Agentic AI Expert -Healthcare, Robotics, MS, Ph.D.

Specialties & Experience of this Expert Witness

Additional Information

Specialties & Experience of this Expert Witness General Specialties: Artificial Intelligence and Software Engineering Keywords/Search Terms: Agentic AI, Autonomous AI Agents, Multi-Agent Systems, AI Agents, Agentic Workflows, LLM Agents, Autonomous Decision-Making, AI Orchestration, Tool-Using AI, Agentic AI Safety, AI Agent Liability, Agentic AI Governance, Human-in-the-Loop Systems, AI Agent Accountability, Autonomous System Failures, AI Ethics, AI Bias, AI Risk, Chatbot, AI Liability, Product Liability, Software Defect, Patent Litigation, Trade Secret Misappropriation, Data Privacy, Algorithmic Bias, AI Regulation, Autonomous Vehicle Safety, Cybersecurity, Generative AI, ChatGPT, Deepfake Detection, NIST AI Risk Management Framework, EU AI Act, Daubert, Standard of Care, Robotics Safety Education: Ph.D. in Artificial Intelligence and Robotics, University of California, Davis; M.S. in Artificial Intelligence and Controls Engineering, San Jose State University Years in Practice: 10 Dr. Alireza Mounesisohi holds a Ph.D. in Artificial Intelligence and Robotics from the University of California, Davis, and a Master of Science in Artificial Intelligence and Controls Engineering from San Jose State University. He currently serves as Lead AI Agentic Engineer at ImmunityBio, Inc., where he is responsible for the design, implementation, and technical oversight of autonomous AI agent systems and automated data pipelines used in regulated healthcare and biotechnology settings. Dr. Mounesisohi has over ten years of professional experience in software engineering, machine learning, robotics, and distributed computing systems, having held engineering positions at Dock Health, Union.ai, Domino Data Lab, and on NASA-funded robotics research programs, where he developed robotic vision and autonomous navigation systems for space exploration applications. His professional work has included the development and evaluation of autonomous decision-support systems utilizing large language model agents, robotic agentic autonomy and control systems, machine learning pipelines for biotechnology and clinical research organizations, distributed computing systems for pharmaceutical manufacturers, and computer vision systems for aerospace robotics. His areas of technical competence include agentic artificial intelligence architecture, multi-agent system design, robotic agentic autonomy, autonomous decision-making processes, reinforcement learning, robotics and controls engineering, machine learning methodology, deep learning, natural language processing, computer vision, predictive analytics, and explainable AI. He is additionally experienced in cloud computing infrastructure, distributed systems, microservices architecture, MLOps, data engineering, and software development practices applicable to regulated industries, including compliance with data-security and privacy requirements such as HIPAA. Additional areas of expertise include large language model orchestration, retrieval-augmented generation, autonomous agent pipelines, tool-calling and tool-using AI agents, AI governance and risk management frameworks, algorithmic bias evaluation, AI model validation and testing, clinical decision-support systems, healthcare informatics, biotech data science, API design (FastAPI, Flask, Spring Boot), and container orchestration technologies including Kubernetes. He holds professional certifications from The Linux Foundation in Kubernetes, container orchestration, and DevOps/site-reliability engineering practices. Dr. Mounesisohi is available to provide expert analysis, opinion, and testimony on matters involving artificial intelligence systems, agentic and autonomous software architectures, robotic autonomy and control systems, machine learning system design and evaluation, AI safety and governance, and related software engineering issues arising in litigation, arbitration, or regulatory proceedings.