Uri Alon

Uri Alon

Postdoctoral Researcher,
Language Technologies Institute,
Carnegie Mellon University

I am a post-doc at the Language Technologies Institute (LTI) of Carnegie Mellon University, working with Prof. Graham Neubig, and a member of NeuLab.

My research interests are broad and include programming language processing (PLP), natural language processing (NLP) and deep learning in general.

I obtained a PhD in the department of Computer Science at the Technion, advised by Prof. Eran Yahav.

Previously, I served 7 years as an officer onboard a missile ship in the Israeli Navy. Later, I completed my BSc summa cum laude at the Computer Science Department at the Technion, as an alumnus of The Rothschild-Technion Scholars Program for Excellence. Between 2014-2016, I worked at Microsoft R&D center in Haifa, developing data security services for the cloud. Between June-September of 2018, I interned at Google New-York, researching neural models for speech recognition.

In addition, I hold a B.A. in Humanities.

I am happily married to Lee and father of Gur 🙂

News

September 2022 - We released a new repository for evaluation of code generation: code-bert-score, along with pretrained models of several programming languages, based on CodeBERT.

August 2022 - a new preprint: DocCoder: Generating Code by Retrieving and Reading the Docs

July 2022 - I released a new HuggingFace 🤗 transformers implementation of RetoMaton, kNN-language models and kNN-machine translation: https://github.com/neulab/knn-transformers

June 2022 - I was selected for the ACM SIGPLAN Reynolds Doctoral Dissertation Award (formerly “SIGPLAN Outstanding Doctoral Dissertation Award”)!

May 2022 - our RetoMaton paper was accepted to ICML’2022!

April 2022 - our PolyCoder paper will appear in ICLR 2022’s DL4Code and PLDI 2022’s MAPS workshops.

March 2022 - a new preprint: A Systematic Evaluation of Large Language Models of Code

February 2022 - a new preprint: Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval

January 2022 - our paper How Attentive are Graph Attention Networks? was accepted to ICLR’2022!

Publications

Preprints

Accepted Papers

PhD Thesis

  • Machine Learning for Programming Language Processing

Technical Reports

  • Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
    • Jonathan Shen, …, Uri Alon, …
    • [PDF]

Workshops

Awards

  • 2022 - Reynolds Doctoral Dissertation Award (formerly “SIGPLAN Outstanding Doctoral Dissertation Award”)
  • 2021-2022 – Rothschild Post-Doctoral Fellowship
  • 2021-2022 – Fulbright Post-Doctoral Fellowship (declined)
  • 2020 – ACM SIGPLAN Research Highlight, “code2vec: Learning Distributed Representations of Code” (POPL’2019)
  • 2019 – Jacobs Excellence Scholarship
  • 2019 – Department Funding Excellence Scholarship
  • 2018 – Department Funding Excellence Scholarship
  • 2016 – Excellent Teaching Assistant
  • 2016 – Dean’s Excellent Scholarship
  • 2016 – Alumnus of the Rothchild-Technion Program for Excellence
  • 2015 – SAMBA – CS Excellent Students

Demos

https://www.code2vec.org

code2vec (POPL'2019)

Demo

Code

https://www.code2seq.org

code2seq (ICLR'2019)

Demo

Code

https://www.AnyCodeGen.org

AnyCodeGen (ICML'2020)

Demo

Code

Service

  • Reviewer: NeurIPS ‘2022, TMLR, ICML’2022 (top 10% Best Reviewers), ICLR’2022 (Highlighted Reviewer), AIPLANS NeurIPS 2021 workshop, ICML’2021 (top 10% Best Reviewers), ICLR’2021, NeurIPS’2020, ICLR’2020
  • Program Committee: MAPS 2022, Deep Learning for Code ICLR’22 workshop, PLDI’2021, NeurIPS’2020 CAP workshop, AIDM’20, AIDM’19
  • Area Chair: Learning on Graphs ‘2022