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.
I have 43 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.
