Deahan Yu
(he/him)
Assistant Teaching Professor
Education
- PhD in Information Science, University of Michigan
- MS in Health Informatics, University of Michigan
- BS in Statistics, Carnegie Mellon University
Biography
Deahan Yu is an assistant teaching professor at the Khoury College of Computer Sciences at Northeastern University, based in Boston.
Yu teaches courses in machine learning and data mining. Given the myriad applications of machine learning across diverse fields such as health care, finance, and business, he wants his students to understand not only the theoretical foundations of machine learning algorithms, but also the algorithms’ broader impact and ethical considerations.
Yu chose to teach at Khoury College because its vision aligns with his aspiration to empower students as leaders, and he sees the Northeastern environment as welcoming, supportive, and respectful. He is thrilled to mentor, advise, and lead students during their learning journeys.
Outside of teaching, he enjoys running, rock climbing, golf, coffee, and ice cream.
Recent publications
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Data Science and Natural Language Processing to Extract Information in Clinical Domain
Citation: V. G. Vinod Vydiswaran, Xinyan Zhao, Deahan Yu. (2022). Data Science and Natural Language Processing to Extract Information in Clinical Domain COMAD/CODS, 352-353. https://doi.org/10.1145/3493700.3493773 -
Data Science and Natural Language Processing to Extract Information from Clinical Narratives
Citation: V. G. Vinod Vydiswaran, Xinyan Zhao, Deahan Yu. (2021). Data Science and Natural Language Processing to Extract Information from Clinical Narratives COMAD/CODS, 441-442. https://doi.org/10.1145/3430984.3431967 -
Identifying Medication Abuse and Adverse Effects from Tweets: University of Michigan at #SMM4H 2020
Citation: V. G. Vinod Vydiswaran, Deahan Yu, Xinyan Zhao, Ermioni Carr, Jonathan Martindale, Jingcheng Xiao, Noha Ghannam, Matteo Althoen, Alexis Castellanos, Neel Patel, Daniel Vasquez. (2020). Identifying Medication Abuse and Adverse Effects from Tweets: University of Michigan at #SMM4H 2020 SMM4H@COLING, 90-94. https://aclanthology.org/2020.smm4h-1.13 -
Uncovering the relationship between food-related discussion on Twitter and neighborhood characteristics
Citation: V. G. Vinod Vydiswaran, Daniel M. Romero, Xinyan Zhao, Deahan Yu, Iris N. Gomez-Lopez, Jin Xiu Lu, Bradley E. Iott, Ana Baylin, Erica C. Jansen, Philippa Clarke, Veronica J. Berrocal, Robert Goodspeed, Tiffany C. Veinot. (2020). Uncovering the relationship between food-related discussion on Twitter and neighborhood characteristics J. Am. Medical Informatics Assoc., 27, 254-264. https://doi.org/10.1093/jamia/ocz181
