معرفی
Paul Squires is a Clinical Professor of Psychology at New York University's College of Arts & Science, Department of Psychology. He holds adjunct roles at NYU Tandon School of Engineering and has taught at multiple institutions including Stevens Institute of Technology and Fairleigh Dickinson University. His work focuses on applying machine learning and natural language processing to industrial-organizational psychology, particularly in analyzing knowledge worker career paths and job taxonomies. He has extensive consulting experience with firms like AT&T, KPMG, and the U.S. Department of Defense.
Education:
- PhD in Educational Psychology & Measurement, Fordham University
- MS in School Psychology, Pace University
- BA in Psychology, Manhattan College
Research Interests: Combines AI-driven systems with traditional HR practices, emphasizing validation of assessments, psychometric methodologies, and ML applications in workforce analytics. Recent work explores replacing conventional job classifications with AI systems using NLP and text mining techniques.
Teaching: Instructs graduate courses in research methods, applied statistics (using SPSS), and machine learning tools (R/Python). Core courses include job analysis, psychometrics, and performance appraisal systems.
Professional Contributions: Published over 30 papers on topics ranging from RFID technology in HR to leadership development. Served as a member of the Society of Industrial and Organizational Psychology (SIOP). Active in presenting at conferences like IEEE Big Data and NYU Tandon's Human Capital Innovations.
Labs/Teams: Collaborates with NYU Tandon researchers on projects involving big data analytics and people analytics initiatives.
