashboard that can represent a list of movement impairments with associated quantifiable cluster of kinematics and a summary of assessment profiles for stroke patients.
• Collaborated with Dr. Arun and his team to understand lower body kinematics and the process of extracting them using Xsense and OpenSim sensors. Now we are developing models that can use fewer sensors to extract quality kinematics.
Interactive Neurorehabilitation Lab | Data Scientist, Graduate Research Assistant
University of Southern California, Los Angeles, California: May 2022 – May 2026
Virginia Tech, Blacksburg, Virginia: August 2019 – May 2022
• Collaborated with Valero Lab to create hand models to understand hand-object interactions for ARAT exercises
• Developed a Hierarchical Bayesian model to explain the relationship among different layers of movement quality assessment
• Collaborated with ML team for data analysis, human skeleton extraction with ‘OpenPose’, and temporal segmentation of stroke patient’s action with a Hierarchical Bayesian model
• Implemented R-CNN-based human-object interaction algorithm for stroke survivor’s movement quality assessment
• Developed a better understanding of stroke patient’s physical and cognitive impairments from physical therapist collaboration
• Mentored and supervised a multidisciplinary team of undergrad and Ph.D. students for machine learning research and data analysis
DSP Research Lab | Applied Deep Learning Researcher
Dhaka, Bangladesh: April 2018 – February 2019
• Proposed and implemented an innovative deep-learning architecture for better-quality ultrasound image reconstruction
• Extracted temporal feature with a recurrent architecture from 3D tissue displacement
• Improved image reconstruction quality by 4-5% with the incorporation of RNN and 3D-CNN
• Detected musical beat using Empirical mode decomposition
Bangladesh University of Engineering and Technology | Research Engineer
Dhaka, Bangladesh: September 2017 – April 2018
• Initiated patient data collection and experiments with multiple CIRS phantom in clinical setup with radiologist collaboration
• Conducted research for simulation of ultrasound wave propagation and provided clinical support for patient report writing
• Performed analytic Gaussian modeling on ultrasound tissue displacement data to achieve a 6-9 percent improvement over existing algorithms
TEACHING EXPERIENCE
University of Southern California | IDSN 543 Augmented Intelligence
January 2025 – May 2025
• Designed the course content and syllabus for undergraduate and graduate level students.
• The course trains the students to understand models and algorithms applied in the field of neuro-rehab and how they are connected to multimodal data
PROJECTS
Cyber Human System for Upper Extremity Stroke Survivors
USC, USA: May 2022 – present
• Capture data of stroke patients performing different rehab exercises using multi-camera and sensors
• Analyze the data using trained models and generate automated assessment scores and recommendations for the expert clinicians
Hand Vein Detection with BPM estimation Using Pulse Sensor
BUET, Bangladesh: January 2017 – December 2017
• Decomposed raw sensor data into EMG and ECG signal using Empirical Model Decomposition
• Estimated BPM and vein coordinates from decomposed sensor data with a 78% accuracy
Hand Vein Detection Using Near-Infrared Imaging
BUET, Bangladesh: January 2017 – December 2017
• Administered project management and front-end development for a mechanical hand to inject medicine and extract blood from vein
• Introduced a real-time optimization algorithm for vein detection with 92% accuracy
PATENTS
Apparatus, methods, and computer products for deep learning-based shear wave imaging (Provisional patent application number: 62816344)
GOOGLE SCHOLAR
Profile: https://scholar.google.com/citations?user=kDhKjksAAAAJ&hl=en , citations: 67
WEBSITE
..\Users\tamim\Desktop\Tamim Ahmed, PhD Candidate.html
GRANTS
· National Science Foundation (Grant Number: 2014499), 2021-2025
· National Institute on Disability, Independent Living, and Rehabilitation Research (Grant Number: 90REGE0010),2019-2025
· Applied to J&J MedTech with the proposal “enhancing surgeons by doing event detection during surgery”-2025
HONORS
NIH and NSF grant-funded Ph.D. (2019-current)
Pratt Fellowship, (2019-2020)
Best Innovative Project, ICCIT, 2017
Talent Pool Scholarship, Bangladesh (2013-2017)
PUBLICATIONS
• Tamim Ahmed, “Enhancing Human Expert Performance Through Probabilistic Multi-Expert Fusion”, under review Nature Digital Medicine
• Tamim Ahmed, “A Methodology for Integrating AI into Embodied Human Intelligence for the Performance of Complex Tasks”, under review Frontiers in AI
• Tamim Ahmed, “OpenSim validated 3D reconstructed kinematics from multi-camera setup in stroke rehabilitation”, under preparation
• Jisoo Lee, Tamim Ahmed, “Automatic Temporal Segmentation for Post-Stroke Rehabilitation: Key Point Detection and Temporal Segmentation Approach for Small Datasets”, accepted in WACV 2025
• T. Ahmed, T. Rikakis, J. Lee and P. Turaga, 2024 "A Multi-camera Data Segmentation and Imputation Block for Cyber-Human Assessment of Movement in Upper Extremity Stroke Rehabilitation," under review in IEEE Journal of Biomedical and Health Informatics (JBHI).
• T. Ahmed, T. Rikakis, S. Khan and A. Kelliher, 2024, “Co-designing an Automated Assessment System for Rehabilitation”, under review for CHI, 2026
• T. Ahmed, T. Rikakis, A. Kelliher and S. L. Wolf, 2024 "A Hierarchical Bayesian Model for Cyber-Human Assessment of Movement in Upper Extremity Stroke Rehabilitation," in IEEE Transactions on Neural Systems and Rehabilitation Engineering, doi: 10.1109/TNSRE.2024.3450008.
• Ahmed, Tamim, et al. (2024). Advances in Computer Vision for Home-Based Stroke Rehabilitation in Computer Vision: Challenges, Trends, and Opportunities (1st ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9781003328957
• Ahmed, Tamim, et al. 2023. ASAR Dataset and Computational Model for Affective State Recognition During ARAT Assessment for Upper Extremity Stroke Survivors. In Companion Publication of the 25th International Conference on Multimodal Interaction (ICMI '23 Companion). Association for Computing Machinery, New York, NY, USA, 11–15. https://doi.org/10.1145/3610661.3617154
• Low-cost Capture and Analysis of Movement Quality and Functionality for Adaptive Therapy of Upper Extremity Stroke Survivors; Tamim Ahmed, Thanassis Rikakis, Aisling Kelliher, Francisco J. Valero-Cuevas; NSF Dare Conference Poster 2023
• Ahmed, Tamim, et al. "Automated movement assessment in stroke rehabilitation." Frontiers in Neurology (2021): 1396.
• Hybrid Workflow Process for Home Based Movement Capture, J. Clark, S. Zilevu, T. Ahmed, A. Kelliher, S. Yeshala, S. Garrison, C. Garcia, O. Menezes, M. Seth, T. Rikakis. forthcoming at ACM IMX 2021
• Kelliher, Aisling, et al. "Towards Standardized Processes for Physical Therapists to Quantify Patient Rehabilitation." Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 2020.
• 2017. Ahmed, Tamim, et al. "Real-time injecting device with automated robust vein detection using near-infrared camera and live video." Global Humanitarian Technology Conference (GHTC), San Jose, CA
• 2017. Ahmed, Tamim, et al. "Auto-HRID: Automated Heart Rate Monitoring and Injecting Device with Precise Vein Detection." IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE), India
SKILLS
Technical
Machine Learning
Deep Learning
Data Analysis
Signal Processing
Image Processing
Data Observation and Interpretation
Personal & workplace
Learning from observation
Proactive
Collaborative
Team Player
Programming Languages
Python
MATLAB
Frameworks
Keras
PYTORCH
Numpy
Scikit Learn
OPENPOSE
R-CNN
LEADERSHIP & VOLUNTARY WORK
Seminar on Ultrasound Elastography | Presenter
Dhaka, Bangladesh: April 2018
WIECON-ECE conference | Presenter
Dehradun, India: December 2017
Inter University Robotics Competition | Head Organizer
Dhaka, Bangladesh: August 2017
ICCIT | Team Project Showcase
Dhaka, Bangladesh: August 2017
COLLABORATION
Carilion Clinic
Collaborated with clinicians from Carilion Clinic to develop
· Rubric for movement quality assessment for the SARAH system
· Rubric for movement quality assessment for the SARAH video segmentation
· Annotation tool for rating the captured data
Shirley-Ryan Ability Lab (SR Lab)
Collaborating with clinicians from SR Lab to develop
· Rubric for movement quality assessment for the ARAT system
· Capturing tool for capturing stroke survivors performing ARAT exercises
· Calibration tool for camera and activity space calibration
Virginia Tech
Collaborating with two PhD students to
· Develop a fusion model for a multimodal movement quality assessment tool
· Make wireless data transfer for Activity of Daily Living (ADL) capture
· Develop annotation tool for SARAH video rating
Arizona State University
Collaborating with a PhD student to
· Label SARAH and ARAT objects using CVAT
· Train an object detection model for SARAH and ARAT
· Develop a multimodal hybrid segmentation model for segmenting SARAH and ARAT-captured videos
MENTORING
• I have mentored an M.S. student. She was the lead designer of the UI used for annotating the ARAT videos. She needed to understand the biomechanics of the segments and the relationship of different cameras with the segments. Under the supervision of Dr. Thanassis and Dr. Aisling, I have created a rubric to define the duration of the segments and their relationship with different camera views.
• We hired an undergrad to annotate the ARAT videos using our annotation tool. I taught her to use the annotation tool for segmentation. In addition, she also used rubrics to understand the biomechanics of the segments.
• I have also mentored a volunteer collaborator who designed the database to store the annotations. Since he was new in the field, he needed help understanding the data structure and inter/intra relationships between different components.
• I have mentored an MS student in developing the ARAT capture system, which is to our knowledge, the world’s first ARAT data capture system using RGB cameras