Joseph C Sremack, CISA, CFE, CIPP/US Expert Witness
Curriculum Vitae

Forensic AI, Software & Data Analysis

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Specialties & Experience of this Expert Witness

General Specialties:

Artificial Intelligence and Software Engineering

Keywords/Search Terms:

data analysis, data science, source code analysis, patent infringement, natural language processing, class action certification, GIS and geospatial data, artificial intelligence, systems controls, data privacy, model analysis, LLM, Python, Java, neural networks, trade secrets, deepfake detection, computer vision, machine learning, SQL

Education:

Master of Science, Computer Science, North Carolina State University; Bachelor of Arts, Computer Science and Philosophy, The College of Wooster

Years in Practice:

20+

Additional Information

Joe Sremack is a forensic technology expert with more than two decades of experience in complex data, software, and artificial intelligence analysis for high-stakes legal matters. As Practice Leader of CBIZ's Forensic Data Analytics and Technology division, he has served as consultant and testifying expert in over 500 engagements across state and federal courts, international arbitrations, and regulatory proceedings in numerous countries. Mr. Sremack is the author of AI Forensics: Investigation and Analysis of Artificial Intelligence Systems (Chapman & Hall, March 2026) and Big Data Forensics (Packt Publishing, 2015). He is a frequent speaker on AI forensics, source code analysis, and data analytics at legal and industry conferences. His technical expertise spans artificial intelligence system examination (including large language models, generative AI, and machine learning pipelines), deepfake and synthetic media authentication, proprietary source code analysis, advanced data analytics, and IT infrastructure assessment. He develops custom analytical tools and methodologies for forensic examination of data and software systems. He provides expert analysis in matters involving: * AI intellectual property disputes: model theft, training data misappropriation, AI-generated content ownership * Algorithmic bias and discrimination: hiring algorithms, lending models, insurance underwriting AI * Deepfake and synthetic media: evidence authentication, AI-generated content detection * Source code and software analysis: trade secret misappropriation, open source license compliance, patent infringement * Data privacy and regulatory compliance: online tracking, PII/PHI disclosure, AI governance and EU AI Act readiness * Enterprise system forensics: data collection, timestamp authentication, system controls validation * Class action certification and electronic discovery involving complex data systems and AI technologies His cross-industry experience includes engagements for Fortune 500 corporations, government agencies, and international entities in matters involving substantial financial exposure and complex regulatory compliance.