Meet the new faculty members joining MIT Sloan in 2026
Debiased machine learning, the currency of invoicing, and training good models with bad data: Meet the new experts bringing their knowledge and skill sets to the MIT Sloan School of Management.
Faculty
Zana Buçinca is an Assistant Professor at the MIT Sloan School of Management (in the Work and Organizations Studies Group) and the Department of Electrical Engineering and Computer Science.
Before joining MIT, she was a postdoctoral scholar with Microsoft's Office of Applied Research. She holds a PhD in computer science from Harvard, where her research on human-AI interaction and worker-centric AI drew on cognitive and social science theories to design novel interaction techniques that complement workers and amplify their values in AI-assisted tasks.
Her work has been recognized with the IBM PhD Fellowship, a Siebel Scholarship, and Best Paper Awards at top human-computer interaction conferences. She has also been named a Rising Star in AI by the University of Michigan, a Rising Star in Management Science & Engineering by Stanford, and one of the Top 10 Most Inspiring Women in STEM by UNDP Kosovo.
Buçinca, Zana, Siddharth Swaroop, Amanda E. Paluch, Susan A. Murphy, and Krzysztof Z. Gajos. ACM Transactions on Computer-Human Interaction. Forthcoming.
Zana Buçinca, Siddharth Swaroop, Amanda E. Paluch, Finale Doshi-Velez, and Krzysztof Z. Gajos. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, Yokohama, Japan: April 2025.
Siddharth Swaroop, Zana Buçinca, Krzysztof Z. Gajos, and Finale Doshi-Velez. In Proceedings of the 30th International Conference on Intelligent User Interfaces, Cagliari, Italy: March 2025.
Zana Buçinca. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, Honolulu, HI: May 2024.
Siddharth Swaroop, Zana Buçinca, Krzysztof Z. Gajos, and Finale Doshi-Velez. In Proceedings of the 29th International Conference on Intelligent User Interfaces, Greenville, SC: April 2024.
Buçinca, Zana, Yücel Yemez, Engin Erzin, and Metin Sezgin. IEEE Transactions on Affective Computing Vol. 14, No. 1 (2023): 823-835.
Debiased machine learning, the currency of invoicing, and training good models with bad data: Meet the new experts bringing their knowledge and skill sets to the MIT Sloan School of Management.