matthewfl

matthewfl 26th January 2024 at 4:14pm

Matthew Francis-Landau

I am Matthew, I completed my Ph.D. in February 2024 at JHU CLSP. I was advised by Jason Eisner.

I am currently on the job market and looking for jobs in both industry and academia.

I was working on the implementation of Dyna, a new programming language for quickly implementing new NLP and ML algorithms.

Contact me
Blog
Papers
Software
Teachings

Research Summary

matthewfl 22nd December 2021 at 8:53pm

My research is focused on new approaches for implementing declarative logic programming using a relational algebra that is manipulated (executed) via term rewriting. This approach to logic programming can simultaneously support features such as backwards chaining (Prolog-style of execution), forward chaining (Datalog-style of execution), infinite relations, delayed constraints, prototype-based inheritance, memoization, and weighted rules. While each of these features has previously appeared in other programming languages, they have not appeared all together at the same time in a single programming language. Having all of these features together in a single programming language (Dyna) makes a powerful programming language. Dyna can, in turn, represent many machine learning algorithms using only a few lines of code. However, this combination of features has also makes Dyna very challenging to implement as existing techniques to implement logic programming can not be directly applied.

Papers

matthewfl 26th January 2024 at 2:30am

Declarative Programming via Term Rewriting - Matthew Francis-Landau Ph.D. dissertation at Johns Hopkins 2024
Evaluation of Logic Programs with Built-Ins and Aggregation: A Calculus for Bag Relations - Matthew Francis-Landau, Tim Vieira, Jason Eisner WRLA 2020
Exact and/or Fast Nearest Neighbors - Matthew Francis-Landau, Benjamin Van Durme
MFST: A Python OpenFst Wrapper With Support for Custom Semirings and Jupyter Notebooks - Matthew Francis-Landau
Dyna: Toward a Self-Optimizing Declarative Language for Machine Learning Applications - Tim Vieira, Matthew Francis-Landau, Nathaniel Wesley Filardo, Farzad Khorasani, Jason Eisner MAPL 2017.
Fine-grained parallelism in probabilistic parsing with Habanero Java - Matthew Francis-Landau, Bing Xue, Jason Eisner, Vivek Sarak SC-IA³ 2016.
Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks - Matthew Francis-Landau, Greg Durrett, and Dan Klein. NAACL 2016.

Other undergraduate research

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Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks
Contact
Declarative Programming via Term Rewriting
Dyna
Dyna: Toward a Self-Optimizing Declarative Language for Machine Learning Applications
Evaluation of Logic Programs with Built-Ins and Aggregation: A Calculus for Bag Relations
Exact and/or Fast Nearest Neighbors
Fine-grained parallelism in probabilistic parsing with Habanero Java
matthewfl
MFST: A Python OpenFst Wrapper With Support for Custom Semirings and Jupyter Notebooks
Papers
Research Summary
Self Image
Software
Teaching