Asiful Arefeen
  • Bio
  • Publications
  • Talks
  • News
  • Awards
  • Projects
  • Teaching
  • Recent Talks
    • Counterfactual Explainable Recommendation
    • Adversarial Counterfactual Visual Explanations
    • CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations
    • Generating Interpretable Counterfactual Explanations By Implicit Minimization of Epistemic and Aleatoric Uncertainties
    • Counterfactual Explanations for Multivariate Time Series
    • Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations
    • Forecasting the future clinical events of a patient through contrastive learning
    • Feature Importance Explanations for Temporal Black-Box Models
    • Entropy-based Logic Explanations of Neural Networks
    • Rep-Net: Efficient On-Device Learning via Feature Reprogramming
    • Training Generative Adversarial Networks with Limited Data
    • Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response
    • Augmented Experiment in Material Engineering Using Machine Learning
    • Computational Framework for Sequential Diet Recommendation: Integrating Linear Optimization and Clinical Domain Knowledge
    • Local Interpretable Model-Agnostic Explanations
    • Characterizing Decision Boundary for DNN on High Dimensional Data
    • Grad-CAM for Interpreting DNN Model Decisions
    • Boosting Lying Posture Classification with Transfer Learning
    • Optimizations in Sparse Coding
    • Recent Techniques in Semi-Supervised Learning
    • SNR- Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning
    • Which Tasks Should Be Learned Together in Multi-task Learning?
    • Anywidth Network
    • Paper Review: Attention is All You Need.
    • Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis
    • MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
    • U-Net: Convolutional Networks for Biomedical Image Segmentation
    • Social and competition stress detection with wristband physiological signals
  • Projects
  • Projects
    • GlyMan
    • HydroGuard
    • Smart Home
    • ExAct
  • Teaching
    • BMI 310: App Development for Population Health
    • BMI 502: Foundations of BMI Methods
  • News
    • 🎉 Easily create your own simple yet highly customizable blog
    • 🧠 Sharpen your thinking with a second brain
    • 📈 Communicate your results effectively with the best data visualizations
    • 👩🏼‍🏫 Teach academic courses
    • ✅ Manage your projects
  • Awards
  • Publications
    • Designing User-Centric Behavioral Interventions to Prevent Dysglycemia with Novel Counterfactual Explanations
    • 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
    • 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
    • Forewarning Postprandial Hyperglycemia with Interpretations using Machine Learning
  • Recent news

HydroGuard

Apr 20, 2024 · 1 min read
Image credit: TVBIZZ Magazine

During summer, Phoenix metropoliton experiences temperature as high as 118 F. How AI can help the people who work under the scorching Phoenix sun without proper hudration?

Last updated on Apr 20, 2024
Heat & Health
Asiful Arefeen
Authors
Asiful Arefeen
PhD Candidate
← GlyMan May 10, 2024
Smart Home Apr 20, 2024 →

© 2024 AREFEEN

Published with Hugo Blox Builder — the free, open source website builder that empowers creators.