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Sakib1263/README.md

Salam

I am Sakib Mahmud, currently working as a Research Assistant at Qatar University (QU) and Hamad Medical Corporation (HMC). My research field primarily revolves around Artificial Intelligence (AI) applications in the HealthCare sector.

Notable Publications

I have 28 publications in peer-reviewed journals and 3 in conference proceedings. Notable mentions:

  • Our proposed NABNet [1] can continuously reconstruct ABP waveforms from PPG and ECG signals (2023, BSPC Elsevier, IF: 5.076), inspired by our pioneering study PPG2ABP first appeared during 2020 [2].
  • Our proposed QUCoughScope [3] is able to reliably detect COVID-19 from cough and breath sounds (2022, Diagnostics MDPI, IF: 3.992).
  • We also reliably detected and quantified the lung infections caused by COVID-19 from Chest X-Ray images (2021, CIBM Elsevier, IF: 6.698) [4] and from Chest CT scans (2021, Diagnostics MDPI, IF: 3.992) [5].
  • Can COVID-19 be reliably estimated from wearable data? We replied to that question in PCovNet [6] (2022, CIBM Elsevier, IF: 6.698).
  • Our team in Qatar University (QU) developed electronic [7] (2022, Sensors MDPI, IF: 3.847) and optoelectronic [8] (2022, JSNA: Physical Elsevier, IF: 4.291) sensor based smart insoles for real-time plantar pressure and temperature data acquisition for home monitoring of patients with foot complications such as Diabetic Neuropathy.

Please visit my Google Scholar and ResearchGate profiles for more details.

Tools I Use

C MATLAB Python R TensorFlow PyTorch PyCharm VSCode Embedded C Arduino Esp32 Google Sheets Tableau LabVIEW Eagle Fusion360 Git GitHub

Current GitHub Stats

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Pinned

  1. TF-1D-2D-Segmentation-End2EndPipelines TF-1D-2D-Segmentation-End2EndPipelines Public

    1D and 2D Segmentation Models with options such as Deep Supervision, Guided Attention, BiConvLSTM, Autoencoder, etc.

    Jupyter Notebook 28 19

  2. TF-1D-2D-ResNetV1-2-SEResNet-ResNeXt-SEResNeXt TF-1D-2D-ResNetV1-2-SEResNet-ResNeXt-SEResNeXt Public

    Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).

    Jupyter Notebook 39 9

  3. Inception-InceptionResNet-SEInception-SEInceptionResNet-1D-2D-Tensorflow-Keras Inception-InceptionResNet-SEInception-SEInceptionResNet-1D-2D-Tensorflow-Keras Public

    Models Supported: Inception [v1, v2, v3, v4], SE-Inception, Inception_ResNet [v1, v2], SE-Inception_ResNet (1D and 2D version with DEMO for Classification and Regression)

    Jupyter Notebook 32 5

  4. DenseNet-1D-2D-Tensorflow-Keras DenseNet-1D-2D-Tensorflow-Keras Public

    Models Supported: DenseNet121, DenseNet161, DenseNet169, DenseNet201 and DenseNet264 (1D and 2D version with DEMO for Classification and Regression)

    Jupyter Notebook 15 3

  5. VGG-1D-2D-Tensorflow-Keras VGG-1D-2D-Tensorflow-Keras Public

    Models Supported: VGG11, VGG13, VGG16, VGG16_v2, VGG19 (1D and 2D versions with DEMO for Classification and Regression).

    Jupyter Notebook 14 2

  6. NABNet NABNet Public

    NABNet: A Nested Attention-guided BiConvLSTM Network for a robust ‎prediction of Blood Pressure components from reconstructed Arterial Blood ‎Pressure waveforms using PPG and ECG Signals

    Jupyter Notebook 33 3