Nick Machairas

Nick Machairas, Ph.D.

Founder and Principal

Geotechnics (strong focus on deep foundations), Predictive Analytics, Modern Database Systems, Higher Education

Nick Machairas is an Advanced Geotechnical Analytics expert and the founder of Groundwork AI, leading the company's consulting, product development and educational efforts. Eager to remain at the forefront of the digital transformation of the Geoprofession, Nick applies advanced analytics to tough geotechnical engineering problems while working on next-gen processes for handling geotechnical data enabling AI-driven monitoring, design, construction and risk assessment. He has been invited to train, write and present on the subject at conferences and the private industry.

Nick is also a lecturer at NYU and Columbia University teaching graduate and undergraduate courses in computing, machine learning, modern databases and engineering ethics.

Nick earned his Doctoral degree from NYU, Master of Science from Columbia University and Bachelor of Science in Civil Engineering from NYU.

Notable Publications

(see CV for full list)

  • Machairas, N., and Iskander, M. (2020). "Advanced Data Analytics in Geotechnics." Geostrata, American Society of Civil Engineers, 24(4), 32–39. (link to)
  • Machairas, N., Li, L., and Iskander, M. (2020). "Application of Dynamic Image Analysis to Sand Particle Classification Using Deep Learning." Geotechnical Special Publication 317, American Society of Civil Engineers, 612–621. (link to)
  • Bachus, R., Machairas, N., and Cadden, A. (2019). "DIGGS Does Deep Foundations." Proceedings of the 44th Annual Conference on Deep Foundations, Deep Foundation Institute, Hawthorne, New Jersey, 814–827.
  • Machairas, N., and Iskander, M. G. (2018). "An Investigation of Pile Design Utilizing Advanced Data Analytics.” Geotechnical Special Publication 294, American Society of Civil Engineers (ASCE), 132–141. (link to)
  • Machairas, N., Highley, G. A., and Iskander, M. G. (2018). "Evaluation of the FHWA Pile Design Method Against the FHWA Deep Foundation Load Test Database Version 2.0." Transportation Research Record, 2672(52):268-277, SAGE Publications (link to)