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Projects

This page brings together selected funded projects, research collaborations, and open-source software connected to dependable, safe, and explainable AI.

Project Directory

The projects below are based on the official Repository@Hull Worktribe records for Dr Koorosh Aslansefat.

Project Dates Role Funder / Partner Focus
AKT TRUST-LLM 2024 PI Innovate UK / Walton & Co Responsible and trustworthy LLMs for planning-law institutional memory.
KTP: Connexin 2023-2025 Co-I Innovate UK / Connexin Speech-to-text, sensor networks, smart speakers, and adult social care.
iCASE PhD Studentship with QinetiQ 2024-2027 Co-I / supervisor EPSRC / Naimuri, a QinetiQ company LLM assurance, hallucination detection, and model correctness.
iCASE with QinetiQ via Newcastle University 2024-2027 Co-I / supervisor EPSRC / QinetiQ / Newcastle University Knowledge-enhanced LLM assurance.
Digital Twin for Offshore Wind Turbine Gearing 2024-2025 Co-I University of Hull / IIT Madras Physics-informed digital twins for fault diagnosis and prognosis.
Transforming Urban Health 2025 Co-I University of Hull / IIT Madras IoT indoor-air-quality monitoring and citizen-centred health interventions.
Vital Knowledge Exchange Visits 2024 PI University of Hull / IIT Madras Responsible AI knowledge exchange and collaboration building.
Alan Turing Institute Post-Doctoral Enrichment Award 2022 Awardee Alan Turing Institute SafeML and machine-learning safety monitoring.

Grants and Collaborations

The full funding portfolio is listed on the Funding page. Selected collaborations include:

Role Project Partner or funder
Academic Lead Trustworthy AI Agent for Incident Management Innovate UK and Veracity Healthcare
PI TRUST-LLM: Responsible Use of Safe and Trustworthy LLM for Planning Law Innovate UK and Walton & Co
PI OCTOPUS: Mobile Robotic Systems and AI for Monitoring Ports and Estuary Waters International collaboration with France, Spain, and South Korea
PI Vital Knowledge Exchange on Responsible AI Projects UoH-IIT-M and IIT Madras
Co-I LLM Assurance Framework through SafeML EPSRC, QinetiQ, and Newcastle University
Co-I Responsible AI for Care Chatbots Innovate UK and Connexin
Co-I National Edge AI Hub for Real Data EPSRC and 50+ industry partners
Co-I Supergen Offshore Renewable Energy Impact Hub EPSRC and 44+ industry partners
Research Associate SESAME: Secure and Safe Multi-Robot Systems EU H2020
Research Assistant GO0D MAN: Agent-Oriented Zero Defect Manufacturing EU H2020

Open Source

  • SafeML

    Statistical safety monitoring for machine-learning classifiers. SafeML has been used for uncertainty quantification in safety-critical applications and was recommended in German Industry Standard DIN SPEC 92005.

    Repository

  • XWhy / SMILE

    Robust model-agnostic explanation methods for safety-critical machine learning, including Statistical Model-agnostic Interpretability with Local Explanations.

    Repository

  • SafeDrones

    Runtime reliability evaluation for UAVs and multi-drone systems using executable digital twins and safety-aware coordination methods.

    Repository

  • SafeLLM

    Domain-specific safety monitoring for large language models, with applications in wind maintenance and industrial decision support.