Rate My Professor Vladimir Shapiro

Vladimir Shapiro is an Assistant Teaching Professor in the College of Professional Studies at Northeastern University, where he also serves as the Analytics Program Lead for the Bachelor of Science in Analytics program. He earned his PhD from the Technical University of Sofia in Bulgaria. His academic interests encompass data science, machine learning, computer vision, and artificial intelligence, with applications in areas such as industrial inspections, student performance assessment, and public health modeling. Shapiro's research has contributed to advancements in AI-powered non-destructive testing, object detection and annotation, temporal thermography, and pattern recognition techniques including Hough and Radon transforms.

Shapiro has authored or co-authored 28 publications, accumulating over 700 citations as per Google Scholar metrics. Key works include the patent 'Generation of object annotations on 2D images' (2022), 'A System to Inspect Corrosion Under Insulation via Temporal Thermography & Artificial Intelligence' (conference paper, 2022), 'COVID-19 Sex-Age Mortality Modeling - A Use Case of Risk-Based Vaccine Prioritization' (2021), 'COVID-19 Outbreaks and Age Mortality Patterns' (2020), 'Modelling COVID-19 age-sex mortality metrics' which received a Best Poster Award (2020), 'Particle tracking through elastic matching' (2017), 'Towards a Multinational Car License Plate Recognition System' (2006), and 'Accuracy of the straight line Hough Transform: The non-voting approach' (2006). More recently, he presented 'An AI-Inspired Approach to Student Performance Assessment' at The Paris Conference on Education 2025. Additionally, he holds a patent for 'Operatorless particle processing systems and methods' (WO2014152039 A2, 2014). His work demonstrates impact in bridging academic research with practical applications in AI and data analytics, influencing fields from industrial process optimization to educational evaluation methodologies.