Poster: Cloud-Based Passenger Safety Monitoring for Agentic Autonomous Public Transport
IEEE VNC 2026
Cloud-based vision-language monitoring for detecting safety-critical incidents inside autonomous public transport.
Research record
Publications
Peer-reviewed papers, conference contributions, posters, and selected preprints. For a citation-oriented record, visit Google Scholar.
2026
Poster: Digital Twin for Optimizing the Electric Bus Fleet Operations Under Network-Induced Uncertainty
IEEE VNC 2026
A communication-aware digital twin for reliable electric-bus fleet scheduling and charging under incomplete telemetry.
MILD: Mediator Agent System with Bidirectional Perception and Multi-Layered Alignment for Human-Vehicle Collaboration
arXiv:2605.01507
An agentic mediator that aligns driver needs, vehicle perception, safety rules, and explainable driving strategies.
2025
An Agentic LLM Framework for Adverse Media Screening in AML Compliance
arXiv:2602.23373
An agentic RAG framework that automates adverse-media screening for AML and KYC compliance.
Cleaning Maintenance Logs with LLM Agents for Improved Predictive Maintenance
arXiv:2511.05311
An evaluation of LLM agents for cleaning noisy maintenance logs used in predictive-maintenance pipelines.
Agentic Vehicles for Human-Centered Mobility: Definition, Prospects, and Synergistic Co-Development with Vehicle Autonomy
arXiv:2507.04996
A framework distinguishing vehicle agency from autonomy and describing how both can co-develop for human-centered mobility.
2024
2019
Triplet Loss and its Applications to Driver Identification and Verification [WIP]
A major issue in driver identification is lack of enough data from the target group of drivers. In this work I use Triplet loss to train neural nets that learn to discriminate between small chunks of driving data. Through this we significantly reduce the amount of data needed to perform accurate driver identification or verification.
Driver Identification only using GPS trajectories: A Deep Learning Approach
This is one of my latest works in which I apply deep learning to problem of driver identification using GPS data collected from smartphone.
2018
Revisiting Gaussian Mixture Models for Driver Identification
Accepted for presentation at IEEE ICVES