Zakia Hammal
Robotics Institute / Biomedical Engineering / Machine Learning Department
Carnegie Mellon University
About Professor Zakia Hammal
Carnegie Mellon University stands as a global leader in technological innovation and interdisciplinary research, making it an exceptional environment for groundbreaking academic pursuits. Professor Zakia Hammal holds a unique tri-departmental appointment across the renowned Robotics Institute, the dynamic Biomedical Engineering Department, and the pioneering Machine Learning Department. These departments are celebrated for their world-class faculty, state-of-the-art facilities, and a collaborative ecosystem that pushes the boundaries of artificial intelligence, human-centered robotics, and advanced healthcare technologies. This distinguished academic setting provides an unparalleled foundation for exploring complex challenges at the intersection of computing and human well-being, attracting top talent globally.
🧬Research Focus
Professor Hammal’s impactful research centers on advanced multimodal human behavior modeling, affective computing, and applying sophisticated machine learning techniques to critical health informatics problems. Her work involves developing innovative computational methods to analyze nonverbal communication, including facial expressions, vocal cues, and body movement dynamics, offering deeper insights into social interaction and psychological states. This research has significant real-world applications, particularly in automated assessment within clinical and therapeutic contexts. Her team's contributions are instrumental in areas like evaluating depression severity, measuring pain intensity, assessing expressiveness in children with facial abnormalities, and analyzing intricate mother-infant interactions relevant to conditions like autism spectrum disorder.
🎓Student Fit & Career
Graduate students seeking to contribute to cutting-edge research at the nexus of technology and human health will find an ideal mentor in Professor Hammal. Her lab welcomes highly motivated PhD students with strong backgrounds in machine learning, computer vision, signal processing, or behavioral science, eager to engage in interdisciplinary problem-solving. Students will gain invaluable experience in developing novel algorithms and deploying solutions with direct societal impact. Under her expert academic mentorship, graduates are well-prepared for diverse career paths, including advanced research roles in academia, leading R&D positions in AI and robotics within industry, or specialized roles in healthcare technology innovation and data science.
Research Areas
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