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Fabian Zaiser

PhD student in Computer Science

University of Oxford

About me

I am a PhD Student in Computer Science at the University of Oxford, supervised by Luke Ong. Until recently, I was also a Stipendiary Lecturer at Merton College, Oxford.

My research interests are in Programming Language Theory and Formal Verification. More specifically, my PhD research is about Probabilistic Programming: expressing statistical models as programs and automating Bayesian inference on them. I want to advance the techniques to analyze and verify the properties of probabilistic programs.

Besides my research, I have done a lot of teaching in the past few years, part of it as a Stipendiary Lecturer. I am also a big fan of the Rust programming language and have contributed a few features to its compiler. In the summer of 2022, I interned in the Kani team at AWS, which works on the verification of Rust programs.

Interests

  • Programming Language Theory
  • Probablilistic Programming
  • Formal Methods
  • The Rust programming language

Education

  • PhD in Computer Science, since 2019
    University of Oxford
  • MSc in Computer Science, 2018–2019
    University of Oxford
  • MSc in Mathematics, 2015–2018
    University of Bonn
  • BSc in Mathematics, 2012–2015
    University of Bonn
  • BSc in Computer Science, 2012–2015
    University of Bonn

Publications

Nonparametric Hamiltonian Monte Carlo

Carol Mak, Fabian Zaiser, Luke Ong
ICML • 2021

The approximation ratio of the 2-Opt Heuristic for the metric Traveling Salesman Problem

Stefan Hougardy, Fabian Zaiser, Xianghui Zhong
Operations Research Letters • 2020

The Extended Theory of Trees and Algebraic (Co)datatypes

Stefan Hougardy, Fabian Zaiser, Xianghui Zhong
VPT/HCVS at ETAPS • 2020

Talks

Exact Inference for Discrete Probabilistic Programs via Generating Functions

LAFI workshop at POPL 2023 • 15 Jan 2023

Exact Inference for Discrete Probabilistic Programs via Generating Functions

ANR PPS meeting 2023 • 5 Jan 2023

Guaranteed Bounds for Posterior Inference in Universal Probabilistic Programming

PLDI 2022 • 16 Jun 2022

Rigorous Bounds for Posterior Inference in Universal Probabilistic Programming

Logic of Probabilistic Programming at CIRM 2022 • 31 Jan 2022

Rigorous Approximation of Posterior Inference for Probabilistic Programs

LAFI workshop at POPL 2022 • 16 Jan 2022

The Extended Theory of Trees and Algebraic (Co)datatypes

SMT workshop at CAV 2021 • 18 Jul 2021

The Extended Theory of Trees and Algebraic (Co)datatypes

HCVS workshop at ETAPS 2021 • 28 Mar 2021

Teaching

Teaching Assistant (Professional Masters Programme in Software Engineering, Oxford)

  • Algorithmics (spring 2021, summer 2021, spring 2022 & fall 2022): week-long course

Stipendiary Lecturer (Merton College, Oxford)

  • Models of Computation (fall 2021)
  • Discrete Mathematics (fall 2021)
  • Functional Programming (fall 2021)
  • Design and Analysis of Algorithms (spring 2022)
  • Algorithms and Data Structures (spring 2022)
  • Continuous Mathematics (spring 2022)

Class teaching and marking

  • Department of Computer Science, Oxford
    • Lambda Calculus and Types (spring 2021)
    • Bayesian Statistical Probabilistic Programming (fall 2020)
    • Imperative Programming III practicals (programming classes, summer 2020)
    • Imperative Programming I & II practicals (programming classes, spring 2020)
    • Principles of Programming Languages practicals (programming classes, fall 2019)
  • University of Toronto
    • Calculus 1 (winter 2015/2016 and spring 2016)
  • University of Bonn
    • Algorithms & Computational Complexity (winter 2016/2017)
    • Analysis (summer 2015)
    • Algorithmic Mathematics programming classes (winter 2014/15)
    • Analysis II (summer 2014)

Contact