Farhad Shakerin is a Principal Software Engineer with a rare blend of research rigor and production experience, currently at Microsoft after rising through senior engineering and data science roles. He holds advanced graduate training from The University of Texas at Dallas where his PhD/postdoc work produced the open-source SHAP_FOLD system and won an NSF grant for explainable, logic-based ML. His research marries inductive logic programming, SHAP explanations, and high-utility itemset mining to produce non-monotonic logic programs that capture global model behavior—bringing symbolic reasoning to contemporary ML. Before academia he spent eight years building safety-critical C++ systems for Tehran metro signaling that still operate at scale, evidencing a track record of dependable engineering. He is passionate about non-neural NLU, commonsense reasoning with ASP and knowledge graphs, and translating formal methods into practical software. Colleagues know him for bridging traditional AI and modern ML in ways that make models both powerful and auditable.
9 years of coding experience
17 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at The University of Texas at Dallas
Bachelor of Science (BSc) Computer Software Engineering, Bachelor of Science (BSc) Computer Software Engineering at Iran University of Science and Technology
The source for REST API specifications for Microsoft Azure.
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