Dr. Nghiem is a highly-skilled engineer and an academic passionate about research and education, with extensive experience in engineering, research, education, and management/leadership.As an engineer, Dr. Nghiem has 10+ years experience in control theory and engineering, electrical engineering, optimization theory and implementation, scientific computing and programming, machine learning, and the integration of these disciplines for developing high-performance, intelligent data-driven autonomous systems. He has advanced programming skills, especially in scientific applications, in multiple languages and tools, including Matlab/Simulink, C/C++, Python, and Julia, in addition to solid general experience and background in software and programming and exceptional fast-learning ability. His skills and experience enable him to tackle any challenging problems in classical and modern controls, cyber-physical systems, and data-driven science and engineering. Being a professor founding and managing a research lab for several years, he has honed his management, interpersonal, leadership, teamwork, and communication skills.As an academic, his research advances the learning and control foundation and applications of intelligent cyber physical systems (iCPS) by bringing together control, optimization, machine learning / AI, and computing. He focuses on the creation of methods, algorithms, and engineering solutions for autonomous learning and real-time operation of iCPS. His work spans multiple application domains, including AI-enabled smart energy systems (such as smart buildings and connected communities), smart environment sensing and monitoring, robots, autonomous vehicles, real-time control systems, and verification of control systems. His current research interests include physics-informed machine learning, active learning of dynamic systems, simultaneous active learning and control, learning-integrated optimization, and safe learning-based control / MPC. Besides research, he has taught and developed courses in electrical engineering and computer science (e.g., classical and modern controls, engineering programming, autonomous vehicles, model-based embedded systems) at the University of Pennsylvania, Northern Arizona University, and University of Central Florida.