Curriculum vitae
Last updated .
Education
- — PhD, Computer Science, University of Greenwich, London. Funded by the M³4Impact / E3 doctoral studentship. Supervised by Dr Peter Lawrence and Dr Asim Siddiqui.
- — MSc, Computer Science — Distinction, University of Greenwich, London. Dissertation on real-time fire and smoke detection from video with human-in-the-loop verification.
- — BTech, Computer Science and Engineering, KIIT University, Bhubaneswar, India. Funded by the Study in India Scholarship.
Research experience
- — Doctoral researcher, University of Greenwich. Artificial intelligence for performance-based fire safety engineering: reliability of language model output, retrieval-augmented generation over regulatory documents, and levels of autonomy in safety-critical workflows.
Professional experience
- — Backend Software Engineer Intern, ANTT Robotics R&D. Built and documented REST API endpoints with Node.js, Express and MongoDB. Worked with the machine learning team on a customer-need prediction feature, integrating the OpenAI API through prompt design and response handling. No model was trained or fine-tuned in this work.
- — Web Development Trainee, Spring Rain Pvt Ltd. Full-stack development training placement, working on practical projects.
Publications and talks
- Kanon, S., Lawrence, P., Siddiqui, A. “A Risk-Informed Classification Framework for Artificial Intelligence Autonomy in Fire Safety Engineering Workflows.” Manuscript in preparation with supervisors.
- — “AI in Fire Engineering Workflows: Opportunities, Challenges and Trustworthy Integration.” NRIPS Symposium 2026, University of Greenwich. Internal university research symposium.
Software
- corpusforge — Data-optimisation toolkit: distributed ingestion, deduplication, quality filtering, contamination detection, and matched-compute fine-tuning evaluation. In development.
- fse-ragbench — Retrieval and generation evaluation harness, with a benchmark for retrieval-augmented generation over public fire-safety guidance. In development.
- git4kolibrios — A Git client for KolibriOS, an operating system written largely in x86 assembly. The target is clone over HTTP, written in C against the KolibriOS SDK, which means SHA-1, zlib inflation, packfile parsing and delta resolution all have to be built from scratch. In development.
- Real-time fire and smoke detection from video — MSc dissertation project. Transfer learning with MobileNetV2 and MobileNetV3-Large (TensorFlow/Keras, OpenCV) on a 651-image dataset derived from MIVIA fire-detection video sequences. A PyQt5 operator console routed model alarms to a human reviewer before escalation. The dataset is small, and the size is stated because it bears on what the results can support.
- PrerokGlobal — Team project. Shipment and logistics platform. Team of six; I led backend and DevOps. TypeScript, Node.js, Express, MongoDB, Docker and CI/CD.
Awards and funding
- — M³4Impact / E3 doctoral studentship, University of Greenwich.
- — Study in India Scholarship, funding the BTech at KIIT University.
Technical skills
Languages. Python, TypeScript, JavaScript, Java, C++.
Machine learning and vision. TensorFlow, Keras, OpenCV; transfer learning with MobileNetV2 and MobileNetV3-Large.
Backend and databases. Node.js, Express, REST API design, MongoDB, PostgreSQL, MySQL.
Frontend and interfaces. React, Next.js, Redux, Tailwind CSS, PyQt5.
Infrastructure and platforms. Docker, CI/CD, Git and GitHub, Linux, AWS, Firebase, Vercel.
Fire engineering and building models. buildingEXODUS, SMARTFIRE, openBIM/IFC, IfcOpenShell, Neo4j, RDF.
Service and teaching
- Informal peer mentoring in algorithms, data structures and software engineering.
- Guided students taking part in competitive programming.
- Taught Git and GitHub fundamentals, and mentored students through their first open-source contributions.