Sarah Ostadabbas
Associate Professor, Electrical and Computer Engineering
Director, Women in Engineering Program
Office
- 520 ISEC
- 617.373.4992
Related Links
Research Focus
Computer Vision; Machine Learning; Artificial Intelligence; Augmented Cognition with Medical Applications; Augmented/Virtual Reality
About
Professor Ostadabbas is an associate professor in the Electrical and Computer Engineering Department at Northeastern University (NU) in Boston, Massachusetts, USA. She joined NU in 2016 after completing her post-doctoral research at Georgia Tech, following the achievement of her PhD at the University of Texas at Dallas in 2014. At NU, Professor Ostadabbas holds the roles of Director at the Augmented Cognition Laboratory (ACLab), Director of Women in Engineering (WIE), and Co-Director at The Center for Signal Processing, Imaging, Reasoning, and Learning (SPIRAL). Her research focuses on the convergence of computer vision and machine learning, particularly emphasizing representation learning in visual perception problems. In her applied research, she has significantly contributed to the understanding, detection, and prediction of human and animal behaviors through the modeling of visual motion, considering various biomechanical factors. Professor Ostadabbas also extends her work to the Small Data Domain, including applications in medical and military fields, where data collection and labeling are costly and protected by strict privacy laws. Her solutions involve deep learning frameworks that operate effectively with limited labeled training data, incorporate domain knowledge for prior learning and synthetic data augmentation, and enhance the generalization of learning across domains by acquiring invariant representations. Professor Ostadabbas has co-authored over 130 peer-reviewed journal and conference articles and received research awards from prestigious institutions such as the National Science Foundation (NSF), Department of Defense (DoD), Sony, Mathworks, Amazon AWS, Verizon, Oracle, Biogen, and NVIDIA. She has been honored with the NSF CAREER Award (2022), Sony Faculty Innovation Award (2023), was the runner-up for the Oracle Excellence Award (2023), and One of the 120+ Women Spearheading Advances in Visual Tech and AI Recognized by LDV Capital (2024). She served in the organization committees of many workshops in renowned conferences (such as CVPR, ECCV, ICCV, ICIP, ICCASP, BioCAS, CHASE, ICHI) in various roles including Lead/Co-Lead Organizer, Program Chair, Board Member, Publicity Co-Chair, Session Chair, Technical Committee, and Mentor.
Education
- Postdoc (2015)—Georgia Tech
- PhD (2014) Electrical & Computer Engineering (Signal Processing)—UT Dallas
- MS (2007) Electrical Engineering (Control)—Sharif University of Tech, Tehran, Iran
- BS (2006) Electrical Engineering (Electronics)—Amirkabir University of Tech, Tehran, Iran
- BS (2005) Electrical Engineering (Biomedical)—Amirkabir University of Tech, Tehran, Iran
Honors & Awards
Professional Affiliations
- Member of IEEE
- IEEE Women in Engineering
- IEEE Signal Processing Society
- IEEE EMBS
- IEEE Young Professionals
- ACM SIGCHI.
Research Overview
Computer Vision; Machine Learning; Artificial Intelligence; Augmented Cognition with Medical Applications; Augmented/Virtual Reality
Augmented Cognition Laboratory
ACLab works at the intersection of computer vision and machine learning. We are interested in representation learning algorithms for visual perception (object recognition, localization, segmentation, pose estimation, activity tracking, …) with the multidisciplinary goal of understanding, detecting, and predicting human behaviors by estimating their physical, physiological and emotional states. For a robust and efficient state estimation, we represent the state of the world in a low-dimensional embedding, called “pose”, which is a succinct interpretable representation of the important information in the state. At ACLab, we use machine intelligence (mainly Computer Vision and Machine Learning) to solve these pose estimation problems and to give human leverage, not to replace them! At ACLab, we are also working on problems in Small Data domains. To deal with data limitation, we do integrate explicit (structural or data-driven) domain knowledge into the learning process via generative models, while benefiting from the recent advancements in data efficient ML.
Selected Research Projects
- Graph-Centric Exploration of Nonlinear Neural Dynamics in Visuospatial-Motor Functions During Immersive Human-Computer Interactions
- – Principal Investigator, National Science Foundation
- PFI-RP: Augmented Reality and Electroencephalography for Detecting, Assessing, and Rehabilitating Visual Unilateral Neglect in Stroke Patients
- – Principal Investigator, National Science Foundation
- Development of a precision closed loop BCI for socially fearful teens with depression and anxiety
- – Principal Investigator, National Science Foundation
- CAREER: Learning Visual Representations of Motor Function in Infants as Prodromal Signs for Autism
- – Principal Investigator, National Science Foundation
- CHS: Small: Collaborative Research: A Graph-Based Data Fusion Framework Towards Guiding A Hybrid Brain-Computer Interface
- – Principal Investigator, National Science Foundation
- CRII: SCH: Semi-Supervised Physics-Based Generative Model for Data Augmentation and Cross-Modality Data Reconstruction
- – Principal Investigator, National Science Foundation
- NCS-FO: Leveraging Deep Probabilistic Models to Understand the Neural Bases of Subjective Experience
- – Co-Principal Investigator, National Science Foundation- Neural and Cognitive Systems
- NRI: EAGER: Teaching Aerial Robots to Perch Like a Bat via AI-Guided Design and Control
- – Principal Investigator, National Science Foundation
- SCH: INT: Collaborative Research: Detection, Assessment and Rehabilitation of Stroke-Induced Visual Neglect Using Augmented Reality (AR) and Electroencephalography (EEG)
- – Principal Investigator, National Science Foundation
Department Research Areas
Selected Publications
- D. Teotia, A. Lapedriza, and S. Ostadabbas, “Interpreting face inference models using hierarchical network dis-section,” International Journal of Computer Vision (IJCV), 2022.
- S. Liu, X. Huang⋆, L. Marcenaro, and S. Ostadabbas, “Privacy-preserving in-bed human pose estimation: High- lights from the ieee video and image processing cup 2021 student competition,” IEEE Signal Processing Magazine, 2022.
- A. Farnoosh and S. Ostadabbas, “Deep Markov Factor Analysis: Towards concurrent temporal and spatial analysis of fMRI data,” in Thirty-fifth Annual Conference on Neural Information Processing Systems (NeurIPS), 2021.
- A. Farnoosh, B. Azari, S. Ostadabbas, “Deep Switching Auto-Regressive Factorization: Application to Time Series Forecasting,” The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI’21). February 2-9, 2021.
- B. Rezaei, A. Farnoosh, and S. Ostadabbas, “G-LBM: Generative Low-dimensional Background Model Estimation from Video Sequences,” 16th European Conference on Computer Vision (ECCV’20), August 23-28, 2020.
- S. Liu, S. Ostadabbas, Seeing Under the Cover: A Physics Guided Learning Approach for In-Bed Pose Estimation, 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’19), October 13-17, 2019, Shenzhen, China
- S. Liu, S. Ostadabbas, “Inner Space Preserving Generative Pose Machine,” 15th European Conference on Computer Vision (ECCV’18), September 8-14, 2018, Munich, Germany.
Oct 01, 2024
Patent for Color-Sensing Technology
ChE Affiliated Faculty Swastik Kar and ECE Associate Professor Sarah Ostadabbas were awarded a patent for “Device and method for color indentification.”
Oct 01, 2024
Ostadabbas Wins 2024 Cade Prize for Inventivity
ECE Associate Professor Sarah Ostadabbas received the 2024 Cade Prize for Inventivity in the technology category for AiWover, a groundbreaking spin-off from her lab that uses AI to transform visual monitoring of babies and toddlers and enhances both safety and developmental tracking.
Aug 29, 2024
Creating Age-Inclusive VR
ECE Associate Professor Sarah Ostadabbas, in collaboration with the University of Rhode Island, was awarded a $600,000 NSF grant for “Graph-Centric Exploration of Nonlinear Neural Dynamics in Visuospatial-Motor Functions During Immersive Human-Computer Interactions.” She is investigating how aging impacts the ability to use emerging HCI technologies.
Jul 08, 2024
Using AI To Save Lives on the Battlefield
Liam McEneaney, MS’25, engineering and public policy, is working with ECE Associate Professor Sarah Ostadabbas and MIE Teaching Professor Beverly Kris Jaeger-Helton, and in collaboration with MIT Lincoln Lab, to develop an AI-powered computer program that will accurately and quickly fill out tactical combat casualty care cards for injured soldiers on its own on the battlefield by processing video and audio from medics in real time, and quickly sending the digital card to hospital staff.
May 20, 2024
ECE Professors Recognized Among Leading Women in Visual Tech and AI
ECE Professor Octavia Camps and ECE Associate Professor Sarah Ostadabbas were recognized by LDV Capital as two of the 120+ Women Spearheading Advances in Visual Tech and AI, which highlights contributions of women in fields such as machine vision, pattern recognition, and generative models.
Feb 21, 2024
Engineers Week Women in Engineering Panel Discusses Unique Challenges Facing Women in Engineering
During Engineers Week, a panel of faculty and students shared their experiences and advice on their education and career journeys as women engineers. They offered advice to future female engineers to empower them and help them grow, including the importance of faculty and peer mentors.
Nov 28, 2023
NSF PFI Grant To Integrate AR Technologies Into Stroke Rehabilitation
ECE Associate Professor Sarah Ostadabbas, in collaboration with the University of Pittsburgh and Myomo, Inc., secured a $550,000 NSF grant for their project titled “PFI-RP: Augmented Reality and Electroencephalography for Detecting, Assessing, and Rehabilitating Visual Unilateral Neglect in Stroke Patients.” It aims to create a comprehensive tool for detecting, assessing, and rehabilitating neglect in stroke patients.
Nov 14, 2023
MS to PhD Research Leads to Improved Autonomous Vehicles
Xiangyu Bai, MS’23, electrical and computer engineering, who is now pursuing his PhD at Northeastern in computer engineering, conducts research in the area of computer vision focused on improving autonomy simulations. He is advised by Associate Professor Sarah Ostadabbas and works in her Augmented Cognition Laboratory.
Oct 09, 2023
Ostadabbas Receives Sony Faculty Innovation Award
ECE Associate Professor Sarah Ostadabbas received the Sony Faculty Innovation Award for her project titled “Live Stream Temporally Embedded 3D Human Body Pose and Shape Estimation.” She is the first at Northeastern to receive this prestigious award.
Sep 15, 2023
Ostadabbas a Finalist of the Eureka Award of the 2023 Oracle Excellence Award
ECE Associate Professor Sarah Ostadabbas was selected as one of the finalists of the Eureka Award of the 2023 Oracle Excellence Awards. With Oracle for Research, researchers in academic, commercial, and governmental settings, across all disciplines, are exploring novel ways to achieve ground-breaking results to make the world a better place.