Shidhartho Roy PhD Student, Biomedical Engineering · Carnegie Mellon University

Shidhartho "Sid" Roy is a Ph.D. student in Biomedical Engineering at Carnegie Mellon University, advised by Prof. Sossena Wood in the Wood Neuro Research Group and co-advised by David Lindlbauer in the Augmented Perception Lab at CMU's Human-Computer Interaction Institute.

His research focuses on making pain measurable beyond the clinic and identifying neurophysiological markers of human experience and behavior. Clinical pain assessments capture only brief snapshots of a condition that changes throughout daily life. To bridge this gap, he develops biomedical devices and virtual reality (VR) systems that translate laboratory pain assessments into self-administered tools, particularly for people with sickle cell disease. His work combines electroencephalography (EEG), autonomic signals, and wearables to investigate how physiological measurements can support pain assessment in everyday settings. Beyond pain, he studies how the brain and body respond to unexpected events in VR and driving environments, exploring whether neurophysiological markers remain reliable during naturalistic activities.

His research has appeared in Journal of Biomedical Optics, The Journal of Pain, Computers in Biology and Medicine, Artificial Intelligence in Medicine, IEEE Access, and SPIE proceedings, with presentations at SfN, BMES, OHBM, and ASH. His first-author work on melanin bias in near-infrared spectroscopy was recognized as a Journal of Biomedical Optics 2024 Top Paper, and he has received CMU BME Research Excellence and Mentorship Awards. His research has been supported by the Bradford and Diane Smith Fellowship in Engineering, the Mastercard Foundation, PITA, and sponsored research from BMW Research Group and Meta Reality Labs. He holds an M.S. in Biomedical Engineering from CMU and a B.Sc. in Electrical and Electronic Engineering from KUET.

Publications

2026

  1. Novel optode sensor development for functional near infrared spectroscopy systems and its use in dark, coarse, and curly hair
    A. Duong, S. Roy, E. Meinert-Spyker, J. Cao, J. Kwasa, J. M. Kainerstorfer, P. Grover, S. Wood
    Clinical and Translational Neurophotonics 2026, Proc. SPIE 13834, 138340HConference
    Paper
  2. Altered Sensory-Pain Transitions in Sickle Cell Disease Reflect Central Sensitization
    S. Roy, J. Disu, N. Mossazghi, L. Abdelmohsen, S. Wood
    Journal of Sickle Cell Disease, 3(Supplement_1), yoag020.057Conference
    Paper
  3. Altered Detection-Pain Transition Profiles and Cortical Signatures of Sensitization in Sickle Cell Disease
    S. Roy, J. Disu, N. Mossazghi, L. Abdelmohsen, E. Meinert-Spyker, S. Wood
    The Journal of Pain, 41, 106022Conference
    Paper

2025

  1. Increased synchronization in cognitive flexibility tasks in Sickle Cell Disease: A Feasibility Study
    N. Mossazghi, S. Roy, J. Disu, L. Abdelmohsen, E. Meinert-Spyker, S. Wood
    Organization for Human Brain Mapping (OHBM) Annual Meeting, Brisbane, Australia, June 2025Conference

2024

  1. Exploring the impact and influence of melanin on frequency-domain near-infrared spectroscopy measurements
    S. Roy, J. Wu, J. Cao, J. Disu, S. Bharadwaj, E. Meinert-Spyker, P. Grover, J. M. Kainerstorfer, S. Wood
    Journal of Biomedical Optics, 29(S3), S33310Journal★ JBO 2024 Top Paper
    PDFPaper
  2. The potential of using a hemodynamic signal as a biomarker of cognitive load in sickle cell disease
    S. Roy, N. Mossazghi, E. Bulger, J. Lin, C. Saber, B. Shinn-Cunningham, J. M. Kainerstorfer, J. Z. Xu, S. Wood
    fNIRS 2024 Biennial Meeting (Birmingham, UK), Blitz presentation Su-088-768, September 2024Conference
    PDF
  3. Assessing the Impact of Cognitive Load on Resting State Tissue Oxygen Saturation in Adult Patients with Sickle Cell Disease
    L. Abdelmohsen, N. Mossazghi, S. Roy, J. D. K. Disu, E. Meinert-Spyker, C. Saber, J. Xu, S. Wood
    Blood, 144(Supplement 1), 3879Conference
    Paper

2022

  1. EEG based stress analysis using rhythm specific spectral feature for video game play
    S. Roy, M. Islam, M. S. U. Yusuf, N. Jahan
    Computers in Biology and Medicine, 148, 105849Journal
    PreprintPaper
  2. Challenges of deep learning methods for COVID-19 detection using public datasets
    M. K. Hasan, M. A. Alam, L. Dahal, S. Roy, S. R. Wahid, M. T. E. Elahi, R. Martí, B. Khanal
    Informatics in Medicine Unlocked, 30, 100945Journal
    PDFPaper

2021

  1. Metrics and enhancement strategies for grid resilience and reliability during natural disasters
    E. Hossain, S. Roy, N. Mohammad, N. Nawar, D. R. Dipta
    Applied Energy, 290, 116709Journal
    Paper
  2. Missing value imputation affects the performance of machine learning: A review and analysis of the literature (2010–2021)
    M. K. Hasan, M. A. Alam, S. Roy, A. Dutta, M. T. Jawad, S. Das
    Informatics in Medicine Unlocked, 27, 100799Journal
    Paper
  3. Solar Energy in the United States: Development, Challenges and Future Prospects
    S. Tabassum, T. Rahman, A. U. Islam, S. Rahman, D. R. Dipta, S. Roy, N. Mohammad, N. Nawar, E. Hossain
    Energies, 14(23), 8142Journal
    PDFPaper
  4. DRNet: Segmentation and localization of optic disc and Fovea from diabetic retinopathy image
    M. K. Hasan, M. A. Alam, M. T. E. Elahi, S. Roy, R. Martí
    Artificial Intelligence in Medicine, 111, 102001Journal
    Paper
  5. Dermo-DOCTOR: A framework for concurrent skin lesion detection and recognition using a deep convolutional neural network with end-to-end dual encoders
    M. K. Hasan, S. Roy, C. Mondal, M. A. Alam, M. T. E Elahi, A. Dutta, S. T. Uddin Raju, M. T. Jawad, M. Ahmad
    Biomedical Signal Processing and Control, 68, 102661Journal
    PreprintPaper
  6. Multi-Class Probabilistic Atlas-Based Whole Heart Segmentation Method in Cardiac CT and MRI
    T. K. Ghosh, M. K. Hasan, S. Roy, M. A. Alam, E. Hossain, M. Ahmad
    IEEE Access, 9, 66948–66964Journal
    PDFPaper

2020

  1. Frequency Impact Analysis with Music-Evoked Stimulated Potentials on Human Brain
    S. Roy, M. Islam, M. S. U. Yusuf, T. I. Rohan
    Innovations in Electronics and Communication Engineering (Springer), pp. 505–513 (Lecture Notes in Networks and Systems)Conference
    Paper
  2. Efficient Approach to Detect Epileptic Seizure using Machine Learning Models for Modern Healthcare System
    T. I. Rohan, M. S. U. Yusuf, M. Islam, S. Roy
    2020 IEEE Region 10 Symposium (TENSYMP), pp. 1783–1786Conference
    Paper
  3. Automatic Mass Classification in Breast Using Transfer Learning of Deep Convolutional Neural Network and Support Vector Machine
    M. K. Hasan, T. A. Aleef, S. Roy
    2020 IEEE Region 10 Symposium (TENSYMP), pp. 110–113Conference
    Paper
  4. CVR-Net: A deep convolutional neural network for coronavirus recognition from chest radiography images
    M. K. Hasan, M. A. Alam, M. T. E. Elahi, S. Roy, S. R. Wahid
    arXiv preprint, arXiv:2007.11993Preprint
    PDFPaper

2019

  1. Age based Mood Swing Analysis and Brain Mapping for Music Genre
    S. Roy, M. S. U. Yusuf, M. Islam, T. I. Rohan
    2019 5th International Conference on Advances in Electrical Engineering (ICAEE), pp. 165–170Conference
    Paper
  2. Efficient two stage approach to detect face liveness: Motion based and Deep learning based
    M. M. Hasan, M. S. U. Yusuf, T. I. Rohan, S. Roy
    2019 4th International Conference on Electrical Information and Communication Technology (EICT), pp. 1–6Conference
    Paper
  3. Stress Identification during Sustained Mental Task and Brain Relaxation Modeling with β/α Band Power Ratio
    M. S. U. Yusuf, M. Islam, S. Roy
    2019 4th International Conference on Electrical Information and Communication Technology (EICT), pp. 1–5Conference
    Paper
Full list on Google Scholar

Experience

Aug 2024 – Present
PhD Student, Biomedical Engineering
Carnegie Mellon University
  • Conducting PhD research on EEG-based biomarkers of pain dysregulation in sickle cell disease.
  • Comparing thermal pain-evoked neural responses between sickle cell disease patients and healthy controls using EEG and NIRS-based methods.
  • Designing an extended reality-based EEG protocol with immersive and haptically synchronized pain stimulation.
Aug 2023 – Aug 2024
Research Associate, Electrical and Computer Engineering
Carnegie Mellon University
  • Investigated cognitive load-induced hemodynamic changes in sickle cell disease using frequency-domain near-infrared spectroscopy.
  • Studied neurovascular responses during Digit Symbol Substitution Task performance.
  • Generated evidence relevant to cognitive workload-aware interface design for clinical populations.
Jan 2022 – Aug 2023
Graduate Research Assistant, Biomedical Engineering
Carnegie Mellon University
  • Characterized the relationship between melanin concentration and near-infrared spectroscopy signals across human participants.
  • Showed reduced arterial oxygen saturation estimates and reduced signal-to-noise ratio in participants with higher melanin index.
  • Conceptualized a novel optode holder design to improve measurement quality in participants with curly hair.
Mar 2020 – Dec 2021
Researcher, Artificial Intelligence in Medical Image Computing Lab
Khulna University of Engineering and Technology
  • Worked on medical image segmentation and localization using convolutional neural networks.
  • Designed residual and skip-connection based methods to recover local information from shallower layers.
  • Applied these methods to heart segmentation in computed tomography and magnetic resonance imaging data.

Education

2024 – Present
Ph.D., Biomedical Engineering
Carnegie Mellon University · Research focus: EEG-based biomarkers of pain dysregulation in sickle cell disease
BME Mentorship Award
2023
M.S., Biomedical Engineering (Research)
Carnegie Mellon University · GPA 3.69/4.0
BME Research Excellence Award
2020
B.Sc., Electrical and Electronic Engineering
Khulna University of Engineering and Technology · GPA 3.64/4.0

Skills & Methods

Modalities
EEG, fMRI, NIRS, FD-NIRS
Analysis
Biomedical signal processing, Machine learning, Monte Carlo simulations
Programming
Python, MATLAB, R, C, C++, C#, Java
Libraries & tools
TensorFlow, Keras, Scikit-learn, NLTK, Unity, Simulink, GitHub
Fabrication
Arduino, 3D printing, Laser cutting