46 lines
2.2 KiB
Markdown
46 lines
2.2 KiB
Markdown
I am a postdoc in 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/), hosted by [Nate
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Foster](http://www.cs.cornell.edu/~jnfoster/), [Bobby
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Kleinberg](http://www.cs.cornell.edu/~rdk/), and [Dexter
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Kozen](http://www.cs.cornell.edu/~kozen/).
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**I will be joining the University of Wisconsin--Madison in Fall 2018 as an
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assistant professor. Looking for good students!**
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Previously, I was a postdoc in the [Programming Principles, Logic, and
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Verification Group](http://pplv.cs.ucl.ac.uk/welcome/) at the [University
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College London](https://www.ucl.ac.uk/), hosted by [Alexandra
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Silva](http://www.alexandrasilva.org/). I was a graduate student in the
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[Department of Computer Science](https://cis.upenn.edu) at the [University of
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Pennsylvania](https://www.upenn.edu), associated with the [Theory
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Group](http://theory.cis.upenn.edu), the [PL
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Club](https://www.cis.upenn.edu/~plclub/), and the [Privacy
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Group](http://privacy.cis.upenn.edu). I was very fortunate to be co-advised by
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[Benjamin Pierce](https://cis.upenn.edu/~bcpierce) and [Aaron
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Roth](https://cis.upenn.edu/~aaroth).
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## Research Interests ##
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My research spans two classical areas of computer science: **algorithms** from
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theoretical computer science (commonly known as **TCS**) and **formal
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verification**. My work has mostly centered on [**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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From the verification side, I investigate 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. More generally, I consider formal verification for
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properties of randomized algorithms, including **incentive compatibility**,
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Markov chain **mixing**, and various notions of **algorithmic stability**. From
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the algorithms side, I apply differential privacy to optimization, machine
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learning, and mechanism design.
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## Service ##
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- **LICS 2018** PC
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- **WWW 2018** PC
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- **FCS 2017** PC
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- **TPDP 2017** PC
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- **MFPS 2017** PC
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- **PLDI 2016** ERC
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