Rate My Professor Tuka Alhanai

Tuka Waddah Alhanai is an engineer, scientist, and researcher at the forefront of computer-human intelligence as an Assistant Professor of Computer Engineering at New York University Abu Dhabi. She leads the Laboratory for Computer-Human Intelligence (CHI-lab), developing computational systems that quantify subjective elements of the human experience, including characteristics that form successful teams, elements leading to marketplace hits, and crowd assessments of competence from profile images. Her work employs machine learning, human-computer interaction, game theory, recommendation systems, and crowdsourcing to augment human decision-making—from physical activity choices to team formation—and interpret thoughts via signals like prosody, language, and movement, ultimately aiming to enhance human health and wellbeing. Alhanai holds a PhD in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology (2019) and a B.S. from the Petroleum Institute (2011).

In her academic career, Alhanai serves as Associated Faculty in the Computer Science and Engineering Department at NYU Tandon and contributes to designing MS and PhD programs at NYU Abu Dhabi while fostering partnerships with regional sponsors for student training and research. Previously, she founded Ghamut Corporation, recipient of the MIT Legatum Award (2016), MassChallenge winner (2017), and NSF SBIR grantee (2019). Her accolades include the MIT Technology Review's 10 Innovators Under 35 MENA Award (2018) and the UAE Government Excellence Award (2019). In February 2026, she was appointed to the United Nations Independent International Scientific Panel on AI. Alhanai publishes in premier venues such as AAAI, ACL, and IEEE, with notable works including "Predicting Latent Narrative Mood using Audio and Physiologic Signals" (AAAI, 2017), "Spoken Language Biomarkers for Detecting Cognitive Impairment" (ASRU, 2017), "Development of the MIT ASR System for the 2016 Arabic Multi-genre Broadcast Challenge" (SLT, 2016), and co-authorship on "Perception, performance, and detectability of ChatGPT-generated text in scientific publications" (Scientific Reports, 2023). Her research has garnered media attention from The Wall Street Journal, Wired, BBC, and TechCrunch, influencing fields like mental health engineering and AI ethics in academia.