Hassan Ghasemzadeh is a Program Director and a Professor in the College of Health Solutions at Arizona State University (ASU). He is a member of graduate faculty in biomedical informatics & data science, computer science, computer engineering, and biomedical engineering at ASU. Prior to joining ASU, he was an assistant/associate professor of computer science at Washington State University (WSU 2014-2021), and a postdoctoral research manager at the University of California Los Angeles (UCLA 2011-2013). His research interests include digital health, machine learning and algorithm design.
Awards and Honors
- 2026 Best Poster Award, ASU College of Health Solutions Faculty Research Day
- 2025 Best Poster Award Runner Up, IEEE Body Sensor Networks (BSN) Conference
- 2025 Best Poster Award Honorable Mention, IEEE Biomedical & Health Informatics (BHI)
- 2025 Nominee for Outstanding Teaching – Graduate, ASU College of Health Solutions
- 2025 Best Poster Award, ASU College of Health Solutions Faculty Research Day
- 2024 Research Award, ASU College of Health Solutions
- 2024 Best Poster Award, ASU College of Health Solutions Faculty Research Day
- 2022 Best Paper Honorable Mention Award, BSN Conference
- 2020 Best Wearables Note Award, UbiComp/ISWC Conference
- 2020 Best Paper Runner-Up Award, CVPR Workshop on Continual Learning
- 2019 Early Tenure and Promotion, WSU School of EECS
- 2019 Best Paper Award Nomination, ACM Transactions on Interactive Intelligent Systems
- 2019 Academic Advisor Excellence Award, WSU GPSA
- 2019 Best Paper Award, IEEE Council on Electronic Design Automation (CEDA)
- 2018 Early Career Development Award, National Science Foundation (NSF CAREER)
- 2018 Early Career Award, WSU School of EECS
- 2018 Outstanding Communication, Connection & Engagement Award, WSU VCEA
- 2017 Best Paper Award Nomination, IEEE/ACM DATE Conference
- 2017 Community Health Impact Fellowship, Pullman Regional Hospital
- 2016 Research Initiation Initiative Award, National Science Foundation (NSF CRII)
- 2015 Travel Award, NSF Early Career Investigators Workshop on CPS in Smart Cities
- 2012 Main architect of WANDA, licensed to WANDA, Inc., acquired by EMV Capital.
- 2011 Algorithm architect of Sense4Baby, licensed to Sense4Baby, acquired by AirStrip.
- 2011 Best Paper Award, IEEE RTAS Conference
- 2011 Faculty of the Year Award, San Diego State University (SDSU), Biomedical Informatics
- 2009 Best Poster Award, ACM HotMobile
- 2006 Excellence in Teaching Award, CSE Department, Azad University, Damavand
- 2005 Excellence in Teaching Award, CSE Department, Azad University, Damavand
- 2003 Founding Faculty & Chair, CSE Department, Azad University, Damavand
Latest
- Multimodal examination of the acute effects of cannabis on subjective and physiological stress-related outcomes: a randomized placebo-controlled laboratory study
- Gated Adaptation for Continual Learning in Human Activity Recognition
- GluBox: Glucose Prediction for Type 1 Diabetes from Multimodal Wearable Sensors using Region-Sensitive Loss and Bayesian Optimization
- Time-Aware Multimodal Sensor Fusion for Blood Glucose Forecasting in Non-Diabetic Adults
- Counterfactual Modeling with Fine-Tuned LLMs for Health Intervention Design and Sensor Data Augmentation
- Comparable physiological stress responses following music listening and quiet reading: An exploratory pilot study
- GlyTwin: Enhancing Digital Twin for Glucose Control in Type 1 Diabetes using Patient-Centric Counterfactual Treatments
- Contextual Bandit-based MPC Tuning for Optimized Personalization of Physical Activity Behavioral Interventions
- Glycemic-Aware and Architecture-Agnostic Training Framework for Blood Glucose Forecasting in Type 1 Diabetes
- Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health
- Hybrid Attention Model Using Feature Decomposition and Knowledge Distillation for Blood Glucose Forecasting
- Self-Supervised Learning and Opportunistic Inference for Continuous Monitoring of Freezing of Gait in Parkinson’s Disease
- Trustworthy AI in Digital Health: A Comprehensive Review of Robustness and Explainability
- Improving Shape Bias in Learnable Geometric Moment Representations
- AI-Powered Wearable Sensors for Health Monitoring and Clinical Decision Making
- Assessing the quality of reporting in artificial intelligence/machine learning research for cardiac amyloidosis
- SenseCF: LLM-Prompted Counterfactuals for Intervention and Sensor Data Augmentation
- CAN-STRESS: A Real-World Multimodal Dataset for Understanding Cannabis Use, Stress, and Physiological Responses
- Time-Aware Cross-Attention for Multi-Modal Sensor-Based Blood Glucose Forecasting
- LLM-Powered Prediction of Hyperglycemia and Discovery of Behavioral Treatment Pathways from Wearables and Diet
- AZT1D: A Real-World Dataset for Type 1 Diabetes
- Detection and Severity Assessment of Parkinson’s Disease by Analysis of Wearable Sensors Data Using Gramian Angular Fields and Deep Convolutional Neural Networks
- Guiding Diffusion with Deep Geometric Moments: Balancing Fidelity and Variation
- Freezing of Gait Detection Using Gramian Angular Fields and Federated Learning from Wearable Sensors
- AttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset
- Enhancing Metabolic Syndrome Prediction with Hybrid Data Balancing and Counterfactuals
- NutriGen: Personalized Meal Plan Generator Leveraging Large Language Models to Enhance Dietary and Nutritional Adherence
- LEAD: Localized Explanations with Adversarial Decision Boundary Characterization for Interpretable Disease Prediction
- MealMeter: Using Multimodal Sensing and Machine Learning for Automatically Estimating Nutrition Intake
- Cost-Effective Multitask Active Learning in Wearable Sensor Systems
- CUDLE: Learning Under Label Scarcity to Detect Cannabis Use in Uncontrolled Environments using Wearables
- Multimodal examination of daily stress rhythms in chronic Cannabis users
- Domain-Informed Label Fusion Surpasses LLMs in Free-Living Activity Classification
- GlyMan: Glycemic Management using Patient-Centric Counterfactuals
- 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