About

Academic Journey

A PhD candidate in Computing Science at the University of Glasgow (2023–2026). My research focuses on how complex, multi-stage attacks propagate through software supply chains and AI pipelines, and how to detect and attribute them automatically. I combine graph-based learning (temporal graph analysis, provenance graph mining) with runtime behavioral analysis to build detection systems that go beyond static rules.

My research spans software and AI supply chain security, runtime observability, attack attribution, and graph-based threat detection.

Before my PhD, I worked in industry on detection and MLOps-style pipelines (ELK, Airflow, anomaly detection). Selected writing and talks from that period:

Combining Artificial Intelligence with Threat Intelligence — JUMPSEC guide on sourcing, consuming, and operationalising threat intel with ML
Implementation and Dynamic Generation for Tasks in Apache Airflow — JUMPSEC Labs technical note on DAG structure, dynamic tasks, and cross-DAG dependencies
Talk involving projects I did — YouTube segment
JUMPSEC works on a prototype lightweight anomaly detection system — SecuritySenses overview of the Airflow + Deeplog-style prototype and design goals

I work primarily with Python, Go, and Rust, and have a strong focus on building tools that are deployable, not just publishable.

Technical Capabilities

Detection & Analysis Pipelines End-to-end threat detection — from data collection (Zeek, ELK, Airflow) through feature engineering and model training to alert triage. Experience with graph databases (Neo4j) and vector search (Milvus) for security analytics.
Security Engineering (DevSecOps) Hands-on application security across the SDLC: OWASP Top 10 testing, SBOM/SLSA compliance, WAF tuning, log-based IOC matching. Practical blue-team experience with SIEM workflows and network traffic inspection.
AI/LLM Security Jailbreak and prompt-injection evaluation, safety guardrails, model supply chain integrity. Familiar with PEFT fine-tuning, RAG pipelines, and LLMSecOps practices.
Systems & Infrastructure Backend and tooling development in Go and Rust. MLOps with containers, CI/CD, DVC, and MLflow. Cloud experience with AWS ML, Azure Log Analytics, and BigQuery.

Education

PhD in Computing Science

University of Glasgow, United Kingdom
2023 – 2026 (expected)

Supervisors:

Prof Jeremy Singer
Dr Christos Anagnostopoulos

External Supervisors:

Dr Yutian Tang (University of Glasgow)
Prof Ashkan Sami (Edinburgh Napier University)
Dr Marc Juarez Miro (The University of Edinburgh)

External Collabrators:

Wenbo Guo (Nanyang Technological University)
Run Hao (Aarhus University)
Bo Shao (CISPA)
Chongyang Xu (MPI SWS)
JieWen Luo (Royal Holloway, University of London)

Research focus includes software and AI supply chain security, AI systems security, LLM safety, and temporal graph learning.

Visiting PhD Researcher

University of Edinburgh, United Kingdom
Feb 2026 – July 2026

Visiting research collaboration with Dr Marc Juarez, focusing on Agent/DNN based backdoor detection

Core Certificates

GitHub Advanced Security certification
AWS Certified Machine Learning – Specialty
CREST Practitioner Security Analyst (CPSA): Credential ID 266639836
CompTIA Security+ ce Certification

Personal Interests

Strategy games (Go, Chinese Chess)
Martial arts and disciplined physical training
Endurance sports and racket sports