Nick is a geoprofessional, lecturer, and entrepreneur with deep expertise in predictive analytics, modern data management, and software engineering. He is passionate about empowering his clients and colleagues by seamlessly integrating explainable artificial intelligence with proven engineering workflows. Through the responsible use of high-quality data and cutting-edge technologies, Nick is developing tailored predictive products that precisely fit project requirements and provide powerful insights and recommendations. The end result: innovative data-driven environmental and geotechnical engineering solutions that are more reliable, efficient, and cost-effective than traditional approaches.
Nick’s early research and consulting efforts focused on applying machine learning to deep foundations, bridging the gap between calculated and measured capacities, and have since evolved to intelligent assistants that enable synergistic human-machine engineering design workflows. He is a lecturer at New York University (NYU) and Columbia University teaching undergraduate and graduate courses in Computer Programming, Machine Learning, Modern Database Management Systems, and Engineering Leadership and Ethics, satisfying a long-held aspiration to teach and mentor.
Nick speaks frequently at industry conferences and is an active member in several standing committees, including the American Society of Civil Engineers and Geo-Institute’s Data Interchange for Geotechnical and Geoenvironmental Specialists (DIGGS), Deep Foundations, and Innovation committees, as well as the Transportation Research Board (TRB), Geotechnical Instrumentation (AKG60), and Bridge Foundation (AKG70) committees.
“Relentless innovation is a core Haley & Aldrich principle – it’s also one of my strongest motivators and what I believe is a fundamental prerequisite to delivering exceptional client experiences. By deeply embedding advanced analytics and cutting-edge technology in everything we do, we strive to deliver unmatched transformative client experiences as well.”
