Shidhartho Roy, MS
Researcher in Biomedical Engineering
Hello, I'm Shidhartho Roy, a passionate Biomedical Engineer and Research Associate at Carnegie Mellon University. My work is at the exciting intersection of human cognition and engineering, where I employ advanced machine learning and signal processing to enhance healthcare technologies. With a master's degree and a track record of published research, I am deeply invested in innovating for better health outcomes. My technical fluency across programming languages and tech frameworks equips me to tackle complex challenges, while my academic leadership roles underscore my commitment to community and progress.
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Research Interests
My research dynamically bridges biomedical engineering and machine learning to innovate in human-computer interaction and medical diagnostics. At Carnegie Mellon University, I actively dissect the influence of skin pigmentation on biosignal accuracy, enhancing interpretations of Near-Infrared Spectroscopy (NIRS) data. My investigations into EEG signals and decision-making are reshaping user interface design, while my contributions to heart segmentation methods and diabetic retinopathy detection via deep learning illustrate a profound impact on medical image processing. My efforts on COVID-19 detection methodologies exemplify his commitment to tackling pressing health crises with advanced computational techniques. My work not only advances the biomedical field but also offers vital insights for developing equitable and precise healthcare technologies.
Publications
Roy, S., Islam, M., Yusuf, M. S. U., & Jahan, N. (2022). EEG based stress analysis using rhythm specific spectral feature for video game play. Computers in Biology and Medicine, 148, 105849.
Hossain, E., Roy, S., Mohammad, N., Nawar, N. and Dipta, D.R., 2021. Metrics and enhancement strategies for grid resilience and reliability during natural disasters. Applied Energy, 290, p.116709.
Hasan, M. K., Roy, S., Mondal, C., Alam, M. A., Elahi, M. T. E., Dutta, A., Raju, T.U.., Jawad, M.T., & Ahmad, M. (2021). Dermo-DOCTOR: A framework for concurrent skin lesion detection and recognition using a deep convolutional neural network with end-to-end dual encoders. Biomedical Signal Processing and Control, 68, 102661.
Ghosh, T. K., Hasan, M. K., Roy, S., Alam, M. A., Hossain, E., & Ahmad, M. (2021). Multi-class probabilistic atlas-based whole heart segmentation method in cardiac CT and MRI. IEEE Access, 9, 66948-66964.
Hasan, M. K., Alam, M. A., Elahi, M. T. E., Roy, S., & Martí, R. (2021). DRNet: Segmentation and localization of optic disc and Fovea from diabetic retinopathy image. Artificial Intelligence in Medicine, 111, 102001.
Hasan, M. K., Alam, M. A., Dahal, L., Roy, S., Wahid, S. R., Elahi, M. T. E., ... & Khanal, B. (2022). Challenges of deep learning methods for COVID-19 detection using public datasets. Informatics in Medicine Unlocked, 30, 100945.