Vikram is lecturer in the Computer Science department at Princeton University. He is interested in fairness and interpretability in machine learning, and how it applies to visual systems. He has worked primarily in constructing better datasets (either real or synthetic) and understanding and evaluating interpretability methods for convolutional neural networks. 

He is passionate about teaching and learning, and works to build classrooms that allow for students to learn by doing while creating an inclusive space. He has taught courses on AI/ML, computer vision, Python at Princeton's FSI, AI4All, Princeton Learning Cooperative and Department of Computer Science, among others.

He earned Ph.D. in Computer Science from Princeton in 2023, advised by Prof. Olga Russakovsky.