About me

I'm a PhD student in the Programming Languages Research Group at University of Bristol, supervised by Meng Wang and Roly Perera. My current research investigates the implementation and application of algebraic effects and probabilistic programming languages. My other interests include functional programming (in particular, Haskell), type-level programming, embedded domain-specific languages, and recursion schemes.

Research

I'm currently exploring the abstraction of algebraic effects and effect handlers for probabilistic programming language design. At the moment, I'm working out how abstract operations and effect handlers can be used as a type-safe, modular design pattern for programmable inference. In recent work, I used this approach to develop an implementation of probabilistic models as first-class citizens.

Other projects include fleshing out a compositional approach of using recursion schemes to implement neural networks; in particular, I show how neural networks can be represented as fixed-points of recursive data structures, and forward and back propagation as folds and unfolds over these structures.

Papers, etc.

Mar, 2023 Effects and Effect Handlers for Programmable Inference
                  M.Nguyen, R.Perera, M.Wang, S.Ramsay

Jan, 2023 Towards type-driven data-science in Idris
                  O.Kammar, K.Marek, M.Nguyen, M.Steuwer, J.Walters, R.Wright
^{LAFI ‘23}
Sep, 2022 Folding over Neural Networks (preprint, proceedings)
                  M.Nguyen, N.Wu
^{MPC ‘22}
Sep, 2022 Modular Probabilistic Models via Algebraic Effects (preprint, proceedings, repository)
                  M.Nguyen, R.Perera, M.Weng, N.Wu
^{ICFP ‘22}
Jan, 2022 Linked visualisations via Galois dependencies (preprint, proceedings, repository)
                  R.Perera, M.Nguyen, T.Petricek, M.Weng
^{POPL ‘22}
Sep, 2021 Composable, Modular Probabilistic Models (extended abstract, poster)
                  M.Nguyen, R.Perera, M.Weng
^{ICFP ‘21 Student Research Competition}
Aug, 2021 Composable, Modular Probabilistic Models (paper)
                  M.Nguyen, R.Perera, M.Weng
^{IFL ‘21}
Jun, 2019 Modelling Neural Networks with Recursion Schemes (dissertation, poster, repository)
                  M.Nguyen, N.Wu
^{Masters Dissertation @ University of Bristol}

Talks

Sep, 2022 Folding over Neural Networks (slides)
^{MPC ‘22}
Sep, 2022 Modular Probabilistic Models via Algebraic Effects (video, slides)
^{ICFP ‘22}
May, 2022 Modular Probabilistic Models via Algebraic Effects (slides)
^{PLInG Seminar @ University of Edinburgh}
Sep, 2021 Composable, Modular Probabilistic Models (video, slides)
^{ICFP ‘21 Student Research Competition}
Sep, 2021 Composable, Modular Probabilistic Models (video, slides)
^{IFL ‘21}

Work

Jun '22 - Sep '22
Research Intern: Dependently typed probabilistic programming for Idris2 (repositories)
with Ohad Kammar @ University of Edinburgh

Teaching

2019 - 2022
I give seminars and guest lectures to the Programming Languages Research Group and CS undergraduates @ University of Bristol.
2020 - 2021
Primary supervisor for a 4th year CS student in their masters dissertation: Deep Learning Architectures As Pure Functions @ University of Bristol.
2017 - 2022
Teaching assistant for the Functional Programming, Language Engineering, and Advanced Topics in Programming Languages units @ University of Bristol.

Awards

2021 ICFP '21 ACM Student Research Competition, 1st Place
2019 Bloomberg Award - Best Machine Learning Paper, University of Bristol
2018 Graphcore Award - Best Group Project, University of Bristol
2017 Netcraft Award - Top Ten Achieving CS Students, University of Bristol

Minh Nguyen