Mona Far
PhD Candidate Knowledge-Graph Reasoning
Melbourne, Victoria, Australia
Summary
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Senior🎓
Top SchoolMona Far is a data-driven applied scientist and PhD candidate at Monash University specializing in knowledge-graph and neuro-symbolic reasoning, with 12 years of industry and research experience across ML, NLP, and applied AI. She blends academic rigor—an MPhil/MSc from ANU focused on patent prior-art search—with production experience as a data scientist at Accenture and engineering roles building real-time safety systems. Her current research aims to make generative models safer and more trustworthy in high-stakes decisions by teaching them to reason carefully and refuse harmful outputs. She also teaches algorithms and Python to postgraduate students, reflecting a commitment to translating complex ideas into practical skills. Colleagues describe her work as empathetic and safety-centered, combining deep technical breadth with a human-first perspective on AI deployment.
12 years of coding experience
10 years of employment as a software developer
Australian National UniversityB.S, Electrical and Electronics Engineering, B.S, Electrical and Electronics Engineering at Shahid Beheshti University
English, PersianProgramming languages (1)
Github contributions (1)
rbouadjenek/patent-search
Jun 2014 - Jul 2015
Automatically exported from code.google.com/p/patent-search
Contributions:345 commits, 5 pushes in 1 year 1 month
patent-searchpatentsearch
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