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Camelia Pop has a strong background in research and teaching mathematics. Their most recent position was as a Research Scientist at Edgestream Partners, L.P. starting in September 2018. Prior to that, they were a Tenure-track Assistant Professor at the University of Minnesota-Twin Cities from September 2015 to August 2018. In this role, they conducted research in probability and partial differential equations, with a focus on mathematical finance and population genetics. Camelia also taught courses such as Stochastic Processes, Probability, Point-set Topology, and Mathematical Finance. Before their time at the University of Minnesota, Camelia was a Hans Rademacher Instructor of Mathematics at the University of Pennsylvania from July 2012 to August 2015.

Camelia Pop has a strong background in mathematics. Camelia obtained their Bachelor's degree in Mathematics from Babeș-Bolyai University, where they studied from 2003 to 2007. Camelia continued their education at Rutgers University, where they completed their Ph.D. in Mathematics from 2007 to 2012.

In addition to their formal education, Camelia Pop has also obtained several certifications related to machine learning. Camelia completed courses in Sequence Models, Convolutional Neural Networks, Improving Deep Neural Networks, Structuring Machine Learning Projects, and Neural Networks and Deep Learning. These certifications were obtained from Coursera in 2017 and 2018.