Kiarash Amiri

Independent, reproducible research on why machine-learning intrusion detectors fail when normal network traffic changes. • On 40 weeks of ISP traffic from 50 institutions (CESNET-TimeSeries24), a detector calibrated to 1% false alarms averaged 16.3%. • On UGR'16, the shape of a traffic shift separated attacks from benign change of the same size (ROC-AUC 0.72; magnitude 0.58). • Pre-registered hypotheses; Python pipeline with CI: github.com/Amirikiarash/drift-aware-nids

Monitoring for 3,000+ Linux and Windows servers across 50+ sites of a large retail chain. • Built and run the monitoring layer (PRTG, ManageEngine): sensors, baselines, thresholds, dashboards. • Alert and incident analysis to cut false alarms; thresholds recalibrated as traffic changes. • Knowledge base of 200+ documented solutions from recurring tickets. • Cisco routing and switching; Active Directory (500+ users); SLA reporting. • Remote second-level support since 2024; HP server recovery via iLO.

IT and network support for more than 100 client organisations: Windows, connectivity and application faults. • Configured Kerio Control firewalls and VPN solutions; hardened client perimeters. • Designed WLAN infrastructure and Windows Server file sharing. • Supported Microsoft 365 migrations. • Wrote technical documentation that halved onboarding time for new staff.

Part-time network support for the school; taught the fundamentals of the internet to students.

Coursework: Security Protocols; Applied Cryptography and its mathematical foundations; Security of Modern Communication Systems; Secure Software Development; Database Security; Management of Information Security.

Principal subjects: Algorithm Design; Software Engineering; System Programming; Computer Architecture; Artificial Intelligence; Computer Simulation; Discrete Mathematics; Engineering Statistics and Probability.