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Victoria Stodden is an Associate Professor in the Daniel J. Epstein Department of Industrial and Systems Engineering at the University of Southern California. With a background in statistical methodology and data science, her research focuses on the intersection of machine learning, reproducibility, and statistical applications in various fields. She has contributed significantly to the academic community through her publications and collaborative work, emphasizing the importance of transparency and reproducibility in research. Stodden is also committed to teaching and mentoring the next generation of engineers and researchers, ensuring they are equipped with the necessary skills to navigate the complexities of modern data analytics and systems engineering. Her work is characterized by a blend of theoretical exploration and practical implementation, aiming to bridge the gap between academia and real-world applications.
Requires general GRE for all graduate degrees.