She has won several research awards from IEEE conferences and the engineering community, including the Best Paper Award at the 2019 IEEE International Workshop on Machine Learning for Signal Processing, the NJ Tech Council STEM Innovator to Watch Award in 2019, and the IEEE Philadelphia Section Benjamin Franklin Key Award in 2021. Dr. Dera has served as a member of the IEEE Signal Processing Society and the IEEE Computational Intelligence Society, as well as a member of ACM SIGHPC. She is also an NVIDIA Deep Learning Institute University Ambassador.

Dr. Dera specializes in robust and trustworthy modern machine learning solutions for real-world applications, including healthcare, remote sensing, and surveillance systems. Her research focuses on developing innovative techniques to ensure the robustness, safety, adaptability, and reliability of AI systems by integrating Bayesian theory and statistical signal processing foundations into modern machine learning frameworks. Her work highlights the intricate connections between Bayesian uncertainty learning in machine learning models and their robustness, self-awareness, and adaptability to dynamically changing environments and system failures. She publishes in the areas of trustworthy, reliable, and explainable machine learning, signal and image processing, and optimization.