58 lines
2.9 KiB
Markdown
58 lines
2.9 KiB
Markdown
I am an assistant professor in the [Department of Computer
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Sciences](https://www.cs.wisc.edu/) at the [University of
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Wisconsin--Madison](https://www.wisc.edu).
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**I am always looking for good students!**
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Previously, I was a postdoc at the [Department of Computer
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Science](https://www.cs.cornell.edu/) at [Cornell
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University](https://www.cornell.edu/), and at the [Programming Principles,
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Logic, and Verification Group](http://pplv.cs.ucl.ac.uk/welcome/) at the
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[University College London](https://www.ucl.ac.uk/). I was a graduate student in
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the [Department of Computer Science](https://cis.upenn.edu) at the [University
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of Pennsylvania](https://www.upenn.edu).
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I am funded by an NSF CAREER award and a Facebook Research award.
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## Research Interests ##
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I design methods to **formally verify** that programs are correct, especially
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programs that use **randomization**. Such programs can be easy to show correct
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on paper, but surprisingly challenging for computers to analyze. Accordingly,
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my research blends ideas from two classical areas of computer science:
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**randomized algorithms** from theoretical computer science (**TCS**) and
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**formal verification**.
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Drawing inspiration from how humans reason about randomized algorithms, we can
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build simpler and more automated verification techniques. In the past, I've
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applied this approach to properties like **accuracy**, **incentive
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compatibility**, Markov chain **mixing**, and various notions of **algorithmic
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stability**.
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A particular focus of my work has been [**differential
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privacy**](https://en.wikipedia.org/wiki/Differential_privacy), a rigorous
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definition of privacy that is currently under extensive study.
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I have investigated a variety of formal methods---such as [**type
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systems**](https://en.wikipedia.org/wiki/Type_system) and [**program
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logics**](https://en.wikipedia.org/wiki/Hoare_logic)---to verify that programs
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are differentially private.
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From a more traditional algorithms perspective, I am also interested in applying
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differential privacy to optimization, machine learning, and mechanism design.
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## Teaching ##
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- **Security and Privacy in Data Science (CS 763)**: [F20](https://pages.cs.wisc.edu/~justhsu/teaching/current/cs763/)
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- **Introduction to the Theory and Design of PL (CS 538)**: [S20](https://pages.cs.wisc.edu/~justhsu/teaching/s20/cs538/)
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- **Security and Privacy in Data Science (CS 763)**: [F19](https://pages.cs.wisc.edu/~justhsu/teaching/f19/cs763/)
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- **Introduction to the Theory and Design of PL (CS 538)**: [S19](https://pages.cs.wisc.edu/~justhsu/teaching/s19/cs538/)
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- **Topics in Security and Privacy Technologies (CS 839)**: [F18](https://pages.cs.wisc.edu/~justhsu/teaching/f18/cs839/)
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## Service ##
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- **2021** ESOP, PLMW@POPL, CSF, AAAI, COLT
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- **2020** AAAI, CSF, LAFI, WoLLIC, PLMW@POPL, OOPSLA (ERC)
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- **2019** POPL, PLMW@POPL, POST, CSF, DARS (co-chair)
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- **2018** LICS, WWW
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- **2017** FCS, TPDP, MFPS
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- **2016** PLDI (ERC)
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