Edgar Hsieh
AI Networking Engineer
About
R&D Engineer with a Ph.D. background in Network Security and Satellite Communications. Experienced in designing high-availability systems, developing C++/Python simulation cores for LEO satellite networks, and applying Explainable AI (XAI) to threat detection. Proven track record of solving complex infrastructure challenges for research institutes (ITRI/TASA) and industry partners (HTC/Wiwynn).
Work Experience
Nantou, TW
April 2022 – Pres
Ph.D. Researcher (Network Security & AI)
Focusing on Explainable AI (XAI) for Network Intrusion Detection Systems (NIDS).
Highlights
- Developed XAI-Integrated Security Framework: Created a novel intrusion detection framework combining NetFlow analysis and SHAP (Shapley Additive Explanations) to improve model transparency and trust.
- Optimized Feature Selection: Utilized RFE and error-contribution analysis to identify critical NetFlow features (e.g., TCP port usage, connection duration), reducing model training time by 29.86% while improving F1 score by 10%.
- Published Advanced Research: Authored multiple high-impact papers on OS identification and anomaly detection using time-series clustering algorithms.
Assistant Engineer
Leading R&D projects in AI-driven thermal control, high-availability network design, O-RAN virtualization, and satellite network architecture simulation at ITRI.
Highlights
- AI-Driven Thermal Control Module Development: To address the power consumption and thermal challenges in an all-in-one immersion cooling system for O-RAN base stations, I led the development of an AI-powered thermal prediction module. By integrating sensor data via Zabbix and Modbus and utilizing an LSTM forecaster model, the power prediction model achieved 99% accuracy with only six months of data.
- High-Availability Network Patent Proposal: Proposed a multi-gateway seamless switching system patent to solve connection interruption issues for mobile devices switching between base stations, Wi-Fi, and satellite networks. The design combines VPN Tunnelling, SDN, and MPTCP principles to ensure zero service interruption for upper-layer applications during underlying route changes.
- O-RAN Virtualization Solution Technology Transfer: Solely managed a technology transfer project for HTC to build their O-RAN virtualization capabilities. I was singularly responsible for implementation, achieving all four KPI scenarios, authoring a 30+ page technical document, conducting two training sessions, and providing a year of consulting. This successfully concluded a two-year-stalled project and prevented potential legal disputes for the institute.
- Spearheaded LEO Satellite Constellation Design: Developed a high-fidelity simulation core (C++/Python) to solve TASA's multi-stage deployment optimization problem under strict budget constraints.
- Strategic Phased Deployment: Engineered a 'Zero Orbit Adjustment' strategy, enabling seamless transition between deployment phases without fuel-consuming maneuvers, significantly extending satellite operational lifespan.
Intern
Internship focused on developing high-availability mechanisms, carbon footprint frameworks, O-Cloud platforms, and AI-based thermal control models at ITRI.
Highlights
- High-Availability (HA) Mechanism Implementation: Designed and implemented an HA auto-recovery mechanism to meet Wiwynn's stringent system stability requirements for an O-RAN platform. By combining custom monitoring scripts with Kubernetes' three Probe mechanisms, the system was enabled to automatically restart during software failures or power interruptions, ensuring service continuity and preventing permanent outages.
- Proposed a carbon footprint calculation framework for data centers.
- Delivered an O-Cloud platform as the annual technology showcase.
- Developed an AI-based thermal control model for data center environments.
Protocol Engineering and Application Research Laboratory
Nantou, TW
September 2019 – March 2022
Research Assistant
Conducted research on network security and data synchronization, resulting in multiple published papers and funded proposals.
Highlights
- Secured Research Funding: Co-authored and successfully secured MOST grants for two major research initiatives focusing on SDN architecture optimization and Anomaly Detection using Machine Learning, directly contributing to the lab's core research roadmap.
- Published 2 conference papers (TANET, ICJMEF).
Dormitory Network Infrastructure Coordinator
Managed and maintained the network infrastructure for a university dormitory housing 400+ students, ensuring reliable connectivity and prompt issue resolution.
Highlights
- Major Network Outage Resolution: Led the response to a critical broadcast storm that disrupted network services for approximately 200 students across two dormitory floors. Using Wireshark for systematic, layer-by-layer troubleshooting, we identified and resolved the network loop caused by improper cabling within 2 hours and coordinated the decommissioning of legacy equipment to prevent future incidents.
Contact
Park Road
Linkou Dist., New Taipei 244013 TW
(886) 967028013
Education
-
2019 2025
National Chi-Nan University
Ph.D. (Defense Passed)
Ph.D. in Computer Science & Information Engineering
Courses- Graph Theory (Network Topology Optimization)
- Mobile & Wireless Networks
- Special Topics on Computer Networks
- Malware Analysis & Development with Python
- Named Data Networking (NDN)
- IPv6 & Network Programming
-
2015 2019
National Chi-Nan University
Bachelor
Computer Science and Information Engineering
Skills
Programming & Development
Expert
C/C++ (System/Simulation Core)
Python (Data Analysis, AI Models)
Shell Scripting
Git/CI/CD
Domain Knowledge
Advanced
LEO Satellite Networking
Network Security & Intrusion Detection
Explainable AI (XAI / SHAP)
O-RAN & 5G Architecture
Infrastructure & Tools
Advanced
Kubernetes (K8s) & Docker
High Availability (HA) Design
NetFlow Analysis
Linux Kernel Tuning
Publications
On the Selection of Statistical Feature Set of NetFlow Data for Operating System Identification
Netflow-based Operating System Identification Using Machine Learning
Network Anomaly Detection Based on NetFlow Time Series Data in aHealthcare Network Environment
APAMI
14 October 2022
基於 NetFlow 時間序列資料之網路異常行為偵測 (Network Anomaly Detection Based on NetFlow Time Series Data)
SimpleSync: A Better Solution of Synchronization on NDN
TANET
2018
A paper detailing the development and impact of the packet synchronization method on NDN.