ACLab is situated at the convergence of computer vision and machine learning, focusing especially on representation learning for visual perception challenges. Our applied research significantly contributes to the understanding, detection, and prediction of human or animal behaviors in natural settings by assessing their physical, physiological, and emotional states. Our algorithms efficiently encapsulate the state of the world into a low-dimensional “pose” embedding, offering a clear and interpretable summary of critical state information.

Our group specifically tackles machine learning and vision issues in scenarios where data acquisition or labeling is constrained by cost, privacy, or security concerns—commonly known as Small Data domains. To navigate these data restrictions, our approach incorporates specific domain knowledge into the learning process through generative models, simultaneously leveraging the latest in data-efficient machine learning techniques.

Challenges in Small Data domains often involve a complex array of elements with profound implications for both engineering and science. Thus, we actively seek collaboration with experts across various fields, including medicine, psychology, therapy, physics, and neuroscience. These interdisciplinary partnerships have significantly shaped the direction and impact of my research.

For many of these projects, augmented reality (AR) and virtual reality (VR) tools are essential for both the assessment and enhancement portions of the project. Below, you can find some of our active research projects. Also visit our The Signal Processing, Imaging, Reasoning, and Learning (SPIRAL) Group for more information about our collaborative cluster. 

ACLab Funded Projects:

NSF-HCC-Small 2417448 ($250K)

“Collaborative Research: HCC: Small: Graph-Centric Exploration of Nonlinear Neural Dynamics in Visuospatial-Motor Functions during Immersive Human-Computer Interactions” (Role: PI, Date: 10/2024-9/2027)

Sony Faculty Innovative Award ($100K)

“Live Stream Temporally Embedded 3D Human Body Pose and Shape Estimation” (Role: PI, Date: 10/2023-9/2024)

NSF-PFI-RP 2234346 ($550K)

“PFI-RP: Use of Augmented Reality and Electroencephalography for Visual Unilateral Neglect Detection, Assessment and Rehabilitation in Stroke Patients” (Role: CoPI, Date: 12/2023-11/2026)

NSF-DARE 2327066 ($150K)

“Collaborative Research: Development of a precision closed loop BCI for socially fearful teens with depression and anxiety” (Role: PI, Date: 11/2023-10/2026)

NSF-CAREER 2143882 ($600K) 

“CAREER: Learning Visual Representations of Motor Function in Infants as Prodromal Signs for Autism” (Role: PI, Date: 5/2022-4/2027)

Northeastern-UMaine Seed Funding ($50K)
“Using artificial intelligence to examine the interplay between pacifier use and sudden infant death syndrome” (Role: CoPI, Date: 11/2020-10/2023)

NSF-IIS 2005957 ($190K)
“CHS: Small: Collaborative Research: A Graph-Based Data Fusion Framework Towards Guiding A Hybrid Brain-Computer Interface” (Role: PI, Date: 10/2020-09/2023)

Northeastern Tier 1 Award ($50K)  
“Novel methods to quantify the affective impact of virtual reality for motor skill learning” (Role: CoPI, Date: 07/2020-09/2021 )

Northeastern GapFund360 ($50K)

“A-Eye: A Nanotechnology and AI-assisted Artificial Cone Cell Capable of Color and Spectral Recognition” (Role: CoPI, Date: 01/2020-12/2020)

ADVANCE Mutual Mentoring Grant ($3K) 
“Translating the ‘Mastermind’ Concept from Business to Academia: Facilitating Peer mentorship among female PIs leading active research labs” [Project Link] (Role: CoI, Date: 01/2020-12/2020)

NSF-NRI 1944964 ($102K)  
“NRI: EAGER: Teaching Aerial Robots to Perch Like a Bat via AI-Guided Design and Control” (Role: PI, Date: 10/2019-09/2020)

NSF-IIS 1915065 ($395K)  
“SCH: INT: Collaborative Research: Detection, Assessment and Rehabilitation of Stroke-Induced Visual Neglect Using Augmented Reality (AR) and Electroencephalography (EEG)” [Project Link] (Role: PI, Date: 09/2019-08/2023 )

NSF-NCS 1835309 ($999K)  
“NCS-FO: Leveraging Deep Probabilistic Models to Understand the Neural Bases of Subjective Experience” ( Role: CoPI, Date: 08/2018-07/2021 )

Amazon AWS ($30K)  
“Synthetic Data Augmentation for Deep Learning” [Project Link] (Role: PI, Date: 07/2018-09/2020)

Biogen ($20K)  
“Low-Cost Kinematic Measures for In-Clinic Assessments of Neurodegenerative Diseases” (Role: PI, Date: 05/2019-12/2019)

NSF-IIS 1755695 ($169K)  
“CRII: SCH: Semi-Supervised Physics-Based Generative Model for Data Augmentation and Cross-Modality Data Reconstruction” [Project Link] (Role: PI, Date: 06/2018-06/2020 )

Northeastern Tier 1 Award ($50K)  
“Decoding Situational Empathy: A Graph Theoretic Approach towards Introducing a Quantitative Empathy Measure” [Project Link] (Role: PI, Date: 07/2017-09/2018 )

MathWorks Microgrant ($20K)  
“Compressive Sensing for In-Shoe Pressure Monitoring” [Project Link] (Role: PI, Date: 06/2017-06/2018)

MathWorks Microgrant ($20K)  
“Curriculum Development: Biomedical Sensors and Signals” (Role: PI, Date: 03/2016-06/2017)

NSF SBIR PHASE I-1248587 ($150K) 
“Pressure Map Analytics for Ulcer Prevention” (Role: PI, Date: 01/2013-06/2013)