I hold an MS by Research from the International Institute of Information Technology, Hyderabad, where I worked with Prof. Bapi S. Raju on automated sleep stage classification using wearable technology and deep learning. This work allowed me to explore the potential of data science in uncovering insights into human sleep patterns.
My research interests lie in applying deep learning and AI in neurotechnology to improve our understanding and treatment of neural disorders. I am focused on developing AI-driven tools and methods to enhance neuroimaging, neurophysiology, and therapeutic approaches, aiming to support more effective diagnosis and management of neurological conditions. For more details, refer to my resume or drop me an email.
A Deep Dive into Sleep: Single-Channel EEG-Based Sleep Stage Classification with Model Interpretability
, Shivam Sharma, S.Mythirayee, Srijithesh Rajendran, Bapi S. Raju
arXiv
Enhancing Healthcare With EOG: A Novel Approach to Sleep Stage
Classification
, Shivam Sharma, Bapi S. Raju
Accepted at ICASSP 2024
There’s life in that old MEG yet: Depth electrode-like laminar source reconstruction with high precision MEG.
Maciek J Szul; ; Ishita Agarval; Siqi Zhang; Gareth R Barnes; Sven Bestmann; James J Bonaiuto
MEG-UKI'23
International Institute of Information Technology
Research Fellow, Healthcare & Artificial Intelligence (HAI)
- Developed two cutting-edge supervised deep learning models to classify sleep stages using EEG and EOG signals, surpassing existing models in accuracy.
- Preprocessed and utilized the first-ever Indian sleep database, focusing on stroke patients.
- Contributed to the advancement of wearable solutions for sleep apnea detection, bridging the gap between medical research and real-world applications by leveraging deep learning techniques.
ISC Marc Jeannerod, CNRS, UMR 5229
Master's Research Intern
- Implemented simulations to explore the current source density (CSD) transform as part of a project aiming to develop laminar source reconstruction for MEG data
- Conducted in-depth analysis using Current Source Density (CSD) transformations, unveiling dynamic current sources and sinks over time.
- Performed relative power analysis, serving as a valuable marker for delineating deep and superficial cortical layers' activity patterns.
Unversity of Hyderabad
Research Intern
- Recorded in-vivo electrophysiological field potentials from grasshopper optic lobe neurons
- Applied advanced mathematical modeling techniques to analyze and interpret the oscillatory patterns observed in grasshopper optic lobe neurons.
Bharatiya Nabhikiya Vidyut Nigam Limited, Department of Atomic Energy
Winter Research Intern
- Identified Magneto-Hydrodynamic (MHD) instability as a likely cause of failure in the Annular Linear Induction Pump.
- Compared simulation data with on-site flow fluctuations measured using magnetic flowmeters, finding a satisfactory match.
- Eigen Frequency Analysis and Computational Fluid Dynamics (CFD) Analysis
International Institute of Information Technology, Hyderabad
Master of Science by Research in ECE | CGPA: 8.83 | Aug'21 – Present
Jadavpur University, Kolkata
Bachelor of Engineering in EE | CGPA: 8.93 | | July'16 – July'20
- Teaching Assistant: CS9.427.S22: Intro. to Neural & Cognitive Modeling
- Teaching Assistant: CS9.423.S23: Cognitive Science and AI