Hassan Ghasemzadeh is an Associate Professor of Biomedical Informatics at Arizona State University (ASU) and an Adjunct Faculty of Computer Science at Washington State University (WSU). He is also a graduate faculty of the computer science, computer engineering, and biomedical engineering programs at ASU. Prior to joining ASU, he was an Assistant/Associate Professor of Computer Science at WSU (2014-2021), a Postdoctoral Research Manager at the University of California Los Angeles (UCLA) Computer Science Department (2011-2013), and an Adjunct Professor of Biomedical Informatics at San Diego State University (SDSU).
His research interests include mobile health, machine learning, embedded systems, and algorithm design. His work has been recognized by NSF CAREER award, NSF CRII award, WSU Early Career award, WSU outstanding communication, connection, and engagement award, WSU academic advisor excellence award, BSN best paper honorable mention, ACM TiiS best paper award nomination, CVPR Workshop best paper runner-up award, UbiComp/ISWC best wearables note award, IEEE RTAS best paper award, ACM HotMobile best poster award, ACM DATE conference best paper award nomination, Pullman Regional Hospital Community Health Impact fellowship, West Health Institute postdoctoral fellowship, and SDSU faculty of the year award.
Latest
- Multimodal examination of daily stress rhythms in chronic Cannabis users
- Domain-Informed Label Fusion Surpasses LLMs in Free-Living Activity Classification
- Minimum-Cost Channel Selection in Wearables
- Poster: HydraSense: Personalized Hydration Monitoring with Wearables and Machine Learning [Abstract]
- Wavelet-Augmented Self-Supervised Learning for Accurate Classification of Cognitive Workload
- AI-Powered Detection of Freezing of Gait Using Wearable Sensor Data in Patients with Parkinson’s Disease [Abstract]
- Adversarial Transferability in Embedded Sensor Systems: An Activity Recognition Perspective
- Efficient Sensing and Classification for Extended Battery Life
- Stress Monitoring in Free-Living Environments
- Neonatal Risk Modeling and Prediction
- Personalized Modeling and Detection of Moments of Cannabis Use in Free-Living Environments
- GlucoseAssist: Personalized Blood Glucose Level Predictions and Early Dysglycemia Detection
- GlySim: Modeling and Simulating Glycemic Response for Behavioral Lifestyle Interventions
- Inter-Beat Interval Estimation with Tiramisu Model: A Novel Approach with Reduced Error
- Model-Agnostic Structural Transfer Learning for Cross-Domain Autonomous Activity Recognition
- Use of Machine Learning to Predict Medication Adherence in Individuals at Risk for Atherosclerotic Cardiovascular Disease
- Computational Framework for Sequential Diet Recommendation: Integrating Linear Optimization and Clinical Domain Knowledge
- ADARP: A Multi Modal Dataset for Stress and Alcohol Relapse Quantification in Real Life Setting
- Multimodal Time-Series Activity Forecasting for Adaptive Lifestyle Intervention Design
- Forewarning Postprandial Hyperglycemia with Interpretations using Machine Learning
- On-Device Machine Learning for Diagnosis of Parkinson's Disease from Hand Drawn Artifacts
- Probabilistic Cascading Classifier for Energy-Efficient Activity Monitoring in Wearables
- Continual Learning for Activity Recognition
- Stressalyzer: Convolutional Neural Network Framework for Personalized Stress Classification
- Boosting Lying Posture Classification with Transfer Learning
- Designing Deep Neural Networks Robust to Sensor Failure in Mobile Health Environments
- Comparing the Predictability of Sensor Modalities to Detect Stress from Wearable Sensor Data
- Stress Classification and Personalization: Getting the most out of the least
- Associations between Physiological Signals Captured using Wearable Sensors and Self-Reported Outcomes among Patients in AUD Recovery: Development and Usability Study
- CL-Gym: Full-Featured PyTorch Library for Continual Learning
- LIDS: Mobile System to Monitor Type and Volume of Liquid Intake
- Personalized Activity Recognition using Partially Available Target Data
- Linear Mode Connectivity in Multitask and Continual Learning
- Mobile Health for Alcohol Recovery and Relapse Prevention
- Design and Evaluation of a Wearable Assistive Technology for Hemianopic Stroke Patients
- Understanding the Role of Training Regimes in Continual Learning
- TransNet: Minimally-Supervised Deep Transfer Learning for Dynamic Adaptation of Wearable Systems
- Transfer Learning for Activity Recognition in Mobile Health
- Dropout as an Implicit Gating Mechanism For Continual Learning
- Optimal Policy for Deployment of Machine Learning Models on Energy-Bounded Systems
- A Dynamic Programming Framework for DVFS-Based Energy-Efficiency in Multicore Systems
- ActiLabel: A Combinatorial Transfer Learning Framework for Activity Recognition
- Adversarial Transferability in Wearable Sensor Systems
- Malaria epidemics in India: Role of climatic condition and control measures
- Memory-Aware Active Learning in Mobile Sensing Systems
- Proximity-Based Active Learning for Eating Moment Recognition in Wearable Systems
- Improved Knowledge Distillation via Teacher Assistant
- Adar: Adversarial Activity Recognition in Wearables
- Big vs little core for energy-efficient Hadoop computing
- CyclePro: A Robust Framework for Domain-Agnostic Gait Cycle Detection
- ECoST: Energy-Efficient Co-Locating and Self-Tuning MapReduce Applications
- Gait Speed and Survival of Older Surgical Patient with Cancer: Prediction after Machine Learning
- How Accurate Your Activity Tracker Is? A Comparative Study of Step Counts in Low-Intensity Physical Activities
- Human-in-the-Loop Learning for Personalized Diet Monitoring from Unstructured Mobile Data
- LabelForest: Non-Parametric Semi-Supervised Learning for Activity Recognition
- Mindful Active Learning
- Resource-Efficient Computing in Wearable Systems
- Resource-Efficient Wearable Computing for Real-Time Reconfigurable Machine Learning: A Cascading Binary Classification
- Robust Interbeat Interval and Heart Rate Variability Estimation Method from Various Morphological Features using Wearable Sensors
- Share-n-Learn: A Framework for Sharing Activity Recognition Models in Wearable Systems with Context-Varying Sensors
- Toward Ultra-Low-Power Remote Health Monitoring: An Optimal and Adaptive Compressed Sensing Framework for Activity Recognition
- A Dynamic Programming Technique for Energy-Efficient Multicore Systems
- Architectural considerations for FPGA acceleration of machine learning applications in MapReduce
- Autonomous Training of Activity Recognition Algorithms in Mobile Sensors: A Transfer Learning Approach in Context-Invariant Views
- Design Space Exploration for Hardware Acceleration of Machine Learning Applications in MapReduce
- Digital Health for Geriatric Oncology
- Electronic Assessment of Physical Decline in Geriatric Cancer Patients
- Energy-efficient acceleration of MapReduce applications using FPGAs
- Impact of Cache Voltage Scaling on Energy-Time Pareto Frontier in Multicore Systems
- Monitoring Lung Mechanics during Mechanical Ventilation using Machine Learning Algorithms
- New Technologies in Geriatric Oncology Care
- Personalized Human Activity Recognition Using Convolutional Neural Networks
- Predicting Adherence to Use of Remote Health Monitoring Systems in a Cohort of Patients with Chronic Heart Failure
- Speech2Health: A Mobile Framework for Monitoring Dietary Composition From Spoken Data
- Toward visual field assessment using head-worn sensing devices
- Trading Off Power Consumption and Prediction Performance in Wearable Motion Sensors: An Optimal and Real-Time Approach
- A beverage intake tracking system based on machine learning algorithms, and ultrasonic and color sensors: poster abstract
- Adaptive compressed sensing at the fingertip of Internet-of-Things sensors: An ultra-low power activity recognition
- An optimal approach for low-power migraine prediction models in the state-of-the-art wireless monitoring devices
- Context-Aware System Design for Remote Health Monitoring: An Application to Continuous Edema Assessment
- Head-mounted sensors and wearable computing for automatic tunnel vision assessment
- Learn-on-the-go: Autonomous cross-subject context learning for internet-of-things applications
- Mobile sensing to improve medication adherence: demo abstract
- Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges
- Personalization without user interruption: boosting activity recognition in new subjects using unlabeled data
- Synchronous dynamic view learning: a framework for autonomous training of activity recognition models using wearable sensors
- A Hardware-Assisted Energy-Efficient Processing Model for Activity Recognition Using Wearables
- A machine learning approach for medication adherence monitoring using body-worn sensors
- A Reliable and Reconfigurable Signal Processing Framework for Estimation of Metabolic Equivalent of Task in Wearable Sensors
- An asynchronous multi-view learning approach for activity recognition using wearables
- An Energy-Efficient Computational Model for Uncertainty Management in Dynamically Changing Networked Wearables
- Autonomous sensor-context learning in dynamic human-centered internet-of-things environments
- CyHOP: A generic framework for real-time power-performance optimization in networked wearable motion sensors
- Plug-n-learn: automatic learning of computational algorithms in human-centered internet-of-things applications
- S2NI: A mobile platform for nutrition monitoring from spoken data
- SmartSock: A wearable platform for context-aware assessment of ankle edema
- Transfer learning algorithms for autonomous reconfiguration of wearable systems
- Wearable sensors for gait pattern examination in glaucoma patients
- Ultra Low Power Signal Processing in Wearable Monitoring Systems: A Tiered Screening Architecture with Optimal Bit Resolution
- Wearable coach for sport training: A quantitative model to evaluate wrist-rotation in golf.
- Context-Aware Data Processing to Enhance Quality of Measurements in Wireless Health Systems: An Application to MET Calculation of Exergaming Actions
- Impact of sensor misplacement on estimating metabolic equivalent of task with wearables
- Improving Compliance in Remote Healthcare Systems Through Smartphone Battery Optimization
- Investigation of gait characteristics in glaucoma patients with a shoe-integrated sensing system
- Power-Aware Computing in Wearable Sensor Networks: An Optimal Feature Selection
- Smart-Cuff: A wearable bio-sensing platform with activity-sensitive information quality assessment for monitoring ankle edema
- Toward robust and platform-agnostic gait analysis
- Cost-sensitive feature selection for on-body sensor localization
- Designing user-specific plug-n-play into body area networks
- Near-Realistic Mobile Exergames With Wireless Wearable Sensors
- Patient-centric on-body sensor localization in smart health systems
- Power-Aware Activity Monitoring Using Distributed Wearable Sensors
- SmartHealthSys 2014: ACM ubicomp international workshop on smart health systems and applications
- Toward seamless wearable sensing: Automatic on-body sensor localization for physical activity monitoring
- Context-aware signal processing in medical embedded systems: A dynamic feature selection approach
- Multimodal energy expenditure calculation for pervasive health: A data fusion model using wearable sensors
- Objective assessment of overexcited hand movements using a lightweight sensory device
- Pervasive Assessment of Motor Function: A Lightweight Grip Strength Tracking System
- Remote patient monitoring: what impact can data analytics have on cost?
- Ultra low-power signal processing in wearable monitoring systems: A tiered screening architecture with optimal bit resolution
- A Mining Technique Using n-Grams and Motion Transcripts for Body Sensor Network Data Repository
- Automatic Segmentation and Recognition in Body Sensor Networks Using a Hidden Markov Model
- Dynamic self-adaptive remote health monitoring system for diabetics
- Dynamic Task Optimization in Remote Diabetes Monitoring Systems
- Energy-efficient signal processing in wearable embedded systems: an optimal feature selection approach
- Generalized precursor pattern discovery for biomedical signals
- Opportunistic hierarchical classification for power optimization in wearable movement monitoring systems
- WANDA: an end-to-end remote health monitoring and analytics system for heart failure patients
- A wireless communication selection approach to minimize energy-per-bit for wearable computing applications
- An Ultra Low Power Granular Decision Making Using Cross Correlation: Minimizing Signal Segments for Template Matching
- Physical Movement Monitoring Using Body Sensor Networks: A Phonological Approach to Construct Spatial Decision Trees
- Ultra Low Power Granular Decision Making Using Cross Correlation: Optimizing Bit Resolution for Template Matching
- Wireless Fetal Monitoring Device with Provisions for Multiple Births
- A body sensor network with electromyogram and inertial sensors: multimodal interpretation of muscular activities
- A greedy buffer allocation algorithm for power-aware communication in body sensor networks
- A mining technique using n-grams and motion transcripts for body sensor network data repository
- Applications of sensing platforms with wearable computers
- Body sensor networks for baseball swing training: Coordination analysis of human movements using motion transcripts
- Burst communication by means of buffer allocation in body sensor networks: Exploiting signal processing to reduce the number of transmissions
- Collaborative signal processing for action recognition in body sensor networks: a distributed classification algorithm using motion transcripts
- Data Aggregation in Body Sensor Networks: A Power Optimization Technique for Collaborative Signal Processing
- Structural action recognition in body sensor networks: distributed classification based on string matching
- Toward power optimization for communication failure recovery in Body Sensor Networks
- A Distributed Hidden Markov Model for Fine-grained Annotation in Body Sensor Networks
- A Method for Extracting Temporal Parameters Based on Hidden Markov Models in Body Sensor Networks With Inertial Sensors
- An automatic segmentation technique in body sensor networks based on signal energy
- An efficient placement and routing technique for fault-tolerant distributed embedded computing
- Communication minimization for in-network processing in body sensor networks: A buffer assignment technique
- Distributed Continuous Action Recognition Using a Hidden Markov Model in Body Sensor Networks
- Energy-Efficient Information-Driven Coverage for Physical Movement Monitoring in Body Sensor Networks
- Report from HotMobile 2009
- Sport training using body sensor networks: a statistical approach to measure wrist rotation for golf swing
- Wearable coach for sport training: A quantitative model to evaluate wrist-rotation in golf
- A phonological expression for physical movement monitoring in body sensor networks
- Action coverage formulation for power optimization in body sensor networks
- Locomotion Monitoring Using Body Sensor Networks
- A New Approach for Design and Verification of Transaction Level Models
- Modified Pseudo LRU Replacement Algorithm