Jordan Suchow

Jordan Suchow is an Assistant Professor in the School of Business at Stevens Institute of Technology, specializing in cognitive science, artificial intelligence, and behavioral experiments. He holds a PhD in Psychology from Harvard University (2014) and a postdoctoral fellowship in computational cognitive science at UC Berkeley. His research focuses on visual perception, memory, cultural evolution, and the design of digital platforms. He is known for pioneering work on 'motion silencing' and developing tools like Dallinger for crowdsourced experiments.

Suchow's research spans computational models of human cognition, including studies on visual working memory, face perception, and cultural transmission. He has led projects funded by DARPA and the NSF, totaling over $3.8 million. His work has been featured in Nature, Proceedings of the National Academy of Sciences, and Trends in Cognitive Sciences.

He has received awards including the Neural Correlate Society's Best Visual Illusion of the Year (2011) and a U.S. patent for data-driven face-trait encoding (2022). His software contributions include Dallinger, MemToolbox, and nbgrader. Suchow advises on digital platforms, cultural consensus theory, and ethical AI governance.