埃尼Mustafaraj是一种数据科学家研究基于网络的社会技术系统。她实现了新的方法来收集用户生成的数字痕迹而与这些系统交互和发明新技术从这些痕迹获取有意义的见解。这样的见解,可以用来改善现有系统或者构建新的更好的满足用户的需求。她目前的研究项目是关于理解标准用户适用于评估网络来源的可信度。目标是设计机器学习算法来提取信号可信度从各种网络平台,使用它们来推进网络文化建设平台,可以很容易地访问和理解这些可信度的信号。2008 - 2014年期间,她与教授塔迈塔克瑟白兰地,萨曼莎·芬恩的12和大量的韦尔斯利的学生研究谣言或其他类型的信息传播在像Twitter这样的社交网络。他们的研究导致TwitterTrails的创建,一个在线工具,记者和其他人感兴趣或真或假的起源和传播信息。自2013年以来,她也一直在研究社会技术系统,使大规模的在线学习。在其中一个项目中,她一直与富兰克林Turbak教授合作,Maja思文凯的18岁,和李伊莎贝尔21理解人们如何学会在麻省理工学院应用程序发明家在线平台,拥有数以百万计的用户。他们使用数据分析、可视化和机器学习模型学习者和他们的学习。 Prof. Mustafaraj loves the Python programming language and teaches CS111 Computer Programming and Problem Solving, one of the most fun and challenging intro courses at Wellesley. She teaches two data science related courses: CS 234 Data, Analytics, and Visualization and CS 315 Data and Text Mining on the Web, in which her students work on real-world projects closely related to her research and learn how to use data science to make a social impact. Finally, she also teaches CS 232 Artificial Intelligence, the field that drew her to study computer science. She aspires to get more women of all backgrounds involved in computer science and more broadly in STEM fields, so that they can shape a more just and equal technological future for our societies, a recurrent theme in all her teaching. Visit her website for more information on her research, teaching, and other interests.
