Tamer's Ph.D. dissertation examines how the diffusion and evolution of technological innovations can be modeled as a process of collective search on technological graphs. He is also interested in how technological graphs could be modeled as a fitness landscape using methods such as Gaussian random fields, NK landscapes, and other tailored models. During his Ph.D. studies, Tamer was also involved in other research projects, including the modeling of technological lock-ins and lock-outs by introducing concepts like local information and switching costs, the study of growth in temporal networks, analysis of financial network data, and interactive visualizations with D3.js.
After completing his Ph.D., Tamer started working with a company to develop a cloud platform for data management and online teaching, where he works as a data scientist and developer. On the research level, Tamer will be working on two projects; one involves financial data science and another about organizational network mapping.