me

Pedro Sandoval-Segura

GitHub / Medium / LinkedIn / UMD / Google Scholar / Semantic Scholar / CV

Hello!

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. Tom Goldstein and Prof. David Jacobs. In May 2019, I earned my bachelor's degree in Computer Science and Mathematics from Harvey Mudd College. I am broadly interested in computer vision and deep learning. My research has explored vulnerabilities of neural networks including adversarial examples and dataset poisoning. I am interested in how characteristics of image datasets impact learning.

In my free time, I enjoy running and building physical computing projects.

Publications

  1. Singla, Sandoval-Segura, Goldblum, Geiping, Goldstein. "A Simple and Efficient Baseline for Data Attribution on Images". NeurIPS Workshop on Attributing Model Behavior at Scale (ATTRIB), 2023. [arXiv:2311.03386][Code]

  2. Sandoval-Segura, Singla, Geiping, Goldblum, Goldstein. "What Can We Learn from Unlearnable Datasets?". Advances in Neural Information Processing Systems 37 (NeurIPS), 2023. [arXiv:2305.19254][Code]

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

  4. 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]

  5. 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]

  6. 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]

  7. 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]

  8. 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

Teaching

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

Contact

psando AT cs DOT umd DOT edu