Dr. Sajanraj T D (B.Tech, M.Tech, PhD) is a Software and Data Science Engineer and KTP Associate working on UKRI-funded R&D to deliver business analytics from passenger information data for the UK rail industry. He bridges academia and industry, applying cutting-edge AI/ML research to real-world transport problems.
Current Role
- Software & Data Science Engineer (KTP Associate) — UKRI KTP (Loughborough University + TrainFX Ltd), Feb 2024–Present
- Focus: passenger information analytics, scalable data pipelines, forecasting, and ML-driven decision support.
Previous Experience
- Assistant Professor & Research Associate — Rajagiri School of Engineering & Technology, Jul 2022–Dec 2023 (Web Dev + Data Science teaching; project guidance; HPC admin)
- Senior Research Fellow — DST-funded “Intelligent Data Analytics Platform for a Metro Rail Transport System”, Feb 2021–Jun 2022
- Junior Research Fellow — DST-funded metro analytics project, Feb 2019–Jan 2021
- Software Developer Intern — Healship Technologies, Jun 2018–Dec 2018 (AI apps: face recognition, detection, classification)
Core Skills
AI/DS: Machine Learning, Deep Learning, LLMs, Computer Vision, forecasting & anomaly/outlier detection, data visualization.
Engineering: AWS, EC2, microservices, cluster computing, ETL, Docker, Kubernetes, ArgoCD, CI/CD, Linux/server administration.
Tools: Python, PySpark, Hadoop, Hive, MySQL, Django/Flask, TensorFlow/Keras, OpenCV, Power BI, Git/GitHub.
Education
- PhD (Computer Science & Engineering — Data Science) — Christ (Deemed to be University), Bengaluru (Awarded Aug 2024)
- M.Tech (CSE) — APJ Abdul Kalam Technological University (KTU)
- B.Tech (CSE) — Cochin University of Science and Technology (CUSAT)
Selected Publications
- Operational pattern forecast improvement with outlier detection in metro rail transport system — Multimedia Tools and Applications (Q1), 2023
- JP-DAP: An Intelligent Data Analytics Platform for Metro Rail Transport Systems — IEEE Transactions on Intelligent Transportation Systems, 2021
- Passenger Flow Prediction from AFC Data Using Station Memorizing LSTM for Metro Rail Systems — Neural Network World, 2021
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