Mohammad Haghighat is an engineering leader with over a decade of experience in artificial intelligence and computer vision. He has worked on a variety of projects in academia and industry using conventional computer vision machine learning algorithms as well as deep neural networks. These include AI-based features for smart appliances and video analytics for surveillance systems. Mohammad has developed solutions for anomaly detection and prediction, image embedding and classification, object detection and tracking, face recognition, gender and age recognition from face and body images, privacy-preserving cloud-based biometric identification and multimodal biometrics. He earned his PhD in ECE from the University of Miami, and has published numerous papers in international conferences.