Pedro Sandoval-Segura

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I am currently a PhD student in the Department of Computer Science at the University of Maryland at College Park, where I am advised by Prof. David Jacobs and Prof. Tom Goldstein. In May 2019, I earned my bachelor's degree in Computer Science and Mathematics from Harvey Mudd College. In May 2021, I received my master's degree in Computer Science from the University of Maryland. I am broadly interested in computer vision and deep learning research. Lately, my research focuses on adversarial examples and the benefits of adversarial training.

I am fortunate to have been selected as an Amazon Lab126 Diversity in AI Fellow for the 2021-2023 academic years.

In my free time, I enjoy running, building physical computing projects, and developing apps for iOS.


  1. Sandoval-Segura, Singla, Geiping, Goldblum, Goldstein, Jacobs. "Autoregressive Perturbations for Data Poisoning". Advances in Neural Information Processing Systems 36 (NeurIPS), 2022. [arXiv:2206.03693]

  2. Sandoval-Segura, Singla, Fowl, Geiping, Goldblum, Jacobs, Goldstein. "Poisons that are learned faster are more effective". In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2022. [CVF Open Access]

  3. Bashir, Montañez, Sehra, Sandoval-Segura, Lauw. "An Information-Theoretic Perspective on Overfitting and Underfitting". In Australasian Joint Conference on Artificial Intelligence (AJCAI), 2020. [arXiv:2010.06076]

  4. Sandoval-Segura, Lauw, Bashir, Shah, Sehra, Macias, Montañez. "The Labeling Distribution Matrix (LDM): A Tool for Estimating Machine Learning Algorithm Capacity". 12th International Conference on Agents and Artificial Intelligence (ICAART 2020), 2020. [arXiv:1912.10597]

  5. Drissi, Sandoval, Ojha, Medero. "Harvey Mudd College at SemEval-2019 Task 4: The Clint-Buchanan Hyperpartisan News Detector". In Proceedings of The 13th International Workshop on Semantic Evaluation (SemEval), 2019. [arXiv:1905.01962]

  6. Drissi, Watkins, Khant, Ojha, Sandoval, Segev, Weiner, Keller. “Programming Language Translation using a Grammar-Driven Tree-to-Tree Model”. ICML Workshop on Neural Abstract Machines and Program Induction v2 (NAMPI), 2018. [arXiv:1807.01784]

Other Writing


CMSC 421: Introduction to Artificial Intelligence (Spring 2021), Graduate Teaching Assistant, University of Maryland at College Park

CMSC 421: Introduction to Artificial Intelligence (Fall 2020), Graduate Teaching Assistant, University of Maryland at College Park

CMSC 436: Programming Handheld Systems (Fall 2019), Graduate Teaching Assistant, University of Maryland at College Park

CS 81: Computability and Logic (Spring 2019), Grader and Tutor, Harvey Mudd College

MATH 187: Operations Research (Spring 2019), Grader, Harvey Mudd College

Past Projects


psando AT cs DOT umd DOT edu