I’m an incoming Assistant Instructional Professor at the University of Chicago. Currently, I am developing teaching materials for the masters program in computational social science where I will be teaching courses in collective intelligence, large-scale online experiments, and computational analysis and research methods. My research interests fall at the intersection of technology and social behavior where I investigate collective intelligence problems in crowd-based systems. In my work, I use theory-driven investigations that rely on mining Big Data about human interactions and behavior, online experiments and surveys, crowdsourcing, natural language processing, and machine learning and statistical modeling frameworks. Supported by these novel combination of approaches, my research advances theories of collective intelligence and complex systems and makes methodological contributions toward human-centered AI and crowd-aware system design. The core contributions of my work are relevant to computational social science, network science, social computing, and increasingly for machine intelligence and human-machine communication. My contributions in these areas are demonstrated by presentations in prime venues such as the International Conference on Computational Social Science (IC2S2), the Network Science Society (NetSci), the International Communication Association (ICA), and several well-received publications at the Association for Computing Machinery (ACM), the Institute of Electrical and Electronics Engineers (IEEE), and the Association for the Advancement of Artificial Intelligence (AAAI). Examples include conferences on Web Science (WebSci and WebConf – formerly WWW), Web and Social Media (ICWSM), Advances in Social Network Analysis and Mining (ASONAM), Computer-Supported Cooperative Work (CSCW), and Collective Intelligence (ACM:CI).