Capt (Dr) Sunil Tyagi, Indian Navy (Retd)
Over 32 years of commissioned service in the Indian Navy (1992–2024), Sunil Tyagi's specialist core was submarine acoustic stealth and underwater acoustics. For six years as Head of the Acoustic Stealth Group at the Directorate of Submarine Design, Naval Headquarters, he held design authority for acoustic stealth, shock, noise and vibration across India's nuclear-submarine programme — developing India's first indigenous submarine acoustic model, bringing underwater-radiated-noise estimation in-house, and institutionalising standardised shock-mounting design methods. Earlier appointments ran from engineer officer at sea to submarine diesel engines at Naval Dockyard, Visakhapatnam; later ones to the Naval Trials and Acceptance Authority and the Centre for Air Power Studies.
He holds a PhD in Mechanical Engineering (Applied Machine Learning) from the Defence Institute of Advanced Technology, Pune (2018), with a granted Indian patent in machine-learning-based fault detection and eight peer-reviewed journal papers from that research, and he taught at DIAT and MILIT, Pune. In September 2026 he published the SKANN preprint on arXiv and filed an Indian provisional patent application on open-set vessel re-identification.
Profile, CV, experience and full publication record: suniltyagi.in · LinkedIn · ORCID 0000-0001-5897-7955
Working principles
- Physics first. Classical, interpretable features run alongside learned representations. When a model separates two recordings, the physics should show why.
- Honest measurement. Evaluation protocols are designed to resist flattering scores, and limitations are published with the results.
- Sovereign deployment. Frozen models, galleries that grow in-house, no data egress and no retraining — on the user's own infrastructure.
- Licence-clean. Development on open-source corpora and open-source dependencies; every released artefact carries an explicit licence.
- Unclassified by design. Public materials describe methods at headline level. Programme specifics, customer data and evaluation results from sponsored work are not disclosed.
- Open where it can be. Preprints, CC BY artefacts and MIT-licensed tools, so that results can be checked by anyone who cares to.
Engagements
Oravont has worked under India's national-security AI Grand Challenge (NCIIPC / Startup India, Problem Statement 12, concluded May 2026) and is working under iDEX, Ministry of Defence (DISC5 Challenge 10, Indian Navy, Underwater Domain Awareness, active); it has a research collaboration in formation with IIT Delhi, in association with a DRDO/NSTL programme; and it has submitted iDEX open-challenge proposals as Principal Investigator. Engagements take the form of collaborative R&D, funded research, consultancy and advisory work, and technical training and knowledge transfer in acoustics, vibration and applied machine learning.
- Oravont Systems LLP · registered office C-43, Sector 39, Noida 201303, Uttar Pradesh, India
- Email info@oravontsystems.com · GitHub github.com/Oravont