Research
An ambitious research list is only credible if each item says how far along it is. Below, published work is separated from work in progress, and quantum research is separated from adjacent applied AI.
Published — quantum, cryptography and secure architecture
Publications listed are peer-reviewed research works by members of the Quebex Labs team. Every entry carries a resolvable DOI so you can check it yourself, and the full record is public at ORCID 0000-0002-0717-5888 ↗.
Biswaranjan Senapati, Bharat S. Rawal · Cyber Security and Applications (Elsevier), vol. 1, article 100019, December 2023 · Open access
DOI: 10.1016/j.csa.2023.100019 ↗Business relevanceDirectly underpins our post-quantum cryptography practice: securing industrial data communication against future quantum attacks.
Biswaranjan Senapati, Lalit Narayan Mishra, Awad Bin Naeem, Amit J. Rangari · Cryptography (MDPI), June 2026
DOI: 10.3390/cryptography10030036 ↗Business relevanceEncrypted-by-design communication patterns that inform how we protect sensitive enterprise and government workloads.
Biswaranjan Senapati, Bharat S. Rawal · Cloud Computing and Data Science, March 2025
DOI: 10.37256/ccds.6220256292 ↗Business relevanceQuantum-AI applied to predictive maintenance and energy efficiency in high-density industrial environments.
Published — applied AI in life sciences and industry
Our published record runs on two tracks, and we group them so you can see at a glance which is which. This second track matters commercially for two reasons: the explainability techniques transfer directly into our optimisation and forecasting work, and the clinical diagnostics cluster is the evidence behind our life-sciences practice.
Lalit Narayan Mishra, Biswaranjan Senapati, Saroj Kumar Nayak, Amit J. Rangari · IEEE Access, 2026
DOI: 10.1109/ACCESS.2026.3675540 ↗Business relevanceTransparent, decision-grade forecasting. The same explainability standard we apply to optimisation work in supply chain and logistics.
Awad Bin Naeem, Biswaranjan Senapati, Abdelhamid Zaidi · AI (MDPI), November 2025
DOI: 10.3390/ai6120305 ↗Business relevanceDeep-learning classification expertise that transfers to industrial and agricultural detection use cases.
IEEE Access, 2024
DOI: 10.1109/access.2024.3373646 ↗Business relevanceSensor-derived clinical signals turned into decision support — the same pipeline pattern we apply to industrial condition monitoring.
Peer-reviewed chapter, 2024
DOI: 10.4018/979-8-3693-5946-4.ch024 ↗Business relevanceClassifier accuracy on imbalanced clinical data, which is the hard part of most real diagnostic datasets.
Journal of Computing & Biomedical Informatics, 2023
DOI: 10.56979/402/2023 ↗Business relevanceMethod selection under clinical constraints — choosing the model that can be defended, not the one that scores highest.
Active research tracks
Each track carries a status label. Nothing here is being sold as a finished product.
Automated cryptographic discovery, agility scoring, and machine-readable CBOM output mapped to multi-jurisdiction mandates. This is the research behind the platform described in our Portfolio.
Hybrid models for failure prediction and energy efficiency in high-density industrial environments, building on our published battery-cell manufacturing work.
Reference implementations measured against strong classical solvers on real industrial problem instances. We intend to publish the results including the cases where quantum methods lose.
Specialised models for drought, cloud-burst and pest-event forecasting to support agricultural planning. Grant-track research, not a commercial offering today.
An early AR/VR experiment in making optimisation and simulation output legible to operators. Genuinely exploratory. We mention it because it exists, not because it is available.
Protecting long-lived credentials in large-scale identity and verification systems under post-quantum assumptions. Architectural research; we make no claim of engagement with any national identity programme.
Science leadership
PhD, Computer & Information Science, University of Arkansas at Little Rock. IEEE Senior Member. Peer-reviewed researcher across quantum communication, cryptography and applied AI, with 22+ years as a Platinum-level ERP and SAP consultant.
The work above is collaborative. Across the six peer-reviewed papers listed on this page, our science lead has published with ten co-authors spanning cryptography, applied AI and clinical machine learning, in venues including IEEE Access, Elsevier and MDPI. Every co-author is named on the papers themselves, and every paper carries a DOI you can follow.
We are extending that network into a formal advisory board and building out the technical bench. We will name advisers here once they are confirmed, rather than before.
For research partners and funders
We bring peer-reviewed research in post-quantum cryptography and secure architecture, enterprise delivery experience across SAP, ERP and cloud estates, and a founding team spanning the United Kingdom and the United States.
We are interested in collaborative research and development programmes with academic groups, national labs, government agencies and industry partners — particularly where post-quantum migration, crypto-agility or benchmarked optimisation is the technical core.