Osbert Bastani

Osbert Bastani

Research Assistant Professor
University of Pennsylvania
470 Levine Hall
obastani[AT]seas.upenn.edu
[CV]

about

I am a research assistant professor at the Department of Computer and Information Science at the University of Pennsylvania. Previously, I completed my Ph.D. at Stanford advised by Alex Aiken, and spent a year as a postdoc at MIT working with Armando Solar-Lezama.


research

I am broadly interested in machine learning and programming languages research. Recently, I have been working on developing algorithms for ensuring correctness of machine learning models. These models are increasingly used in real world systems where failures can be catastrophic, such as autonomous vehicles, medical diagnosis, and legal decision making. For such applications, there are many desirable correctness properties that machine learning models should satisfy, including safety, fairness, causality, and robustness. My work aims to address the following challenges:

  • What correctness properties should machine learning models satisfy?
  • How can we reason about the correctness of existing machine learning models?
  • Can we learn machine learning models for which correctness is easy to verify?


publications

Osbert Bastani, Lazaro Clapp, Saswat Anand, Rahul Sharma, Alex Aiken. Eventually Sound Points-To Analysis with Missing Code. In submission. [arXiv]

Osbert Bastani, Carolyn Kim, Hamsa Bastani. Interpreting Blackbox Models via Model Extraction. In submission. [arXiv]

Osbert Bastani, Yewen Pu, Armando Solar-Lezama. Verifiable Reinforcement Learning via Policy Extraction. NIPS 2018. [arXiv] [presentation] [poster] [code]

Osbert Bastani, Rahul Sharma, Alex Aiken, Percy Liang. Active Learning of Points-To Specifications. PLDI 2018. [paper] [extended] [arXiv] [presentation] [code]

Yu Feng, Ruben Martins, Osbert Bastani, Isil Dillig. Program Synthesis using Conflict-Driven Learning. PLDI 2018 (Distinguished Paper). [paper] [arXiv]

Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori, Antonio Criminisi. Measuring Neural Net Robustness with Constraints. DARS Workshop 2018 (Invited Paper). [paper] [presentation]

Osbert Bastani. Beyond Deductive Inference in Program Analysis. Ph.D. Thesis. [thesis] [defense]

Osbert Bastani, Carolyn Kim, Hamsa Bastani. Interpretability via Model Extraction. FAT/ML Workshop 2017. [paper] [arxiv] [poster] [code]

Osbert Bastani, Rahul Sharma, Alex Aiken, Percy Liang. Synthesizing Program Input Grammars. PLDI 2017. [paper] [extended] [arXiv] [presentation] [code]

Yu Feng, Osbert Bastani, Ruben Martins, Isil Dillig, Saswat Anand. Automated Synthesis of Semantic Malware Signatures using Maximum Satisfiability. NDSS 2017. [paper] [arXiv]

Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori, Antonio Criminisi. Measuring Neural Net Robustness with Constraints. NIPS 2016. [paper] [arXiv] [poster] [code]

Lazaro Clapp, Osbert Bastani, Saswat Anand, Alex Aiken. Minimizing GUI Event Traces. FSE 2016. [paper]

Osbert Bastani, Saswat Anand, Alex Aiken. An interactive approach to mobile app verification. MobileDeLi Workshop 2015 (Invited Paper). [paper]

Osbert Bastani, Saswat Anand, Alex Aiken. Interactively verifying absence of explicit information flows in Android apps. OOPSLA 2015. [paper] [presentation]

Osbert Bastani, Saswat Anand, Alex Aiken. Specification inference using context-free reachability. POPL 2015. [paper] [presentation]

Osbert Bastani, Christopher Hillar, Dimitar Popov, Maurice Rojas. Randomization, sums of squares, near-circuits, and faster real root counting. Contemporary Mathematics 556 (2011): 145-166. [paper]