12 citations · 30 across the 16 of their papers we have counts for
17 papers
Reducing the Adaptation Gap Through Reachable Fisher Geometry
Wasif Jalal, Sachin Deb, Asif Salekin
Parameter-efficient fine-tuning (PEFT) determines not only how many parameters are trained, but also which local directions a model can move in, so similar adapters can affect subg…
Representation Is Not Enough: Body-Localized Thermal Evidence for Contactless Stress and Craving Sensing in Opioid Use Disorder
Sachin Deb, Harshit Sharma, Asif Salekin
Removing wearables from physiological monitoring also removes their supervision: the signal indicating where and when a stress response occurred. Contactless stress sensing therefo…
RETRACE: Resilience-Guided Trait-Conditioned Craving Estimation from Wearable Physiology in Opioid Use Disorder
Yi Xiao, Harshit Sharma, Dessa Bergen-Cico +1
Detecting opioid craving from wearable physiological signals is critical yet difficult, with the potential to support proactive interventions for individuals with opioid use disord…
Ethical Fairness in Ubiquitous Health Sensing without Known Attributes
Shaily Roy, Harshit Sharma, Daniel A. Adler +3
In ubiquitous and mobile health systems, computational models infer human states from wearable, behavioral, and physiological sensing data. In these settings, high accuracy alone i…
UnIT: Scalable Unstructured Inference-Time Pruning for MAC-efficient Neural Inference on MCUs
Ashe Neth, Sawinder kaur, Mohammad Nur Hossain Khan +3
Existing pruning methods are typically applied during training or compile time and often rely on structured sparsity. While compatible with low-power microcontrollers (MCUs), struc…
Human Heterogeneity Invariant Stress Sensing
Yi Xiao, Harshit Sharma, Sawinder Kaur +2
Stress affects physical and mental health, and wearable devices have been widely used to detect daily stress through physiological signals. However, these signals vary due to facto…
CRoP: Context-wise Robust Static Human-Sensing Personalization
Sawinder Kaur, Avery Gump, Yi Xiao +5
The advancement in deep learning and internet-of-things have led to diverse human sensing applications. However, distinct patterns in human sensing, influenced by various factors o…
CurvFed: Curvature-Aligned Federated Learning for Fairness without Demographics
Harshit Sharma, Shaily Roy, Asif Salekin
Modern human sensing applications often rely on data distributed across users and devices, where privacy concerns prevent centralized training. Federated Learning (FL) addresses th…
Only My Model On My Data: A Privacy Preserving Approach Protecting one Model and Deceiving Unauthorized Black-Box Models
Weiheng Chai, Brian Testa, Huantao Ren +2
Deep neural networks are extensively applied to real-world tasks, such as face recognition and medical image classification, where privacy and data protection are critical. Image d…
"Reading Between the Heat": Co-Teaching Body Thermal Signatures for Non-intrusive Stress Detection
Yi Xiao, Harshit Sharma, Zhongyang Zhang +3
Stress impacts our physical and mental health as well as our social life. A passive and contactless indoor stress monitoring system can unlock numerous important applications such…
Classifying Rhoticity of /r/ in Speech Sound Disorder using Age-and-Sex Normalized Formants
Nina R Benway, Jonathan L Preston, Asif Salekin +3
Mispronunciation detection tools could increase treatment access for speech sound disorders impacting, e.g., /r/. We show age-and-sex normalized formant estimation outperforms ceps…
VeriCompress: A Tool to Streamline the Synthesis of Verified Robust Compressed Neural Networks from Scratch
Sawinder Kaur, Yi Xiao, Asif Salekin
AI's widespread integration has led to neural networks (NNs) deployment on edge and similar limited-resource platforms for safety-critical scenarios. Yet, NN's fragility raises con…
Privacy against Real-Time Speech Emotion Detection via Acoustic Adversarial Evasion of Machine Learning
Brian Testa, Yi Xiao, Harshit Sharma +2
Smart speaker voice assistants (VAs) such as Amazon Echo and Google Home have been widely adopted due to their seamless integration with smart home devices and the Internet of Thin…
Psychophysiology-aided Perceptually Fluent Speech Analysis of Children Who Stutter
Yi Xiao, Harshit Sharma, Victoria Tumanova +1
This paper presents a novel approach named PASAD that detects changes in perceptually fluent speech acoustics of young children. Particularly, analysis of perceptually fluent speec…
Psychophysiological Arousal in Young Children Who Stutter: An Interpretable AI Approach
Harshit Sharma, Yi Xiao, Victoria Tumanova +1
The presented first-of-its-kind study effectively identifies and visualizes the second-by-second pattern differences in the physiological arousal of preschool-age children who do s…
Deadwooding: Robust Global Pruning for Deep Neural Networks
Sawinder Kaur, Ferdinando Fioretto, Asif Salekin
The ability of Deep Neural Networks to approximate highly complex functions is key to their success. This benefit, however, comes at the expense of a large model size, which challe…
Preclinical Stage Alzheimer's Disease Detection Using Magnetic Resonance Image Scans
Fatih Altay, Guillermo Ramon Sanchez, Yanli James +3
Alzheimer's disease is one of the diseases that mostly affects older people without being a part of aging. The most common symptoms include problems with communicating and abstract…