Una-May O’Reilly
Principal Research Scientist, Computer Science and Artificial Intelligence Laboratory
Who they work with
Categories
Una-May O’Reilly is founder and leader of the AnyScale Learning For All (ALFA) group at Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory. ALFA focuses on Artificial Adversarial Intelligence through machine learning and evolutionary algorithm lenses. She received the EvoStar Award for Outstanding Achievements in Evolutionary Computation in Europe in 2013. She was a Fellow of the International Society of Genetic and Evolutionary Computation, now ACM SIGEVO, which transferred to special recognition for contributions. She has served as Vice-Chair of ACM SIGEVO. She is the area editor for Data Analytics and Knowledge Discovery for Genetic Programming and Evolvable Machines (Kluwer), and ACM Transactions on Evolutionary Learning and Optimization, and editor for Evolutionary Computation (MIT Press).
Selected Publications
- Gan, C., Jia, J., Srikant, S., Chang, S., Liu, S., Mitrovska, T., O’Reilly, U-M. (2023). CLAWSAT: Towards Both Robust and Accurate Code Models. IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER).
- Wang, M., Srikant, S., Samak, M., O’Reilly, U-M. (2023). RaceInjector: Injecting Races to Evaluate and Learn Dynamic Race Detection Algorithms. ACM SIGPLAN Workshop on the State Of the Art in Program Analysis (SOAP).
- Srikant, S., Lipkin, B., Ivanova, A. A., Federenko, E., O’Reilly, U-M. (2022). Convergent representations of computer programs in human and artificial neural networks. Conference on Neural Information Processing Systems (NeurIPS).
- Srikant, S., Chang, S., Fan, Q., Liu, S., Mitrovska, T., Zhang, G., O’Reilly, U-M. (2021). Generating Adversarial Computer Programs using Optimized Obfuscations. International Conference on Learning Representations (ICLR).
- Al-Dujaili, A., O’Reilly, U-M. (2020). Sign Bits Are All You Need For Black-box Attacks. International Conference on Learning Representations (ICLR).
- Liu, S., Lu, S., Chen, X., Feng, Y., Xu, K., Al-Dujaili, A., Hong, M., O’Reilly, U-M. (2020). Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks. International Conference on Machine Learning (ICML).