PhD Student in Computer Science

ETH Zürich

Biography

I’m a PhD student in Computer Science with Professor Ryan Cotterell at ETH Zürich, supported by a Google PhD Fellowship. I am passionate about the general application of statistics and information theory to natural language processing. A large portion of my research in the last years has been on natural language generation—specifically, on decoding methods for probabilistic models. In my free time, I go rock climbing, trail running, and just about everything that falls in between the two. I am a proud member of the Akademischer Alpenclub Zürich.

I have had the privilege of serving as the advisor for several MSc students during the writing of their theses. Some of these theses have turned into published works.

  • Luca Malagutti: Divergence functions for Natural Language Generation
  • Liam van der Poel: Mutual Information for Identifying and Preventing Hallucinations in Abstractive Summarization (EMNLP Paper)
  • Andy Buinovskij: Advanced Smoothing Techniques for Training Neural Language Model
  • Samuel Pullely: Text Detoxification using Pre-Trained Language Models and Plug-and-Play Generation Methods
  • Franz Knobel: Probing Language Models With Topic Models
  • Gian Wiher: A Taxonomy of Decoding Schemes for Language Generation Models (TACL Paper)
  • Luca Disse: Exploring the Inductive Biases of Sparsity-Inducing Learning Algorithms for Language Modeling
  • Afra Amini: Causal Probing for Gender Differences in Contextual Word Representations (TACL Paper)
  • Martina Forster: Search Errors in Morphological Inflection Generation Systems (EACL Paper)
  • Stefan Lasov: Effects of Sparse Attention on Model Interpretability (EMNLP Paper)
Interests
  • Natural Language Generation
  • Statistical Methods for NLP
  • Information Theory
  • Psycholinguistics
Education
  • MSc in Computational and Mathematical Engineering, 2018

    Stanford University

  • BSc in Mathematical and Computational Science, 2017

    Stanford University

Experience

 
 
 
 
 
PhD Student
ETH Zürich
February 2020 – Present Zürich, Switzerland
PhD student in the Computer Science Department (Machine Learning Institute). Helped to design and teach the Natural Language Processing course as well as the Large Language Models course.
 
 
 
 
 
Research Scientist Intern
DeepMind
March 2022 – August 2022 London, UK
Intern with the Language Team, working with Adhi Kuncoro, Wojciech Stokowiec, and Laura Rimell.
 
 
 
 
 
Research Assistant
ETH Zürich
January 2019 – February 2020 Zürich, Switzerland
Research assistant in the Advanced Software Technologies Lab under Professor Zhendong Su. Area of focus was on building systems for automatically testing machine translation systems.
 
 
 
 
 
Research Assistant
SLAC National Accelerator Laboratory
January 2018 – June 2018 Stanford, California
Research assistant with the Linac Coherent Light Source lab working with scientists to modify and enhance code base for analysis of electron pulse x-ray images generated at SLAC’s new hard x-ray free-electron laser.
 
 
 
 
 
Course Assistant
Stanford University Computer Science Department
September 2017 – December 2017 Stanford, California
Course assistant for CS102 Big Data- Tools and Techniques, Discoveries and Pitfalls. Taught students basic data wrangling and analysis along with visualization techniques using multiple software platforms.
 
 
 
 
 
Data Science Intern
Akamai Technologies
September 2016 – June 2017 Mountain View, California
Part-time internship during academic school year. Projects included integrating AWS ElastiCache into infrastructure of the Data Science Team’s services and refactoring libraries to support multiple databases.
 
 
 
 
 
Software Engineering Intern
Cisco Systems; Tendril Networks; SAP Hybris
June 2015 – September 2017 San Jose, California; Boulder, Colorado
Summer software engineering internships 2015-2017

Recent & Upcoming Talks

  • 18/5/2023: Invited talk at Tel Aviv University’s NLP Seminar

  • 21/4/2023: Invited talk at University of Edinburgh ILCC Seminar

  • 26/9/2022: Invited lecture at Johns Hopkins University Artificial Agents course

  • 6/5/2022: Invited talk at Google Research Machine Translation Team Reading Group

  • 14/3/2022: Invited talk at IST-Unbabel Seminar

  • 10/8/2021: Invited talk at UT Austin’s NLP Seminar

  • 14/7/2021: Invited talk at Berkeley’s NLP Seminar

  • 16/6/2021: Invited talk at MIT’s Computational Psycholinguistics Lab