The UNC School of Information and Library Science (SILS) has hired three new tenure-track faculty members, with appointments beginning July 1. Sayamindu Dasgupta, Marijel “Maggie” Melo, and Yue Wang bring expertise in engaging children with data science, creating inclusive makerspaces, and mining insights from health data, respectively. They will join the SILS faculty as assistant professors, and begin teaching courses for the school this fall.
“We are thrilled to welcome these three dynamic new professors to SILS,” said SILS Dean Gary Marchionini. “They will further strengthen SILS’ research excellence in health informatics, data science, and modern librarianship.”
Sayamindu Dasgupta is a Moore/Sloan & WRF Innovation in Data Science Postdoctoral Fellow at the University of Washington. In his research, he designs and studies the uses of programming toolkits that enable children to engage in data science. Additionally, he uses data scientific methods to understand how children learn in large-scale informal online communities. His work has received recognition and awards in the ACM CHI, ACM CSCW, ACM IDC, and IEEE VL/HCC conferences, and in 2014, he was named in Forbes magazine’s 30 under 30 list for education. He received his doctorate from MIT, where he was a key member of the team behind the Scratch programming language and online community.
Maggie Melo recently completed her PhD at the University of Arizona, where she was an American Association of University Women Fellow. Her work has appeared or is forthcoming in portal: Libraries and the Academy, Hybrid Pedagogy, and Computers and Composition Online. She co-founded the University of Arizona’s first publicly accessible and interdisciplinary makerspace – iSpace – and strategically facilitated its growth from a 400-square-foot room in the Science-Engineering Library to a 5,000-square-foot facility soon to be housed in the University’s Main Library. She also founded the Women Techmakers Tucson Hackathon, the Southwest’s first women’s-only hackathon. She has given keynote addresses and invited-talks at regional and national conferences, including the Google Developer Group’s North American Summit.
Yue Wang is a PhD candidate in the Department of Electrical Engineering and Computer Science at the University of Michigan. He is interested in text data mining and machine learning with applications in health informatics. His thesis focuses on developing principled interactive machine learning approaches that reduce human analysts' information processing workload. His work is motivated by and applied to various data mining problems, including high-recall information retrieval, clinical natural language processing, and qualitative content analysis. He publishes in both computer science and health informatics venues, including KDD, SIGIR, WSDM, and JAMIA. He and his collaborators won first place in the TREC 2013 Microblog Track, and he received the Best Paper Award and Outstanding Reviewer Award in WSDM 2016.
