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@HaloMind-Research

Halo Mind Research Group

Independent & Inter-Disciplinary Research Group focusing on engineering hardware-efficient neural mechanisms, and much more...

The Halo Mind Research Group

Hybrid Architectures & Lightweight Optimization | Machine Intelligence & Neural Dynamics

Halo Mind is a distributed & Inter-Disciplinary AI research group focused on engineering hardware-efficient neural mechanisms, optimized architectures, and much more... Our core mandate is bridging continuous physical dynamics with discrete neural computation to deploy robust architectures in mission-critical, harsh environments.

Our architectural focus centers on:

  • Sub-Quadratic Sequence Modeling (SSM's)
  • Deep Learning Architectures
  • Space AI
  • Medical Vision
  • OCR
  • Distribution-Free Uncertainty Quantification

& much more...

Active Research Projects

  1. Space Weather & Remote Sensing: Deploying CNN-DDL frameworks with dynamic $\Delta$-gates for zero-shot solar cycle generalization and aerospace defect detection.
  2. Volumetric Medical Imaging: Formulating geometric residual learning blocks to resolve representation drift in 3D State Space Models for concentric cardiac segmentation.
  3. Ancient Epigraphy & Complex Vision: Engineering end-to-end self-supervised OCR pipelines (SimCLR + WGAN-GP) for highly degraded historical scripts.

Full Portfolio & Publications: halomind-research.github.io

Contact: halomind.research.group@gmail.com

Popular repositories Loading

  1. DDV-Mamba_for_Efficient_Remote_Sensing DDV-Mamba_for_Efficient_Remote_Sensing Public

    DDV-Mamba: A highly efficient hierarchical vision model utilizing 2D Deep Delta Learning and SSM-Gated Aggregation for real-time satellite land-cover classification.

    Jupyter Notebook 3

  2. Conformal-Satellite-Change-Detection Conformal-Satellite-Change-Detection Public

    Official implementation of "Risk-Controlled Urban Change Detection: Conformal Prediction Wrappers for Provable Reliability in High-Resolution Satellite Imagery" using PyTorch.

    Jupyter Notebook 3

  3. Optimizing-Deep-Learning-for-Brain-Tumor-Classification Optimizing-Deep-Learning-for-Brain-Tumor-Classification Public

    Official implementation of the paper Optimizing Deep Learning for Brain Tumor Classification: A Comparative Ablation Study of Preprocessing and Augmentation Strategies. Includes patient-level data …

    Jupyter Notebook 2

  4. DDV-GNet-Space DDV-GNet-Space Public

    Official PyTorch implementation of DDV-GNet: A real-time (853 FPS) gated convolutional neural network for real-time aerospace defect detection.

    Jupyter Notebook 2

  5. SafeMed-SSL SafeMed-SSL Public

    Official implementation of "Uncertainty-Guided Semi-Supervised Learning for Safe Medical Image Classification".

    Jupyter Notebook 2

  6. Interpretable-Solar-Defect-Detection Interpretable-Solar-Defect-Detection Public

    Official code implementation for "Interpretable Solar Panel Defect Detection" . Uses Swin Transformers and Fuzzy Logic for Explainable AI (XAI).

    Jupyter Notebook 2

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