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.
Welcome to the Augmented Cognition Lab (ACLab)
ACLab's NEWS
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ACLab Funded Projects
- Research in ACLab is generously supported by the National Science Foundation, Department of Defense, MathWorks, Amazon Cloud Services, Biogen, NVIDIA, and Oracle. For the full list of research project please visit: https://web.northeastern.edu/ostadabbas/research/
Notes for Interested Undergraduate Students:
- ACLab is always looking for talented and enthusiastic undergraduate students. Please check the Undergraduate Research and Creative Endeavor Awards center at Northeastern and based on your eligibility and the future deadlines contact me to define a project for you in line with the ACLab's mission. Deadlines: The last weekday of October for Spring semester; The last weekday of February for Summer sessions (i.e., May-August); The last weekday of July for Fall semester.







































