Projects & Research Work

This page highlights selected HELLO research projects, industrial systems, and open-source contributions spanning Explainable AI, Computer Vision, Anomaly Detection, and Industrial AI.

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/video-anomaly-detection-review/" rel="permalink">From Reconstruction to Reasoning: The Evolution of Deep Learning Architectures for Video Anomaly Detection </a>

      <span class="pub-category-badge pub-category-video-anomaly-detection-deep-learning">
        Video Anomaly Detection / Deep Learning
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      A comprehensive study of the evolution of video anomaly detection, from reconstruction and prediction methods to transformers, foundation models, and reasoning-oriented approaches.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/video-anomaly-detection-review/" class="custom-btn btn-paper">Project Page</a>

  </p>

    <p class="pub-meta">
      
        <strong>Status:</strong> Manuscript in Preparation
      
    </p>
  
</div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/time-series-anomaly-detection/" rel="permalink">Deep Learning for Time-Series Anomaly Detection </a>

      <span class="pub-category-badge pub-category-time-series-anomaly-detection">
        Time-Series / Anomaly Detection
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      Research on deep learning and one-class approaches for time-series anomaly detection, including robust training, threshold calibration, and evaluation on benchmark datasets.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/time-series-anomaly-detection/" class="custom-btn btn-paper">Project Page</a>

  </p>

    <p class="pub-meta">
      
        <strong>Status:</strong> Ongoing Research
      
    </p>
  
</div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/sam-xai/" rel="permalink">Segmentation-Aware Explainable AI with SAM and Shapley Attribution </a>

      <span class="pub-category-badge pub-category-explainable-ai-computer-vision">
        Explainable AI / Computer Vision
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      Investigating SAM-based hierarchical image segmentation and Shapley attribution for spatially coherent and quantitatively evaluated computer vision explanations.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/sam-xai/" class="custom-btn btn-paper">Project Page</a>

  </p>

    <p class="pub-meta">
      
        <strong>Status:</strong> Ongoing Research
      
    </p>
  
</div>

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  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/quantum-anomaly-detection/" rel="permalink">Quantum Machine Learning for Anomaly Detection </a>

      <span class="pub-category-badge pub-category-quantum-machine-learning-anomaly-detection">
        Quantum Machine Learning / Anomaly Detection
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      Exploratory research on variational quantum models and quantum-enhanced representations for anomaly detection.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/quantum-anomaly-detection/" class="custom-btn btn-paper">Project Page</a>

  </p>

    <p class="pub-meta">
      
        <strong>Status:</strong> Exploratory Research
      
    </p>
  
</div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/explainable-vqa/" rel="permalink">Explainable Multimodal Visual Question Answering </a>

      <span class="pub-category-badge pub-category-multimodal-ai-explainable-ai">
        Multimodal AI / Explainable AI
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      Investigating explainability and faithfulness in multimodal visual question answering using vision-language models and gradient-based attribution methods.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/explainable-vqa/" class="custom-btn btn-paper">Project Page</a>

  </p>

    <p class="pub-meta">
      
        <strong>Status:</strong> Ongoing Research
      
    </p>
  
</div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/explainable-medical-ai/" rel="permalink">Explainable Deep Learning for Medical Image Analysis </a>

      <span class="pub-category-badge pub-category-medical-imaging-explainable-ai">
        Medical Imaging / Explainable AI
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      Research on explainable deep learning for medical image classification and analysis, combining modern CNN architectures with interpretable prediction methods.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/explainable-medical-ai/" class="custom-btn btn-paper">Project Page</a>

  </p>

    <p class="pub-meta">
      
        <strong>Status:</strong> Ongoing Research
      
    </p>
  
</div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/edm-interpretable-ml/" rel="permalink">Interpretable Hierarchical Machine Learning for Small-Sample Prediction of Surface and Tribological Responses in Electrical Discharge Machining </a>

      <span class="pub-category-badge pub-category-interpretable-ml-smart-manufacturing">
        Interpretable ML / Smart Manufacturing
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      Interpretable hierarchical machine learning for small-sample prediction and analysis of surface and tribological responses in electrical discharge machining.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/edm-interpretable-ml/" class="custom-btn btn-paper">Project Page</a>

  </p>

    <p class="pub-meta">
      
        <strong>Status:</strong> Ongoing Research
      
    </p>
  
</div>

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  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/edge-xad/" rel="permalink">EdgeXAD: Visual Anomaly Detection on Edge Devices </a>

      <span class="pub-category-badge pub-category-edge-ai-visual-anomaly-detection">
        Edge AI / Visual Anomaly Detection
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      Developing efficient normal-only visual anomaly detection pipelines for deployment on resource-constrained edge devices and RGB camera systems.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/edge-xad/" class="custom-btn btn-paper">Project Page</a>

  </p>

    <p class="pub-meta">
      
        <strong>Status:</strong> Ongoing Research
      
    </p>
  
</div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/distrimuse-industrial-dataset/" rel="permalink">DistriMuSe Industrial Robotics Safety Dataset </a>

      <span class="pub-category-badge pub-category-industrial-ai-dataset">
        Industrial AI / Dataset
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      A multi-view RGB dataset for unexpected-condition detection and human safety in industrial robotic palletizing workflows, including normal and anomalous operating scenarios.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/distrimuse-industrial-dataset/" class="custom-btn btn-paper">Project Page</a>

  </p>

    <p class="pub-meta">
      
        <strong>Status:</strong> Dataset in Preparation
      
    </p>
  
</div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/anomaly-detection-trust-case-study/" rel="permalink">Trustworthy Anomaly Detection: Explainability and Evaluation </a>

      <span class="pub-category-badge pub-category-anomaly-detection-trustworthy-ai">
        Anomaly Detection / Trustworthy AI
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      An open-source research project investigating anomaly detection baselines, explainability methods, faithfulness metrics, reproducibility, and trustworthy model evaluation.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/anomaly-detection-trust-case-study/" class="custom-btn btn-paper">Project Page</a>

  </p>

    <p class="pub-meta">
      
        <strong>Status:</strong> Ongoing Open-Source Research
      
    </p>
  
</div>

  <div class="pub-thumb project-thumb">
    <img src=
      
        "https://rashidrao-pk.github.io//images/../files/projects/advis/Thumbnail_ADVIS_SR_2.png"
      
      alt="ADVIS-SR: Real-Time Anomaly Detection for Safe Human–Robot Interaction in real industrial scenario">
  </div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/advis-distrimuse-sr/" rel="permalink">ADVIS-SR: Real-Time Anomaly Detection for Safe Human–Robot Interaction in real industrial scenario </a>

      <span class="pub-category-badge pub-category-eu-project">
        EU Project 🇪🇺
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      Industrial Safety Detector using deep Generative models based Anomaly Detection on real world

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/advis-distrimuse-sr/" class="custom-btn btn-paper">Project Page</a>

      <a href="https://github.com/rashidrao-pk/advis_distrimuse_unito_SR" target="_blank" class="custom-btn btn-code">Code</a>
    
      <a href="https://informatica.unito.it/do/progetti.pl/Show?_id=n2h1" target="_blank" class="custom-btn btn-docs">Docs</a>
    
  </p>

    <p class="pub-meta">
      
        <strong>Type:</strong> Deployment Project
      
         · 
        <strong>Status:</strong> Ongoing Research
      
         · 
        <strong>Year:</strong> 2026
      
    </p>
  
    <p class="pub-meta">
      <strong>Research Area:</strong>
      Computer Vision, Edge AI, Anomaly Detection, Industrial Safety
    </p>
  
  <p class="pub-meta">
    <strong>Subcategory:</strong>
    Industrial AI
  </p>
  
    <p class="pub-meta">
      <strong>Technologies:</strong>
      Python, Edge Devides, PyTorch, OpenCV, VAE-GAN models, ROS2, Zenoh messages
    </p>
  
</div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/nids-scnn/" rel="permalink">NIDS-SCNN: Lightweight and Explainable Network Intrusion Detection </a>

      <span class="pub-category-badge pub-category-cybersecurity-explainable-ai">
        Cybersecurity / Explainable AI
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      Lightweight CNN-based network intrusion detection using time-frequency representations and explainable AI.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/nids-scnn/" class="custom-btn btn-paper">Project Page</a>

  </p>

    <p class="pub-meta">
      
        <strong>Status:</strong> Manuscript in Preparation
      
    </p>
  
</div>

  <div class="pub-thumb project-thumb">
    <img src=
      
        "https://rashidrao-pk.github.io//images/../files/projects/advis/advis_unigra_full.svg"
      
      alt="ADVIS-UniGra: RGB Anomaly Detection for Safe Human–Robot Collaboration">
  </div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/advis-unigra/" rel="permalink">ADVIS-UniGra: RGB Anomaly Detection for Safe Human–Robot Collaboration </a>

      <span class="pub-category-badge pub-category-eu-projects">
        EU Projects 🇪🇺
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      RGB-based anomaly detection application for safety monitoring in collaborative robotics environments using synthetic industrial data.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/advis-unigra/" class="custom-btn btn-paper">Project Page</a>

      <a href="https://github.com/rashidrao-pk/advis_distrimuse_unito" target="_blank" class="custom-btn btn-code">Code</a>
    
      <a href="https://informatica.unito.it/do/progetti.pl/Show?_id=n2h1" target="_blank" class="custom-btn btn-docs">Docs</a>
    
  </p>

    <p class="pub-meta">
      
        <strong>Type:</strong> Research Application
      
         · 
        <strong>Status:</strong> Prototype Delievered
      
         · 
        <strong>Year:</strong> 2025
      
    </p>
  
    <p class="pub-meta">
      <strong>Research Area:</strong>
      Computer Vision, Anomaly Detection, Explainable AI
    </p>
  
  <p class="pub-meta">
    <strong>Subcategory:</strong>
    Industrial AI
  </p>
  
    <p class="pub-meta">
      <strong>Technologies:</strong>
      Python, PyTorch, OpenCV, ROS2, Zenoh
    </p>
  
</div>

  <div class="pub-thumb project-thumb">
    <img src=
      
        "https://rashidrao-pk.github.io//images/../files/papers_data/shapbpt/shapbpt_thumbnail.png"
      
      alt="ShapBPT: Image Feature Attributions using Data-Aware Binary Partition Trees">
  </div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/shap-bpt/" rel="permalink">ShapBPT: Image Feature Attributions using Data-Aware Binary Partition Trees </a>

      <span class="pub-category-badge pub-category-research-xai">
        Research/XAI
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      A data-aware XAI method for image feature attribution using Binary Partition Trees and hierarchical Shapley values.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/shap-bpt/" class="custom-btn btn-paper">Project Page</a>

      <a href="https://github.com/amparore/shap_bpt" target="_blank" class="custom-btn btn-code">Code</a>
    
      <a href="https://shapbpt.readthedocs.io/en/latest/" target="_blank" class="custom-btn btn-docs">Docs</a>
    
      <a href="https://ojs.aaai.org/index.php/AAAI/article/view/39699" target="_blank" class="custom-btn btn-paper">Paper</a>
    
  </p>

    <p class="pub-meta">
      
        <strong>Type:</strong> Research Project
      
         · 
        <strong>Status:</strong> Completed
      
         · 
        <strong>Year:</strong> 2025-2026
      
    </p>
  
    <p class="pub-meta">
      <strong>Research Area:</strong>
      Computer Vision, Edge AI, Anomaly Detection, Industrial Safety
    </p>
  
  <p class="pub-meta">
    <strong>Subcategory:</strong>
    Image Feature Attribution, Shapley Values, Binary Partition Trees
  </p>
  
    <p class="pub-meta">
      <strong>Technologies:</strong>
      Python, Edge Devides, PyTorch, OpenCV, VAE-GAN models, ROS2, Zenoh messages
    </p>
  
</div>

  <div class="pub-thumb project-thumb">
    <img src=
      
        "https://rashidrao-pk.github.io//images/../files/projects/edge_AI_thumb.png"
      
      alt="AI on Edge Devices">
  </div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/ai-on-edge-devices/" rel="permalink">AI on Edge Devices </a>

      <span class="pub-category-badge pub-category-research-edge-ai">
        Research/Edge AI
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      Lightweight AI deployment on edge devices, including Raspberry Pi-based computer vision systems.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/ai-on-edge-devices/" class="custom-btn btn-paper">Project Page</a>

      <a href="https://github.com/rashidrao-pk/AI_on_Edge_Devices" target="_blank" class="custom-btn btn-code">Code</a>
    
  </p>

    <p class="pub-meta">
      
        <strong>Type:</strong> Deployment Project
      
         · 
        <strong>Status:</strong> Completed
      
         · 
        <strong>Year:</strong> 2025
      
    </p>
  
    <p class="pub-meta">
      <strong>Research Area:</strong>
      Edge AI, Computer Vision, Embedded AI
    </p>
  
    <p class="pub-meta">
      <strong>Technologies:</strong>
      Python, Raspberry Pi, TensorFlow Lite, OpenCV
    </p>
  
</div>

  <div class="pub-thumb project-thumb">
    <img src=
      
        "https://rashidrao-pk.github.io//images/../files/papers_data/XAD/anomaly_detection_xai.gif"
      
      alt="Explainable Anomaly Detection">
  </div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/explainable-anomaly-detection/" rel="permalink">Explainable Anomaly Detection </a>

      <span class="pub-category-badge pub-category-research-xai-ad">
        Research/XAI, AD
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      A case study on building trust in anomaly detection systems using VAE-GAN models and explainable AI.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/explainable-anomaly-detection/" class="custom-btn btn-paper">Project Page</a>

      <a href="https://github.com/rashidrao-pk/anomaly_detection_trust_case_study" target="_blank" class="custom-btn btn-code">Code</a>
    
  </p>

    <p class="pub-meta">
      
        <strong>Type:</strong> Research Project
      
         · 
        <strong>Status:</strong> Published
      
         · 
        <strong>Year:</strong> 2024
      
    </p>
  
    <p class="pub-meta">
      <strong>Research Area:</strong>
      Explainable AI, Anomaly Detection, Computer Vision
    </p>
  
    <p class="pub-meta">
      <strong>Technologies:</strong>
      Python, PyTorch, VAE-GAN, XAI
    </p>
  
</div>

  <div class="pub-thumb project-thumb">
    <img src=
      
        "https://rashidrao-pk.github.io//images/../files/papers_data/lime/LIME_Thumbnail.png"
      
      alt="LIME Stratified Sampling">
  </div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/lime-stratified-sampling/" rel="permalink">LIME Stratified Sampling </a>

      <span class="pub-category-badge pub-category-research-xai">
        Research/XAI
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      An improved LIME sampling strategy for generating more stable and reliable image explanations.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/lime-stratified-sampling/" class="custom-btn btn-paper">Project Page</a>

      <a href="https://github.com/rashidrao-pk/lime_stratified" target="_blank" class="custom-btn btn-code">Code</a>
    
      <a href="https://ojs.aaai.org/index.php/AAAI/article/view/29397" target="_blank" class="custom-btn btn-paper">Paper</a>
    
  </p>

    <p class="pub-meta">
      
        <strong>Type:</strong> Research Project
      
         · 
        <strong>Status:</strong> Published
      
         · 
        <strong>Year:</strong> 2024
      
    </p>
  
    <p class="pub-meta">
      <strong>Research Area:</strong>
      Explainable AI, Computer Vision, Image Explanations
    </p>
  
    <p class="pub-meta">
      <strong>Technologies:</strong>
      Python, LIME, Computer Vision, XAI
    </p>
  
</div>

  <div class="pub-thumb project-thumb">
    <img src=
      
        "https://rashidrao-pk.github.io//images/../files/projects/freelance.png"
      
      alt="Applied and Freelance Research Projects">
  </div>

<div class="pub-content project-content">

  <h2 class="archive__item-title" itemprop="headline">
    <a href="https://rashidrao-pk.github.io//projects/applied-freelance-research/" rel="permalink">Applied and Freelance Research Projects </a>

      <span class="pub-category-badge pub-category-applied-ai">
        Applied AI
      </span>
    
  </h2>

    <p class="archive__item-excerpt">
      Applied research and freelance projects in medical imaging, computer vision, machine learning, and intelligent decision systems.

    </p>
  
   <p class="pub-buttons">
    <a href="https://rashidrao-pk.github.io//projects/applied-freelance-research/" class="custom-btn btn-paper">Project Page</a>

      <a href="https://github.com/rashidrao-pk/r4sshd/tree/main/project_completed" target="_blank" class="custom-btn btn-code">GitHub</a>
    
      <a href="/projects/feedbacks/" class="custom-btn btn-demo">Testimonials</a>
    
  </p>

    <p class="pub-meta">
      
        <strong>Type:</strong> Applied Research
      
         · 
        <strong>Status:</strong> Completed
      
         · 
        <strong>Year:</strong> 2017–2022
      
    </p>
  
    <p class="pub-meta">
      <strong>Research Area:</strong>
      Medical Imaging, Computer Vision, Machine Learning
    </p>
  
    <p class="pub-meta">
      <strong>Technologies:</strong>
      MATLAB, Python, Deep Learning, Machine Learning
    </p>
  
</div>

Muhammad Rashid

Projects & Research Work