My current research projects explore the early introduction of computers to two different domains - instruction and text translation. In both, I am interested in how researchers had to reconceptualize human cognition and language to make those accessible to computers. My research examines those transformations and their epistemological, social, and political consequences.
I received my Ph. D. in 2020 from the Department of History and Sociology of Science at the University of Pennsylvania. In 2020-2022, I was the Hixon-Riggs Postdoctoral Fellow in Science and Technology Studies at Harvey Mudd College in Claremont, CA. Currently, I am an assistant professor at the Department of History at Purdue University in West Lafayette, IN.
I held dissertation fellowships at the Charles Babbage Institute and the Consortium for the History of Science, Technology, and Medicine. My research was also supported by the Linda Hall Library and the Association for Computer Machinery History Committee. In different years, I was also selected as a recipient of dissertation fellowships offered by the IEEE History Center and National Academy of Education.
Peer-reviewed articles and essays
“‘Overtake and Surpass:’ Soviet Algorithmic Thinking as a Reinvention of Western Theories,” in Cold War Social and Behavioral Sciences: International and Transnational Entanglements, edited by Mark Solovey and Christian Daye. Palgrave Macmillan, 2021.
“Engineering the Lay Mind: Lev Landa’s Algo-Heuristic Theory and Artificial Intelligence,” in Abstractions and Embodiments: New Histories of Computing and Society, edited by Janet Abbate and Stephanie Dick. Johns Hopkins University Press.
“Rules of Creative Thinking: Algorithms, Heuristics, and Soviet Cybernetic Psychology," BJHS Themes, Volume 8: Histories of Artificial Intelligence: A Geneology of Power, 2023, pp 81-95.
Below you can find brief descriptions of my current research projects
Cyberdreams of the Information Age:
Learning with Machines in the Cold War United States and the Soviet Union
My book manuscript examines how in the 1950s-1970s, two opposed countries - the United States and the Soviet Union - came to have converging views on what constitutes good thinking and a good mind in the era of computerization. In particular, US and Soviet scholars argued that the computer age required minds whose thinking followed strict rules of mathematical logic. This kind of mental capital, they believed was essential to the computerization of industrial production, seen as an urgent economic task in both countries. Computers came to be seen as ideally suited to think logically and efficiently. This belief prompted both countries to build special teaching computers that were supposed to replace human instructors.
However, to build technology that would streamline human cognition, researchers first needed to make human thinking accessible to the machine - that is, to model human thinking computationally. In this process, they made significant contributions to artificial intelligence research.
Tracing multiple and previously ignored exchanges in computing and
psychology across the Iron Curtain, the manuscript examines the co-production of cognitive theories, the shared normative beliefs about good minds at the heart of those theories, and he ways those theories found a way into pedagogical computing and artificial intelligence systems in both countries.
My interviews to media, appearances on podcasts, and personally written blogposts:
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