Faramarz Phorozan is a Higher Degree by Research (HDR) student in the School of Computer Science at the University of Technology Sydney (UTS). A passionate technologist and software engineering leader, Faramarz brings over two decades of hands-on industry experience to his academic research, striving to bridge the gap between rigorous academic theory and production-ready industry solutions.

At UTS, Faramarz’s doctoral research focuses on Multi-Tenant AI Model Isolation in Microservice Architectures. Specifically, he is developing a novel, compliance-aware ML-Ops framework tailored for the FinTech sector. As financial institutions increasingly rely on shared cloud infrastructure to deploy AI, traditional data isolation methods are no longer sufficient to protect against emerging threats such as model extraction and cross-tenant data leakage. Faramarz’s research addresses this critical gap by designing a Hybrid Global-Tenant Model Architecture (HGTMA) that uses intelligent orchestration to dynamically balance security, performance, cost, and strict Australian regulatory compliance (such as APRA CPS 234 and ASAE 3402).

Beyond his academic pursuits, Faramarz is an established industry veteran. Currently serving as a Lead Solutions Architect, he has an extensive career spanning senior leadership and architectural roles—including Head of Engineering and Principal Developer—across the Australian financial technology and software consulting sectors. He has a proven track record of designing scalable distributed systems, stabilizing complex process engines, and leading high-performing engineering teams with technologies such as Python, .NET, and relational databases.

Driven by a lifelong passion for software development that began with painstakingly coding QBasic programs on a DX2 486 PC, Faramarz operates on the core belief that "the learning never stops." Through his mixed-methods, industry-integrated PhD, he aims to establish new industry standards that will enable the safer, more compliant, and highly efficient adoption of AI in financial services.