Pursuing
Ph.D., Computer Science & Engineering
Indian Institute of Technology Guwahati
Research in AI/signal processing for sleep and respiratory health.
Academic profile
Himanshu Sharma
Ph.D. Research Scholar, Computer Science & Engineering
Indian Institute of Technology GuwahatiAI for Sleep & Respiratory Health
Full-night respiratory event localisation • Multimodal sleep-apnea modelling • Home-oriented OSA screening
Researcher working at the intersection of speech/audio AI, biomedical signals and sleep health, with a focus on clinically useful and accessible screening systems.
SoundAirflowCardiacOxygen
signals→representation→AI→health insight
About
About Himanshu
My research explores how acoustic and physiological signals can be transformed into useful representations for sleep-disordered breathing analysis, respiratory-event modelling and low-cost screening.
Research ecosystem
Signals become useful when their relationships are understood.
Explore the main research themes, modalities and model families.
Education
Academic background
2018–2020
M.Tech, Computer Science & Engineering
National Institute of Technology Hamirpur
CGPA: 8.26/10
2013–2017
B.Tech, Computer Science & Engineering
Quantum Global Campus / Uttarakhand Technical University
77.50%
Selected publications
Recent and representative work
The complete historical publication record is preserved on the Publications page.
SnoreFlowNet: Snore-Intensity and Airflow Dynamics Along with Cardiovascular Modalities for Deep Learning Based Sleep Apnea Detection
Bibliographic details pending final verification
Time-Aware Whisper: Fusing Whisper Representations with Timing Cues for Stuttering Detection
Bibliographic details pending final verification
Featured work
Research projects as visual stories
Each project explains the problem, signals, model pipeline and practical impact.
Project
Multimodal Sleep Apnea Screening
A research pipeline that combines respiratory acoustics and physiological dynamics for OSA screening.
Snore intensityAirflowECGPPG
Project
Full-night Tracheal Audio Event Modelling
Full-night acoustic representation learning for localising apnea–hypopnea events and estimating burden.
Tracheal audio
Academic profiles
Find and verify the work elsewhere
Research journey
Experience
Ph.D. period – Present
Research Scholar — Sleep / Audio ML
IIT Guwahati
Research on respiratory acoustics, multimodal biomedical signals and machine learning for sleep health.
Aug 2020 – Dec 2021
Data Analyst
Dolcera Information Technology Services Pvt. Ltd.
Patent data analysis, Python automation, ML-assisted categorisation and database querying.
Latest
News & milestones
2026-08-01
SnoreFlowNet accepted at IEEE HealthCom 2026
Recent multimodal sleep-apnea work accepted for IEEE HealthCom 2026.
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